RU2813679C1 - Method for analysis and/or prediction based on network of sensors and sensor remote monitoring device - Google Patents

Abstract

FIELD: control and measuring equipment.

SUBSTANCE: invention relates to a method for analysis and/or prediction based on a network of sensors, to a sensor remote monitoring device and an external network of sensors for protection against natural hazards. Method of analysis and/or prediction based on a network of sensors for protection against natural hazards includes steps of the method: receiving and collecting electronic data of sensors from distributed sensor modules of an external network of sensors in an external analysis and/or prediction unit, wherein the sensor data include at least external corrosion measurement data, impact sensor data and/or cable tension sensor data, and wherein the sensor data include at least tropospheric parameters measurement data, and wherein each external corrosion measurement data set is associated with at least one tropospheric parameters data set; storing the obtained sensor data of the external sensor network in the storage device of the external analysis and/or prediction unit; analysis of the obtained data of sensors of the external network of sensors to identify the risk of a hazardous natural phenomenon in the corresponding areas of application of sensor modules of the external network of sensors by means of an external analysis and/or prediction unit, wherein the analysis for detecting the risk of a hazardous natural phenomenon directly receives at least one additional information on the application area, which differs from the measurement data of external corrosion and measurement data of tropospheric parameters and providing the identified by means of the external unit of analysis and/or prediction of the risk of a hazardous natural phenomenon to a group of users. Based on the identified risk of a hazardous natural phenomenon, a maintenance plan for the application area and/or after the impact detection is made, and/or after detecting a filling event, depending on the degree and/or type of impact and/or filling event, a maintenance or immediate repair order is initiated.

EFFECT: possibility of obtaining, processing and/or converting into actions and/or instructions for action of comprehensive and/or significant information on risks of natural hazards, primarily in one or more application zones.

42 cl, 7 dwg

Description

State of the art

The invention relates to a method of analysis and/or forecasting according to claim 1 of the formula, to a sensor remote monitoring device according to the restrictive part of claim 21 of the formula, to an external network of sensors according to claim 43 of the formula, and to a structure according to claim 44 of the formula .

Previously, networks of sensors (sensor networks) were proposed that monitor, among other things, the development of corrosion inside structures, for example in pipelines, see US 7,526,944 B2, or in reinforced concrete, see US 8,886,468 B1. In the field of protection against natural hazards, the important topic of corrosion has so far received insufficient attention.

First of all, it is an object of the invention to provide a standard method and/or a standard device with advantageous properties regarding the reflection of natural hazards and/or protection from natural hazards. According to the invention, the problem is solved by means of the features of claims. 1, 21, 43 and 44 of the claims, and preferred embodiments and additional embodiments of the invention can be gleaned from additional claims.

Advantages of the invention

A method of analysis and/or forecasting based on a network of sensors for protection against hazardous natural phenomena is proposed, which includes at least the following method steps:

- receiving and collecting in an external unit the analysis and/or forecasting of electronic sensor data from distributed sensor modules of an external network of sensors,

wherein the sensor data includes at least external corrosion measurement data and/or rope tension sensor data, and wherein the sensor data includes at least troposphere measurement data, and wherein with each set of external corrosion measurement data , primarily geographically, at least one set of data measuring tropospheric parameters is correlated,

- storing the received data from sensors of the external network of sensors in, first of all, a centrally or distributedly located storage device of an external analysis and/or forecasting unit, for example, first of all, in a centrally or distributedly located electronic (volatile or non-volatile) data carrier of an external analysis unit and/or forecasting or, above all, in a centralized or distributed magnetic data carrier of an external analysis and/or forecasting unit,

- analysis of the received, and above all stored, data from sensors of the external network of sensors to identify the risk of a dangerous natural phenomenon in the relevant areas of application of sensor modules of the external network of sensors using an external analysis and/or forecasting unit, and the analysis to identify the risk of a dangerous natural phenomenon directly receives at least one additional information about the application area that differs from the external corrosion measurement data and the troposphere measurement data, and

- provision of the risk of a dangerous natural phenomenon identified through an external unit of analysis and/or forecasting, primarily to an authorized user group.

In this way, it can be possible to obtain, process and/or convert into actions and/or instructions for action comprehensive and/or relevant information about the risks of natural hazards, primarily in one or more application areas. An advantage is that an external sensor network, which primarily also collects data from various types of sensors, can provide particularly accurate and reliable recording and/or monitoring of one or more application areas. In a sensor network-based analysis and/or prediction process, primarily collected data from distributed sensor modules is jointly analyzed, preferably automatically and/or by computer. In a sensor network-based analysis and/or forecasting method, forecasts of the future development of sensor data or monitored application areas as a whole are generated primarily based on the analysis of collected data from distributed sensor modules.

By “hazardous natural phenomena” we should understand, first of all, geophysical hazardous natural phenomena. Natural hazards should be understood, first of all, as natural, preferably geological, physical and/or geophysical phenomena that can have a negative impact on people, animals or structures. For example, a natural hazard may be a landslide, landslide, debris flow, avalanche, erosion, as well as a natural process, such as corrosion, especially atmospheric corrosion, affecting the stability of a structure, at least part of a structure, or also just a potential possibility of (atmospheric) corrosion in a given area. The term “risk of a natural hazard” in this context can be represented, for example, by an assessment of the risk of one of the above-mentioned phenomena occurring, first of all, before the installation of a protective device or in the presence of a protective device against a hazardous natural phenomenon, a risk assessment based on the state of the protective device against a hazardous natural phenomenon a natural phenomenon and/or structure, or a risk forecast, for example, a forecast of the service life of a protective device against a hazardous natural phenomenon and/or structure. Preferably, “risk of natural hazards” should be understood as the risk of corrosion, the risk of rockfall and/or the risk of landslides.

First of all, by “external sensor network” we mean a sensor network comprising (exclusively) remote sensor modules, preferably located outside structures or other enclosed volumes such as pipelines or the like, preferably exposed to the open atmosphere (external atmosphere) . First of all, by “outdoor sensor network” we mean a network of open air sensors and/or a network of sensors exposed to the external atmosphere and measuring parameters of the external atmosphere or effects caused by the external atmosphere. By “external analysis and/or forecasting unit” is meant, first of all, a data processing device or a data processing network, for example a computer or a computer network (for example, cloud), having at least one processor, at least one memory device (RAM , ROM, etc.), as well as at least one work program called by the processor from the storage device. First of all, the external analysis and/or prediction unit is at least partially separated from the sensor modules of the external sensor network. First of all, the external analysis and/or forecasting unit is located at a distance from the sensor modules of the external sensor network, preferably at least more than one kilometer. First of all, an external analysis and/or forecasting unit is provided for receiving, collecting, analyzing and/or providing sensor data from various sensor modules of the external sensor network, preferably from sensor modules of the external sensor network associated with different application areas. For example, the external analysis and/or forecasting unit can be implemented as a central computer center or distributed computer network (keyword “cloud computing”), which receives, collects, analyzes and/or provides data from a globally distributed external network of sensors or data multiple outdoor sensor networks distributed around the world. First of all, an external analysis and/or prediction unit is provided for wireless reception of electronic sensor data measured by sensor modules from an external sensor network. An external analysis and/or prediction unit is specifically provided for storing the acquired sensor data in a (central or distributed) storage device. The external analysis and/or prediction unit is primarily provided for receiving raw sensor data and/or sensor data already pre-analyzed in sensor modules. By “intended” we mean, first of all, specially programmed, designed and/or equipped. By saying that an object is provided for a given function, it is to be understood, first of all, that the object performs and/or realizes this given function, at least in a state of use and/or in an operating state.

By “external corrosion measurement data” we mean, first of all, measurement data that allows conclusions to be drawn about corrosion caused by the external atmosphere. By “external corrosion measurement data” we mean, first of all, corrosion measurement data in the open air. For example, “external corrosion measurement data” is measured by measuring a corrosion current that is generated, for example, as a result of corrosion of the measuring device by exposure to the external atmosphere. First of all, the external corrosion measurement data is measured by an external corrosion sensor, especially an outdoor corrosion sensor of the sensor module. By “rope tension sensor data” we mean, first of all, measurement data that shows at least the tension force of the rope, especially the tension force applied to the rope, especially to the wire rope of the structure, especially the intercepting and/ or ensuring the stability of the structure. The rope tension sensor data may be provided primarily for detecting a structure impact, a structure impact force, a structure integrity condition (keyword “mudflow barrier”), or the like. The term “impact sensor data” should be understood primarily as measurement data that indicates at least one impact of an impact body on a structure, primarily an intercepting structure. It can be assumed that the shock sensor data can be detected based on the same measurement signal as the rope tension sensor data. By “tropospheric parameter measurement data” we mean, first of all, measurement data that allows conclusions to be drawn about at least one tropospheric parameter, primarily the tropospheric sensor module surrounding it. “Troposphere measurement data” may be represented, for example, by temperature, humidity, precipitation, solar radiation, wind speed, wind direction, air pressure, dew point and the like, and/or also by air pollution data, measurement data contained in small quantities of gases (for example, sulfur or similar elements in volcanic zones), ozone measurement data, aerosol concentration measurement data, aerosol composition measurement data, OH measurement data, pH measurement data, salt concentration measurement data, or the like. Preferably, the set of tropospheric measurement data, especially the sensor module, simultaneously includes at least two, preferably at least three, and particularly preferably more than three, different types of tropospheric measurement data. The term “distributed” should be understood primarily as distributed in a distributed manner across an application area and/or distributed in a distributed manner across multiple application areas.

The fact that the external corrosion measurement data set is related to the troposphere measurement data set should be understood, first of all, as the fact that the external corrosion measurement data set and the troposphere measurement data set are logically related to each other. Preferably, the tropospheric measurement data set is geo-referenced to the external corrosion measurement data set, in particular geographically referenced such that both measurement data sets are recorded in close proximity to each other, for example at a distance of no more than 10 cm, preferably no more than 25 cm , more preferably no more than 1 m, even more preferably no more than 10 m, and especially preferably no more than 100 m. The term “application area” should be understood primarily as a structure, a set of structures, a protective device against a hazardous natural phenomenon and/or location , such as a slope or the like. Additional information about the application area may be provided by any information other than the external corrosion measurement data and the tropospheric parameter measurement data, among others, for example, another set of measurement data or also a characteristic of the structure and/or protective means against a natural hazard, such as e.g. , the thickness of the anti-corrosion layer of a part of the structure, the type of structure and/or protective means against a dangerous natural phenomenon or also local topography.

The identified risk of a natural hazard is provided to a group of users, primarily in electronic form, for example in the form of an electronic message or in the form of a data sample via a portal, such as an Internet portal. Preferably, persons from an authorized circle of users have the right to access the portal on which the identified risks of natural hazards are presented in a pre-prepared form, for example graphically. Alternatively, it is, of course, conceivable that no separate permission is required and at least some of the data provided is publicly available. First of all, it can be assumed that warnings and/or alerts based on identified risks of natural hazards are issued primarily to an authorized user group. For this purpose, an external analysis and/or forecasting unit performs, for example, an intelligent and/or automated assessment of the identified risks of natural hazards, and automatically warns and/or warns a group of users if a critical condition is detected. Relevant examples would be where the analysis and/or prediction unit, based on analyzed sensor data, determines that a structure has been struck or that the structure's corrosion condition has exceeded a tolerance threshold, especially a predetermined tolerance threshold.

In addition, it is proposed that at least one of the application areas is a structure including metal parts subject to atmospheric corrosion, especially external metal wires and/or metal wire ropes, preferably external steel wires and/or stainless steel wires with anti-corrosion layer (zinc, ZnAl, plastic, etc.) and that the risk of a dangerous natural phenomenon presented to the user group includes the residual service life of the structure determined on the basis of sensor data. Thus, the possibility of achieving high reliability is advantageously ensured. Another advantage is the ability to optimize planning for maintenance, reconstruction, renovation of buildings and similar activities. The advantage is the possibility of organizing a maintenance plan and/or reconstruction plan for the structure. The advantage is the ability to optimize a comprehensive maintenance plan that includes maintenance of multiple facilities located in different locations.

For example, the routes and/or deployment times of maintenance vehicles and/or maintenance personnel can be optimized through suitable sequencing of maintenance of various facilities. In addition, maintenance and/or consumables such as spare parts can be ordered in a time-optimized manner. In this way, it can be advantageously possible to reduce inventory costs and/or inventory volumes. The structure is intended, first of all, as an intercepting device, primarily an intercepting structure, for example, a rockfall barrier, an anti-mudflow barrier, an avalanche barrier, a rockfall curtain, a screen and the like, as a stability-providing device, primarily ensuring the stability of a structure, for example, strengthening a slope, avalanche protection and the like, or otherwise containing rope and/or wire structures of a structure, for example a suspension bridge, for example a pedestrian suspension bridge, a roof structure, for example a stadium roof structure, a glass facade, a mast attachment, a wind turbine attachment and the like.

First of all, the remaining service life is provided as the remaining service life parameter. First of all, the remaining service life parameter is an (approximate) time calculated from sensor data, preferably based on at least external corrosion measurements and tropospheric measurement data. For example, the remaining service life parameter indicates the remaining service life of the structure in terms of the remaining number of years, months and/or days. Alternatively, the remaining life parameter specifies the remaining life of the structure as a target date (to the nearest year, month or day).

Alternatively, the remaining life parameter may also be provided in the form of a percentage that indicates, for example, the fraction of the remaining thickness of the anti-corrosion layer layer, the fraction of the thickness of the anti-corrosion layer layer that has already been removed, the remaining proportion of the pre-calculated total life, or the like. First of all, in this case, in order to calculate the remaining service life, at least the thickness, especially the initial thickness, of the anti-corrosion layer of the controlled metal part of the structure is entered as additional information about the area of application. Alternatively, the remaining service life parameter may also be provided in the form of a percentage, which indicates, for example, the percentage of the barrier that is filled (the fraction already filled or the fraction still available), for example a mudflow barrier. First of all, in this case, as additional information about the area of application, at least one measured parameter of the barrier filling height, for example the tension force of the rope applied to the tension rope of the barrier, is introduced into the calculation of the remaining service life. It is further contemplated that in both cases at least one climate forecast, for example a climate forecast based on historically measured weather data and/or a climate forecast based on expected future weather data, primarily taking into account local and/or global climate change. First of all, the identified remaining life is made available to a group of users, preferably anywhere in the world, for example via an electronic display device, which preferably has Internet access.

When the presented risk of a natural hazard includes the rate of removal of the anti-corrosion layer, primarily the rate of removal of the zinc layer of metal parts with an anti-corrosion layer, primarily with a zinc layer, detected based on sensor data, the remaining service life of the components coated with an anti-corrosion layer can be advantageous identified in a particularly simple way. First of all, the removal rate for a particular material, such as zinc, can be used to determine the removal rate for other materials, which advantageously allows for a high degree of application flexibility. The “normalized rate of removal of the anti-corrosion layer” should be understood, first of all, as the rate of removal of the anti-corrosion layer, which can be recalculated for various types of anti-corrosion layers. The types of anti-corrosion layers can be primarily zinc layers, ZnAl-based layers, ZnAlMn-based layers, polyethylene terephthalate coatings, polyvinyl chloride coatings and the like. First of all, the rate of removal of the anti-corrosion layer can also be converted into the corrosion rate of stainless steel.

In addition, it is proposed that the presented risk of a dangerous natural phenomenon includes a change in the tension force of the rope, identified on the basis of sensor data, which tensions the mudslide barrier, avalanche protection, rockfall barrier and/or other structure, which, first of all, is subject to gradual filling. Thus, it is possible to advantageously identify the filling level of a mudflow barrier, avalanche protection, rockfall barrier and/or other structure, which level determines the remaining service life of the mudflow barrier, avalanche protection structure, rockfall barrier and/or other structure.

It is also proposed that the corrosion classification of the geographic external environment of the application area is set taking into account the identified rate of removal of the anti-corrosion layer. In this way, a particularly accurate and/or reliable corrosion classification of the geographical environment of the application area can be achieved. The advantage, first of all, in contrast to the widespread corrosion classification methods based only on geographical and/or climatic boundary conditions, is the possibility of a corrosion classification based on actual corrosion measurements. First of all, the classification of corrosion is carried out on the basis of categories from C1 to CX of the DIN EN ISO 12944-1:2019-01 standard. First of all, the corrosion class is assigned to the external environment of the application area based on the level of the detected rate of removal of the anti-corrosion layer.

In addition, it is proposed that in at least one area of application, in particular in at least one previously unsafe location, sensor modules of the external sensor network are installed before the use of protection against natural hazards and that an assessment of the need for use of protection against natural hazards events are subsequently carried out depending on the identified risk of hazardous natural phenomena. Due to this, it is advantageously possible to identify the need to use means of protection against natural hazards in a specific location. This makes it possible to advantageously optimize the overall use of resources to counteract natural hazards. The advantage is increased safety, primarily through the effective distribution of protective equipment against natural hazards. The benefit is the creation of an expert tool that greatly facilitates decision-making for or against natural hazard defenses. First, sensor data (e.g., tropospheric sensor data) collected by the sensor modules, preferably over an indicative period of time (e.g., at least one year or at least two years), is used to calculate the probability of occurrence of a hazardous event. natural phenomenon, such as rockfall, mudflow, landslide, erosion, etc. First of all, the calculated probability is presented to a group of users consisting of decision-makers to consider the use or non-use of means of protection against a dangerous natural phenomenon. First, assessing the need to implement a means of protecting against a natural hazard involves providing the likelihood of the event constituting a natural hazard occurring over a period of time, such as over the average life of the means of protecting against a natural hazard. First of all, the means of protection against a natural hazard may include one or more of the above-mentioned interception and/or stability structures. It is further contemplated that the assessment of the need to implement a remedy against a natural hazard includes a categorization of risk (eg, including at least the categories “high risk”, “moderate risk”, “low risk”).

It is further proposed that in at least one application area, sensor modules of an external sensor network are installed prior to a planned construction event, and subsequent adaptation of the planned construction event is carried out depending on the identified risk of a natural hazard. Thus, the possibility of achieving high reliability is advantageously ensured. The advantage is the possibility of suitable adaptation of the structure, especially one of the above-mentioned interception and/or stability structures. By “adaptation of the planned construction event” one should understand, first of all, the layout, preferably strength, stability, etc., of the structure to be erected during the implementation of the construction project. For example, the interception capacity of a rockfall barrier may be tailored to the size and/or frequency of expected rockfall events. For example, slope reinforcement anchorage can be adjusted to the expected erosion force.

When a construction project involves the installation of wire mesh and/or wire rope, and the type and/or thickness of the wire mesh and/or rope anti-corrosion layer is selected based on the identified risk of a natural hazard, optimal corrosion protection can be achieved and thus thus, optimal and/or maximum possible service life of the installation. The “type of anti-corrosion layer” should be understood, first of all, as the material and/or composition of the anti-corrosion layer (see examples below in the text). First of all, in highly corrosive environments, for example in humid climates and/or near the sea, a more resistant anti-corrosion layer (for example, ZnAl) or other more resistant anti-corrosion protection (for example, stainless steel wire) is preferable to a less resistant anti-corrosion layer layer (for example, Zn). First of all, in highly corrosive environments, such as in humid climates and/or near the sea, wire with a thicker layer of corrosion protection (for example, more than 150 g/ ^m2 ) is preferable to wire with a thinner layer of corrosion protection ( for example, less than 150 g/m ² ). First of all, in less aggressive environments, for example in dry desert regions, cheaper wire with a relatively thin layer of corrosion protection is sufficient. First of all, the calculation calculated from the sensor data is provided to support the planning and/or design of construction facilities to a group of users, including primarily construction designers. First of all, a recommendation calculated on the basis of sensor data regarding the type and/or thickness of the anti-corrosion layer is provided to support the planning and/or design of construction materials to a group of users, especially building designers.

When, in addition, the selection of the thickness of the wire and/or material of the wire mesh and/or wire rope is made on the basis of the identified risk of a natural hazard, and/or when, in addition, the selection of size, especially the size of the total length of the wire mesh and/or the size wire mesh cells are carried out based on the identified risk of a hazardous natural phenomenon, a high level of safety can be advantageously obtained. The advantage is that the protection can be precisely matched to the expected degree and/or intensity of natural hazards. The advantage is to achieve high efficiency and/or durability. Possible selectable (minimum) wire thicknesses are, for example, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm or 7 mm. Possible materials selected include, but are not limited to, steel, high-strength steel (ie, primarily steel with a nominal tensile strength of 800 N/mm or more) or stainless steel. First of all, the tensile strength of the wire mesh and/or wire rope, especially the steel wire mesh and/or steel wire rope, can be selected based on the identified risk of a natural hazard. Possible minimum tensile strength ratings for selectable steel wires include, for example, 400 N/ ^mm2 , 800 N/ ^mm2 , 1000 N/mm2, 1770 N/ ^mm2 , 2200 N/ ^{mm2 or} 3000 N /mm ² . First of all, the size of the wire mesh is set depending on the size of the danger zone detected using sensor modules. For example, sensor data is used to identify where on a slope at a given location it is necessary to ensure the safety of the area using an interception and/or stability structure. First of all, a recommendation calculated based on sensor data regarding wire thickness, wire material, wire mesh size, precise position of the wire mesh and/or mesh size of the wire mesh to support the planning and/or design of construction facilities is provided to a user group primarily including construction planning specialists.

In addition, it is proposed that additional information about the application area includes at least the location coordinates of the corresponding sensor modules installed in the application area, and that these location coordinates are used in identifying the risk of a hazardous natural phenomenon, the representation of which is formed in the form of a corrosion map indicating corrosion data, for example corrosion classification, corrosion intensity values, removal rate of the anti-corrosion layer and the like, at least in the application area and/or in the immediate vicinity of the application area. This advantageously makes it possible to obtain a detailed record of, in particular, at least the local corrosive activity of the application area and/or the surrounding area of the application area. An advantage is that small local differences in corrosiveness can also be shown in this way (for example, due to placement inside or outside a rain shadow, due to location in an area of high solar radiation intensity or in the spray area of a waterfall or surf, etc.). First of all, location coordinates associated with the sensor module can be detected during installation of the sensor module and/or can be entered into the sensor module. Alternatively, it is considered possible that the sensor module as such has a GPS function. A corrosion map may be designed primarily as a cartographic representation that includes a combination of geodetic data and location-related corrosion data. First of all, the corrosion map calculated from the sensor data is provided to a group of users, for example to support the planning and/or design of building materials. First of all, the corrosion map, preferably a presentation of the corrosion map provided to a group of users, includes an overlay of a map, such as a political map, a topographic map and/or a geological map or the like, on a spatially resolved, primarily measured, interpolated and/or modeled , corrosion data and/or corrosion classification.

When the corrosion map is fed into a Building Information Modeling (BIM) system, primarily designed as a natural hazard protection equipment for the application area, preferably intercepting and/or stabilizing the structure, particularly effective, simple and clear management of the application area, especially the structure. The opportunity to improve property management, especially the maintenance of real estate, can be advantageously provided. It is an advantage that critical points can be clearly identified in a user-friendly manner, for example with regard to wear, for example due to corrosion. First of all, the BIM system includes a virtual geometrically rendered model of the application area, especially the structure, on which a corrosion map is preferably superimposed. This makes it possible to directly identify those places and/or parts of the application area, especially the structure, that may be subject to increased corrosion. The advantage is that the corrosion map integrated into the BIM model can be updated throughout the entire service life of the BIM model structure. First of all, the BIM model, on which the corrosion map is superimposed, is provided to a group of users, for example to support the management of the structure.

When, in addition, optimization, especially local optimization of the area of application developed as protection equipment against natural hazards, is carried out on the basis of the identified corrosion map, the possibility of achieving a high level of safety can be advantageously ensured. The advantage is the efficient and/or precisely coordinated design of equipment to protect against natural hazards. The term “equipment for protection against natural hazards” should be understood primarily as an intercepting and/or stability-providing structure. The term “local optimization” of equipment for protection against hazardous natural phenomena should be understood, first of all, as a local adaptation of the form of execution of equipment for protection against hazardous natural phenomena, for example, local strengthening (for example, by changing the thickness of the wire, the thickness of the anti-corrosion layer, etc.) of the equipment for protection against natural hazards, local increase in equipment for protection against natural hazards or the like. For example, it is contemplated that if increased corrosiveness is detected in a partial portion of the application area, excellent corrosion protection is selected for the wire mesh placed in that partial portion and/or a second wire mesh is installed adjacent to or above the first wire mesh in that partial portion, and so on. similar. It is assumed that it is possible that optimization is considered before the natural hazard equipment is first installed, or that optimization is carried out only after that on already installed natural hazard equipment.

It is also proposed that the corrosion map is filled with simulated corrosion data for the area adjacent to the application area, while corrosion data in areas of the corrosion map free from sensor modules of the external sensor network are identified, at least on the basis of data from sensor modules in other application areas, primarily in adjacent application areas and/or in geographically and/or climatically similar application areas. The advantage is that it is possible to obtain a corrosion map that covers a particularly large area and is based on actual corrosion measurements. The advantage is the ability to reliably support construction planning over a geographically large area. The advantage is that even in areas for which measurement data are not yet available (eg corrosion measurement data), construction planning based on actual measurement data can be made possible. First of all, to identify corrosion data in areas free from sensor modules of the external sensor network, interpolation is performed between the corrosion data of two adjacent application areas where sensor modules with corrosion sensors are present. First, areas free of external sensor network sensor modules are compared with application areas in which sensor modules with corrosion sensors are present, and if geographic and/or climatic similarities are identified, it is preferable to assume that corrosion data in application areas that are geographically and/or climatically similar must be at least substantially the same. First of all, in this case, identical corrosion data are assigned to those application areas that are similar in geographic and/or climatic aspects to the application area where the corrosion data was actually measured. By “modeled corrosion data” is meant primarily corrosion data that is not based on direct in-situ measurements, but which is calculated, for example, from empirical values, from comparison with known corrosion measurements and/or by interpolation from known corrosion measurement data. First of all, the corrosion map compiled in this way becomes available to a range of users, for example to support further new construction measures or to make decisions about further new construction measures.

It is further proposed that additional information about the application area include at least the degree of wildlife activity and/or human activity, such as tourist activity, in the vicinity of the application area. Research has shown that significant improvements in identifying risks from natural hazards can be achieved in this way. First of all, forecasting natural hazards, such as rockfall forecasts, can be made more accurate. High, primarily seasonal, activity of wild animals or high, primarily seasonal, anthropogenic activity, such as hikers, can lead to increased redistribution of material in the application area, which can significantly increase the likelihood of events detected by the sensor module, such as rockfalls, especially under given atmospheric conditions. Accordingly, the risk of a natural hazard can be significantly influenced, first of all, by increasing it seasonally, by the corresponding level of activity, at least in a seasonal manner. First of all, an outdoor sensor network is provided to detect wildlife and/or human activity. Preferably, the outdoor sensor network includes at least one camera, in particular at least one wildlife camera, which is provided for detecting and/or counting wild animals and/or people, eg tourists. Alternatively, wildlife activity and/or tourist activity may also be identified based on external data from the application area and/or its surroundings. For example, through external surveillance cameras for wild animals, through counting of wild animals by hunting inspectors, through payments from sold tickets for parking in tourist parking areas, through calculations from sold tickets for mountain railways and the like. By "close environment" is meant primarily an environment of several kilometers, for example no more than 10 km, no more than 5 km or no more than 2 km around the application area, preferably around the outer edges of the application area, or preferably an environment of several hundred meters, for example no more than 800 m, no more than 500 m or no more than 300 m around the application area, preferably around the outer edges of the application area.

Alternatively or additionally, it is proposed that the additional application area information includes at least air quality data in the immediate vicinity of the application area. Research has shown that significant improvements in identifying risks from natural hazards can be achieved in this way. First of all, the forecast regarding the remaining service life of a corroded metal part of a structure can be more accurate, primarily since certain impurities in the air can have an increasing effect on corrosion. Air quality data may primarily include data on trace gases or aerosols in the air. For example, aerosol droplets that can deposit on metal parts and affect corrosion may have low pH values or high salt concentrations. For example, in some areas (for example, near volcanoes or in cities with high levels of air pollution), corrosive gases and/or aerosols (for example, sulfur compounds such as sulfur dioxide) may be present in the air. Preferably, the outdoor sensor network includes at least one air quality sensor. Alternatively, air quality may be determined based on external data from the application area and/or its surroundings. For example, through external measurements of air pollutants or through modeling of air pollutants.

In addition, it is proposed that identified natural hazard risks include predictions of natural hazard risks that are created based on past performance of sensor data and, above all, based on additional information about the application area identified in the past, preferably using predictive analysis data. In this way, it can be advantageously possible to achieve high reliability. For example, optimization and/or adaptation of structures exposed to natural hazard risks can be achieved. An advantage is that the structure can be designed in such a way that it can withstand expected events and/or provide sufficient protection against expected events. For example, correlations of different sensor data measured during an event can be used to draw conclusions about the predictability of future events. An example would be identifying a threshold amount of precipitation, a threshold wind speed, or a threshold value of wildlife activity, above which a rockfall, especially of a given size, becomes likely to occur. For example, an alert may be issued to an operator or facility manager when a natural hazard risk prediction parameter crosses a specified upper or lower threshold, which may result in, for example, alerting an emergency response or maintenance team. For example, a risk forecast for a natural hazard may be provided to a fire command center, which can place certain departments on high alert if the risk forecast for a natural hazard predicts an increased likelihood of the event. For example, a forecast of the risk of a natural hazard may be available to a railway operator, who can stop a train from passing through a certain area or change the route of a train if the forecast of the risk of a natural hazard predicts an increase in the likelihood of the event. For example, a forecast of the risk of a natural hazard may be provided to the authority responsible for the management of hiking trails, which may close hiking trails within a certain area if the forecast of the risk of a natural hazard predicts an increase in the likelihood of the event.

In addition, it is proposed that at least one sensor module of the external sensor network is configured as an intercepting and/or providing stability device for rock, stones, avalanches, mudflows, landslides and the like, primarily designed as an intercepting and /or ensuring the stability of the structure, wherein at least one sensor module of the external network of sensors has a shock sensor for detecting impacts on the intercepting device, and based on data from the shock sensor and/or, based on data primarily measuring the degree of filling of the mudflow barrier data based on the tension force of the rope from the rope tension force sensor as part of the sensor module, together with a series of measurements of the measurement data of the tropospheric parameters of the sensor module, and above all, together with additional information about the application area, an analysis is carried out, primarily pattern recognition, and on the basis of this analysis it is identified A risk forecast of a hazardous natural phenomenon performed as an impact forecast. Improving the risk prediction of natural hazards can be advantageously achieved by incorporating past measurement data. First of all, pattern recognition is carried out in the form of automatic pattern recognition, which is preferably carried out by means of an analysis and/or prediction unit algorithm based on the principle of machine learning and/or on the principle of neural networks. First of all, the risk forecast of natural hazards identified in this way is provided to a group of users. First of all, pattern recognition involves the detection of faulty sensors and/or sensor modules of an external sensor network. For example, anomalous data values can be used to identify individual potentially damaged, incorrectly calibrated, or incorrectly installed sensors and/or sensor modules. Preferably, pattern recognition is also based on the principle of swarm intelligence sensors.

In addition, it is proposed that, based on the identified risk of a natural hazard, a maintenance plan is prepared for the area of application, for example, for a protective structure intended to protect against a natural hazard. In this way, a high level of efficiency can be advantageously achieved, especially service efficiency, for example with regard to the organization of personnel, materials and machines.

First of all, the maintenance plan is available to a group of users. First of all, the maintenance plan is also based on identified risk predictions of natural hazards. First of all, the maintenance plan can be flexibly adjusted to changing sensor measurement data. First of all, the maintenance plan can be flexibly adjusted to detected events, such as impact events and/or backfill events. For example, it is contemplated that it is possible for a given application area to move forward in time in a maintenance plan following the detection of one or more new impacts or backfill events, such as debris flows.

When the organization of maintenance personnel, the organization of service equipment, and/or the organization of consumables is carried out based on identified natural hazard risks in several, primarily regionally distributed, application areas, high maintenance efficiency can be advantageously achieved. For example, inspection routes for maintenance teams that inspect multiple application areas during a maintenance trip can be advantageously optimized in terms of total travel time and/or total travel distance. The term “organization of service personnel” should be understood, first of all, as the assignment of operational areas to the persons performing the service. Preferably, maintenance orders, primarily from the analysis and/or forecasting unit, are distributed in such a way that the total workload can be distributed as evenly as possible among all personnel available in the region, and/or that the total travel distance of those available in the region region of personnel turns out to be the minimum possible. The “organization of maintenance equipment” should be understood, first of all, to assign maintenance equipment to the persons performing maintenance. Preferably, maintenance orders, especially from the analysis and/or forecasting unit, are distributed in such a way that the total assignment of maintenance devices to available personnel is distributed in such a way that the minimum possible downtime of maintenance devices and personnel can be achieved. By “organizing consumables” we mean, first of all, assigning consumables to the persons performing maintenance. Preferably, first of all, by means of an analysis and/or forecasting unit, consumables are distributed among the available personnel in such a way that ensures the minimum possible stock.

It is also proposed that upon detection of an impact to an interceptor device, primarily a rockfall barrier, primarily through an impact sensor, and/or upon detection of a backfill event, such as a debris flow, at the interceptor device, primarily a debris flow barrier, primarily through a sensor rope tension forces, depending on the degree and/or type of impact and/or backfill event, trigger a maintenance order, primarily in the form of a warning, or immediate repair, primarily in the form of an alarm. This advantageously ensures that an appropriate and/or effective response to an event has occurred. The advantage is that safety can be further enhanced. First of all, if the degree of impact and/or backfill indicates serious damage to the interceptor (for example, crossing the upper or lower pre-identified limit value), an alarm is activated, which preferably results in the dispatch of a repair (emergency) team as soon as possible and/or to blocking the application area for unauthorized persons. First of all, if the degree of impact and/or backfill indicates less serious damage to the interceptor (e.g. the measured values are within the acceptable range), an alarm is triggered, preferably leading to an early inspection of the work area and, if necessary, the clearance of the relevant intercepting device.

In addition, it is proposed that depending on the result, for example, an impact on a rockfall barrier and/or a backfilling event of a mudflow barrier and/or on the value of the identified risk of a dangerous natural phenomenon, primarily on the strength of the impact and/or backfilling event, the deployment of a drone is initiated before the entire service drone and/or reconnaissance drone. This makes it possible to achieve high service efficiency and/or reduce organizational costs in an advantageous manner. By “drone” we mean, first of all, an unmanned aerial vehicle that either operates independently or is controlled remotely. A “reconnaissance drone” should be understood, first of all, as a purely sensor-based drone, primarily a drone with a camera, which is designed to carry out, first of all, a visual inspection and/or inspection of the application area, especially the structure. By "maintenance drone" is meant primarily a drone which, in addition to the tasks of a reconnaissance drone, is primarily designed to carry out at least one maintenance operation. The maintenance operation may include, for example, reading data from sensor modules, charging sensor module energy storage units, replacing sensor module parts (eg, batteries), installing a sensor module, and the like. First of all, it is assumed that it is possible that the drone operates at least partially autonomously, using sensor modules located in the area of application for (GPS-independent) navigation, primarily according to the “virtual track” principle, as orientation points and/or auxiliary means of orientation. “Starting” the operation of a drone should be understood, first of all, as the direct autonomous launch of the drone from a parking position. Alternatively, “launching” a drone deployment should also be understood as notifying the person responsible for deploying the drone, who, preferably as a result of the notification, transports the drone to the deployment area and launches it there autonomously or remotely.

In addition, a sensor remote monitoring device is proposed, having a sensor module for an external sensor network, which is primarily provided for recording and providing sensor data for a method of analysis and/or prediction based on a sensor network, and has at least one external corrosion sensor , at least one environmental sensor for detecting measurement data of tropospheric parameters, as well as at least one communication unit for transmitting, primarily wirelessly, sensor data to an external analysis and/or forecasting unit, wherein the sensor module has at least at least, an essentially hermetically sealed housing of the sensor module. This makes it advantageously possible to obtain complete and/or meaningful information about the risks of natural hazards, especially in one or more application areas. The advantage is the possibility of reliable and/or stable monitoring of external sensors. The advantage is the possibility of long-term external monitoring, which preferably operates continuously even in areas with particularly harsh weather conditions. The external corrosion sensor is provided primarily as an outdoor corrosion sensor, which is preferably provided to detect the corrosive activity of the external atmosphere. The external corrosion sensor is provided primarily for detecting corrosion, preferably its progression, by measuring the corrosion current. The external corrosion sensor includes a corrosion monitoring element. First of all, the external corrosion sensor is provided to measure the corrosion current resulting from corrosion processes in the corrosion control element, which is placed open to the external atmosphere, preferably to measure the current value of the corrosion current. Advantageously, the external corrosion sensor detects an electric current proportional to corrosion, in particular proportional to the removal rate of the corrosion protection layer, especially the corrosion control element layer, from which, first of all, a conclusion can be drawn about the change in time of the removal rate of the protection layer against corrosion, the instantaneous removal rate of the corrosion protection layer and/or the current residual thickness of the material of the corrosion protection layer, especially the corrosion control element, and thus also the metal parts placed in the application area.

The corrosion control element is a modified ACM (Atmospheric Corrosion Monitor) sensor. First of all, the AFM sensor is provided to detect the corrosiveness of the medium and/or the corrosion rate, especially the rate of removal of metals and/or alloys, preferably based on the galvanic current flowing between the metals and/or alloys. First of all, the AFM sensor includes at least two electrodes, which are electrically isolated from each other, primarily in a dry state. First of all, the electrodes are made at least in part from different materials, preferably from different noble metals. It is possible that at least one electrode has at least one coating, in which case, in particular, the surface materials of the at least two electrodes are different.

Preferably, the surface materials are made of various noble metals. Advantageously, the at least one electrode is substantially identical to the at least one section of the wire mesh. In this way, the greatest possible transferability of the material removal results measured at the corrosion monitoring element to the removal of wire mesh material can be advantageously obtained. Advantageously, the at least one additional electrode of the AFM sensor is made, at least in part, from a more noble material than the electrode, which is made substantially identical to the wire section. The more noble material may primarily be steel, silver, gold, cobalt, nickel, copper, platinum, palladium, another element in the electrochemical voltage series above zinc, and/or an alloy in the electrochemical voltage series above zinc. First of all, the electrodes, especially the electrodes having different surface materials, are arranged without contact with each other. First of all, electrodes, especially electrodes having different surface materials, do not have direct mutual electrical contacts. Preferably, the electrodes, especially the electrodes having different surface materials, are in electrical contact in a wet state through droplets of water forming the electrolyte. First of all, galvanic current flows when the electrodes are in electrical contact. First of all, the galvanic current causes material removal and/or corrosion of the less noble electrode. The electric current is advantageously proportional to the removal of material. The presence and/or properties, especially the corrosive properties, of the electrolyte depend primarily on the environmental conditions affecting the corrosion control element at a given point in time, which allows one to draw a conclusion about the corrosiveness of the environmental conditions at a given point in time.

The environmental sensor includes at least one thermometer, at least one hygrometer, at least one ombrometer, at least one pyranometer, at least one anemometer, at least one barometer and/or at least one other a measuring device, such as, for example, a measuring device for detecting trace gases, salt concentration or aerosol concentration and the like. First of all, the communication unit is provided for automatic, preferably periodic, transmission of sensor data to an external analysis and/or prediction unit. Preferably, the communication unit has a mobile radio function. First of all, the communication unit communicates via a mobile radio protocol, for example EDGE, GPRS, HSCSD and/or preferably via a GSM mobile radio protocol. However, additionally or alternatively, it is assumed that it is possible to use other radio interfaces for communication with the analysis and/or prediction unit. In addition, it is considered possible that the sensor module, especially the communication unit, has other radio interfaces for communication with electronic devices in the immediate vicinity, for example with other sensor modules of the external sensor network, with drones and/or with external sensors such as an external camera , first of all, an external Bluetooth camera. The other radio interface may be, for example, a Bluetooth radio interface, an NFC radio interface, an RFID radio interface, a LoRa radio interface, or a similar short-range radio interface. Preferably, the communication unit, in addition to the sensor data, transmits other data on the sensor module, such as location, time, battery level, functional status, and the like.

By “substantially hermetically sealed sensor module housing” is meant, first of all, a sensor module housing that is closed in at least a watertight manner, in particular against water columns of at least 5 m in length, preferably at least at least 25 m, more preferably at least 100 m, and particularly preferably at least 250 m.

Preferably, the at least substantially sealed housing of the sensor module is also closed in an at least substantially sealed and/or gas-tight manner. By “at least substantially sealed and/or gas-tight” it is meant primarily that the moisture vapor transmission rate (MVTR) between the interior of the sensor module housing and the environment surrounding the sensor module housing is less than 100 cm ³ /m ² /24 h, preferably less than 25 cm ³ /m ² /24 h, more preferably less than 10 cm ³ /m ² /24 h, and particularly preferably less than 1 cm ³ /m ² /24 h. Alternatively or additionally, “at least "substantially sealed and/or gas-tight" means that the oxygen transfer rate (OTR) between the interior of the sensor module housing and the environment surrounding the sensor module housing is less than 1000 cm ³ /m ² /24 h, preferably less than 250 cm ³ /m ² /24 h, more preferably less than 100 cm ³ /m ² /24 h, and particularly preferably less than 50 cm ³ /m ² /24 h. The hermetically sealed housing of the sensor module is provided primarily to prevent foreign bodies from entering the sensor module, whereby a long service life can be achieved. Advantageously, the housing of the sensor module is resistant to damage by vegetation (eg root penetration or the like). Advantageously, the housing of the sensor module is resistant to damage by wild animals (eg insect penetration, wild animal bites and the like). First of all, inside the housing of the sensor module there is at least one communication unit, at least one energy storage device of the sensor module and/or at least one electronic control and/or adjustment unit and/or computing unit, which interacts with the external corrosion sensor, with an environmental sensor, with a communication unit, with an energy storage device for the sensor module, and the like. First of all, the hermetically sealed housing of the sensor module includes at least one, preferably hermetically sealed and/or hermetically sealed, passage for at least one sensor probe, in particular an external corrosion sensor and/or an environmental sensor. The term “sensor remote monitoring device” should be understood, first of all, as a device for remote monitoring of corrosion and/or impacts for structures, primarily for intercepting and/or ensuring the stability of structures in an area of a hazardous natural phenomenon. First of all, the sensor remote monitoring device is provided for remote monitoring of a structure, primarily intercepting and/or ensuring the stability of the structure, based on data from several sensor modules. First of all, the sensor module is provided for installation in the application area, that is, for attachment to the ground or, preferably, to an interception and/or stability structure, in particular to a rope, preferably a tension rope of the interception and/or stability structure. Preferably, the sensor module is secured to the tension rope of the interception and/or stability structure.

In addition, it is proposed that the housing of the sensor module is designed without cable entries such as plugs, sockets or cable guides, without cable outputs such as plugs, sockets or cable guides, without push-button switches, especially without mechanical switches such as toggle switches and/or push-button switches, and no external antennas such as plastic-layered rod antennas (rubber sausage) or dipole antennas. As a result, a long service life of the sensor module can be advantageously achieved. Due to this, advantageously, the sensor module is particularly resistant to attacks by wild animals and/or other damage caused by wild animals, for example deer, martens, wild boars, mice, rats and the like, which is of great importance especially in situations of external use of sensor modules. First of all, the external part of the sensor module, in particular the housing of the sensor module, is at least substantially free of plastic coverings and/or other external plastic parts. By “substantially free” in this context is meant primarily that less than 25%, preferably less than 15%, preferably less than 10%, more preferably less than 5%, and particularly preferably less than 2%, of the outer surface of the sensor module is formed by plastic. First of all, the surface of the sensor module, in particular the sensor module housing, is at least, preferably more than 75%, more preferably more than 90%, and particularly preferably more than 95% metal.

It is also proposed that the sensor module, especially the communication unit, has a wireless camera interface for connection with an external camera. This makes it advantageous to obtain comprehensive and/or relevant information about the risks of natural hazards.

The advantage is the possibility of directly obtaining additional information about the application area, which can be taken into account, for example, in the preliminary analysis of sensor data inside the sensor module. In addition, it is advantageously possible to maintain an at least substantially airtight seal of the sensor module housing. The camera's wireless interface is primarily a Bluetooth interface, preferably a Bluetooth Low Energy (BLE) interface. However, as an alternative or in addition, other wireless interfaces are contemplated to be possible, for example a Near Field Communication (NFC) interface and/or a ZigBee interface.

In addition, it is proposed that the sensor remote monitoring device includes an external activating and/or deactivating element, which is provided for activating and/or deactivating the sensor module depending on the placement of the external activating and/or deactivating element relative to the sensor module housing within the sensor module . This makes it advantageous to enable reliable and/or stable monitoring of external sensors. The advantage is that it is possible to control, above all, the activation and/or deactivation of sensor modules independently of external switching elements. Preferably, the activating and/or deactivating element is made in the form of an activating and/or deactivating magnet. However, other embodiments are also contemplated, for example in the form of an adhesive element, a clamping element and the like. First of all, the sensor module has a detection unit, which is provided for detecting the presence of an activating and/or deactivating element in the activation and/or deactivation position. For example, the detection unit is designed as a magnetic field sensor. As an alternative, however, mechanical circuits are also possible, the switching elements of which are attracted or repelled by an activating and/or deactivating element designed as an activating and/or deactivating magnet, which makes it possible to control the internal switching process of the sensor module from outside the housing of the sensor module. First of all, the sensor module is deactivated as long as the external activating and/or deactivating element is in the deactivating position. First of all, the sensor module is activated as long as the external activation and/or deactivation element is in the activation position. For example, the sensor module is deactivated as long as the activating and/or deactivating element is attached to the sensor module housing, in particular in the deactivation zone of the sensor module housing forming the deactivation position. For example, a sensor module is activated as long as the activating and/or deactivating element is removed from the immediate vicinity of the sensor module housing. Of course, the reverse scheme is also assumed to be possible.

When a communication unit is provided to transmit sensor data directly, preferably via a radio protocol using the GSM mobile radio standard, primarily without detours through one or more sensor data collection points, to an external analysis and/or forecasting unit, primarily in the form of a cloud, wherein an external analysis and/or prediction unit is provided for receiving sensor data from several sensor modules distributed over different application areas, especially worldwide, it is advantageously possible to achieve a high level of data security. The advantage is that unauthorized eavesdropping of sensor data can be significantly more difficult, primarily since this requires intercepting every single message from every sensor module. The advantage is the ability to avoid additional collection points that require costs and/or effort to maintain. The advantage is the high safety of the sensor network relative to failures, first of all, since not all collection points can fail, but only individual sensor modules. The advantage is that the installation and/or configuration of an external sensor network can be simplified. First of all, the communication unit ensures that the transmitted sensor data is encrypted, preferably using an asymmetric cryptography system. Preferably, the private key and/or public key that is assigned to the sensor module in the asymmetric cryptography system is already integrated into the sensor module at the time of manufacture. This allows you to achieve a particularly high level of data security. In addition, it can be envisaged that to ensure a high level of manipulation security, sensor data could be stored, preferably in an encrypted blockchain, or, preferably, in an encrypted distributed consensus ledger. First of all, the external analysis and/or forecasting unit includes a central communication unit, which is provided for receiving sensor data from several sensor modules of the external sensor network distributed over different application areas, preferably from all sensor modules of the external sensor network.

In addition, when in case of unavailability of the external analysis and/or forecasting unit, especially in the case of limited and/or absent communication, especially GSM communication, the communication unit is provided for transmitting sensor data to another, preferably neighboring, sensor module of the external sensor network , particularly complete coverage of an area can be advantageously achieved. The advantage is the integration of sensor modules located in places with poor or no communication into an external sensor network. For this purpose, it is considered possible that communication between sensor modules is also carried out via a communication unit, however, an alternative radio standard and/or an alternative radio interface is used, preferably a radio interface with a comparatively shorter range, for example LoRa or the like. First, sensor data is passed along a chain of sensor modules until a sensor module with sufficient connectivity is reached to be sent directly to an external analysis and/or prediction unit.

It is further proposed that the sensor module includes at least one acceleration sensor. The advantage is the ability to provide reliable detection of impact events. Advantageously, the detected impact events can thus be correlated with other sensor data, eg tropospheric measurements and/or additional information about the application area (eg other external measurement data). First of all, the acceleration sensor forms a shock sensor. An acceleration sensor is provided for detecting acceleration occurring when impact bodies hit an intercepting and/or stability-providing structure controlled by at least one sensor module. Preferably, the acceleration sensor is at least provided to measure acceleration up to at least 100 g, more preferably at least 150 g, and most preferably at least 200 g, where 1 g corresponds to a value of 9.81 m/s ² . First of all, an acceleration sensor is provided to detect accelerations in all three spatial directions. First of all, an acceleration sensor is provided to detect the direction of acceleration.

First of all, the acceleration sensor is configured as an acceleration sensor of a type known to those skilled in the art, for example, a piezoelectric acceleration sensor, a MEMS acceleration sensor, and the like.

Preferably, the operation of the acceleration sensor is independent of cables and/or ropes running outside the housing of the monitoring device. First of all, the acceleration sensor is located entirely inside the sensor module housing.

It is further proposed that the sensor module includes at least one orientation sensor. In this way, high reliability of sensor data, especially external corrosion measurement data, can be achieved. First of all, an orientation sensor is provided to detect the orientation of the sensor module relative to the direction of gravity. First, an orientation sensor is provided to detect the orientation of the external corrosion sensor relative to the effective direction of gravity. First, by changing orientation as a result of an event, such as an impact from an impactor, additional information about the event, such as the force or direction of the impact, can be obtained. First, orientation measurement can be used to ensure the quality and/or reliability of external corrosion sensor data, primarily by detecting improper orientation of the external corrosion sensor, such as an inverted position of the external corrosion sensor. When the external corrosion sensor is completely or partially covered, precipitation moisture may not reach the external corrosion sensor or may reach too little of the external corrosion sensor so that the corrosion control element of the external corrosion sensor is primarily affected by the metal part being completely exposed to all the precipitation moisture. , corrodes less, that is, generates less corrosion current and thus the measured corrosion value may be too low. First of all, the orientation sensor is designed as a type of orientation or position sensor known to those skilled in the art. First of all, it can be assumed that the orientation sensor simultaneously forms an acceleration sensor or vice versa.

It is further proposed that the sensor module includes at least a rope tension sensor. In this way, effective and/or reliable monitoring of structures including ropes, especially tension ropes, can be achieved. Advantageously, it is possible to reliably detect impact events on intercepting structures, such as rockfall barriers, and/or backfill events on intercepting structures, such as debris flow barriers. In addition, the rope tension sensor advantageously provides the ability to measure the extent of an event, in particular an impact event and/or a backfill event. Preferably, the rope tension sensor is provided for measuring the rope tension force up to 50 kN, more preferably up to 100 kN, particularly preferably up to 150 kN, more preferably up to 200 kN, and particularly preferably up to 294 kN. Preferably, the operation of the rope tension sensor is independent of cables and/or ropes extending outside the control device body assembly. First of all, the rope tension sensor is located entirely inside the sensor module housing.

It is further proposed that the rope tension force sensor for measuring the tension force of the rope includes at least one strain gauge, which is preferably located separately from the rope, the tension force of which is monitored by the rope tension force sensor. In this way, a particularly simple and/or uncomplicated measurement of the rope tension force can be achieved. First of all, the strain gauge is designed to detect the deformation of the rope contact element in the sensor module caused by the force occurring on the rope. First of all, the strain gauge is located in the inner part of the sensor module housing. First of all, the strain gauge includes a temperature response adapter. First of all, the strain gauge is designed as a self-compensating strain gauge. First of all, the strain gauge is not in direct contact with the rope being monitored. First of all, the strain gauge is placed on the side of the rope contact element facing the inside of the sensor module housing. First of all, the strain gauge is placed on the side of the rope contact element facing away from the rope being monitored.

In addition, it is proposed that the rope tension force sensor is at least partially made integral with the connecting device of the sensor module, wherein the connecting device is provided for directly attaching the sensor module to the structure, preferably to the rope of the structure, more preferably to the tension wire rope structure. This makes it possible to measure rope tension in a particularly advantageous and/or space-saving manner.

First of all, the connecting device is provided for deflecting a rope, in particular a tension rope, by means of a rope contact element in such a way that the force acting on the rope, that is, in particular the tension force of the rope, deforms the rope contact element in a measurable manner. Advantageously, the connecting device is designed to be universal for various ropes, especially for ropes of different thicknesses. First of all, the sensor module can be mounted by means of a connecting device on at least ropes with a rope thickness of 16 mm to 24 mm. Adaptation of the connecting device to thicker or thinner ropes is easily possible without deviating from the idea of the invention. Advantageously, any structure that has a rope, especially a rope on which forces can occur, can be retrofitted with sensor modules. First of all, sensor modules can be mounted using a connecting device on all structures with ropes, especially tension ropes. By the fact that two components are formed "partially as a whole" it is to be understood, first of all, that the components have at least one, in particular at least two, preferably at least three, elements in common which form the component part, first of all in total, a functionally important part of both components.

It is further proposed that the external corrosion sensor is based on measuring the electrical corrosion current (also referred to as "corrosion current" for short) resulting from corrosion, wherein the corrosion sensor includes at least one charge storage device, such as a capacitor, which, by means of electrical corrosion current is charged to the maximum charge, after which the charge store, especially the capacitor, is discharged again, and wherein the sensor module has an ammeter, which is provided for measuring the discharge current of the charge store, especially the capacitor, to detect external corrosion measurement data. This makes it advantageously possible to achieve particularly precise and/or reliable corrosion measurements, in particular by making it possible to reliably measure even low corrosion currents, which are for example in the μA range. The advantage is that the measurement of particularly low corrosion currents, especially in the µA range, as usually happens when using external corrosion sensors, primarily of the AFM type, can be carried out without great technical effort (for example, without a zero-resistance ammeter). It is an advantage that the external corrosion sensor can be designed in a particularly cost-effective manner. Corrosive current is primarily a galvanic current.

It is further proposed that the sensor module has at least one battery provided for powering at least one component of the sensor module, wherein the electrical corrosion current of the external corrosion sensor serves as a charging current for electrically charging the battery. This makes it advantageously possible to achieve a particularly long battery life for the sensor module. The advantage is that the sensor module can operate autonomously for particularly long periods of time.

It is also proposed that the sensor module has a preliminary analysis unit, which is provided for performing at least one preliminary analysis of measurement data in the immediate vicinity of the sensor, in particular raw measurement data, of at least one of the sensors of the sensor module and/or at least one an external sensor connected to the sensor module, for example an external camera. This makes it possible to advantageously use electrical energy, which is only available in limited quantities, in an advantageous manner. The advantage is the possibility of reducing and/or optimizing the amount of data transmitted via the communication unit. First of all, due to the fact that data transmission constitutes a large part of the energy consumption of the sensor module, the service life of the sensor module, especially the battery and/or battery of the sensor module, can be optimized. First of all, a pre-analysis unit is provided to perform analysis of raw measurement data in close proximity to the sensor. First of all, the preliminary analysis block is provided for averaging, generalization and/or processing of source data.

First of all, the raw data can be stored in the sensor module and can be queried for new analysis or quality control via the analysis and/or prediction unit or read directly on site. First of all, the preliminary analysis unit is provided for automatically adjusting the intervals between transmissions and/or time points of data transfer to the analysis and/or forecasting unit based on a preliminary analysis of the source data. For example, the interval between transmissions may be increased in phases in which, based on previously analyzed tropospheric measurement data, a generally low level of activity is expected (for example, in relation to corrosion and/or rockfall, etc.), for example, during dry and windless periods. weather. First of all, preliminary analysis of measurement data is provided to minimize the transmitted volume of data. First of all, preliminary analysis of the measurement data is provided to reduce the overall energy consumption of the sensor module. First of all, it costs less energy to apply pre-analysis than could be saved by not sending all the raw data. The preliminary analysis unit is, first of all, made in the form of a computing unit associated with the sensor module. The term “computing unit” should be understood, first of all, as a component that performs information input, information processing, and information output. Preferably, the computing unit has at least one processor, memory, input and output means, additional electrical components, an operating program, standard control programs, standard control programs, and/or standard computer programs. Preferably, the components of the computing unit are placed on a common printed circuit board and/or advantageously housed in a common housing.

When, in addition, the pre-analysis unit provides an independent choice of which part of the sensor measurement data set is transmitted by the communication unit, and/or when the pre-analysis unit provides an independent choice of whether the sensor measurement data set is transmitted by the communication unit or not, an advantageous optimization of energy consumption. For example, it can be assumed that the image recorded by the external camera can be compared by the pre-analysis unit with previously recorded images and that a new image can be sent through the communication unit only if the new image contains significant changes compared to the previously recorded image . For example, it is contemplated that it is possible for a sensor module's sensor data set to be transmitted by the communication unit only when another sensor's data set meets a given criterion, such as indicating a given event (e.g., orientation sensor data and/or orientation sensor data set are transmitted only if case where acceleration sensor data and/or a set of acceleration sensor data indicate that an impact event or the like has occurred).

When a pre-analysis unit is provided to set the interval between transmissions of the communication unit based on measurement data of at least one sensor of the sensor module and/or at least one external sensor connected to the sensor module, beneficial optimization of energy consumption can be achieved. First of all, the pre-analysis unit reduces the interval between transmissions during periods of increased activity (for example, increased corrosion, increased rockfall activity, increased wind speed, increased precipitation, etc.). First of all, the pre-analysis unit increases the interval between transmissions during periods of low activity (for example, low or no corrosion, low or no rockfall activity, low wind speed, lack of precipitation, and the like).

In addition, when a pre-analysis unit is provided for specifying control of the sleep phases and/or measurement intervals of at least one sensor and/or at least one other sensor, in particular different from this sensor, based on measurement data of at least one sensor sensor module and/or at least one external sensor connected to the sensor module, beneficial optimization of energy consumption can be achieved.

For example, it is considered possible that an image is recorded by an external camera only when measurement data from another sensor indicates an event, such as an impact or the like. First of all, in this case, the recording of the image by the camera can be initiated by the measured values of the sensor module, which have been detected by another sensor and analyzed by a preliminary analysis unit directly adjacent to the sensor. For example, it is assumed that it is possible that a sensor module sensor can only be activated when another sensor's data set meets a given criterion, such as indicating a given event (for example, an orientation sensor can only be activated when acceleration sensor data indicates that there was an impact or the like). For example, it is considered possible that the sensor module's sensor may be put into sleep mode if no change in the sensor's measurement data is expected for an extended period of time (for example, an orientation sensor may be put into sleep mode when there is no precipitation and no large amounts of precipitation are being measured). wind force).

In addition, it is proposed that the sensor module has a computing unit with a specially designed and not based on existing operating systems operating system, which is provided primarily for implementing sensor control and/or sensor regulation, a communication unit, a preliminary analysis unit, and the like. This makes it advantageously possible to achieve a particularly high level of data security and/or protection against misuse. The advantage is the possibility of achieving a particularly high level of protection against hacker attacks, for example using Trojans and the like, primarily since any malicious program must be specially adapted to the sensor module’s own operating system. The computing unit is provided primarily for controlling and/or regulating sensors, a communication unit, a preliminary analysis unit, and the like. First of all, the computing unit at least partially constitutes a preliminary analysis unit.

In addition, it is proposed that the sensor module has an energy harvesting unit, which is provided for generating a current, in particular a charging current for charging the battery of the sensor module, from a temperature difference, in particular within the housing of the sensor module. This makes it possible to achieve particularly high energy efficiency in an advantageous manner. This makes it advantageously possible to achieve a particularly long service life of the sensor module. This makes it possible to advantageously increase the autonomy of the sensor module. First, the energy harvesting device includes at least one thermoelectric generator. First of all, a thermoelectric generator is based on the use of the Seebeck effect to generate charging current. First, the energy harvesting device includes at least one Seebeck element. First, the energy harvesting unit is provided to utilize the temperature difference between the upper surface of the sensor module housing (directly exposed to solar radiation) and the lower surface of the sensor module housing (located in the shadow of the sensor module) to generate current and/or voltage.

In addition, it is proposed that the sensor remote monitoring device has at least one additional sensor module, in particular designed separately from the sensor module, which is assigned to the same application area as the sensor module. This makes it advantageously possible to achieve particularly complete and particularly precise control over the application area. First of all, this makes it advantageous to take into account the fact that within the same area of application different conditions may prevail, which can lead, for example, to locally different rates of corrosion (windward side versus leeward side/rainy side slope shadows) or which may lead to locally varying rockfall rates (e.g. steepness/geology of the terrain above the slope). First, the sensor remote monitoring device includes at least two, preferably at least three, more preferably at least four, and most preferably more than five, sensor modules, which are all installed at different locations in the application area. Preferably, the sensor modules of the sensor remote monitoring device, in particular the sensor module and the additional sensor module, are at least substantially identical to each other. First of all, all sensor modules of the sensor remote monitoring device are wirelessly connected to one analysis and/or prediction unit. First of all, the outdoor sensor network includes several sensor remote monitoring devices, each of which has several sensor modules.

It is also proposed that the at least one additional sensor module does not have a (local) communication connection with the sensor module. This makes it possible to achieve a high level of data security in an advantageous manner.

Preferably, each of the sensor modules of the sensor remote monitoring device directly communicates only with an analysis and/or prediction unit located outside the application area.

It is further proposed that the sensor module includes a configuration module, which is provided for wireless communication, for example via an NFC interface of the communication unit, with an external installer configuration device, for example a smartphone, for configuring the sensor module, in particular for initially configuring the sensor module and /or to reconfigure the sensor module. This advantageously allows for a particularly simple installation process. First of all, it is advantageously possible to prevent errors when installing sensor modules, which could lead to erroneous sensor data. First of all, the sensor module preferably includes a communication unit, an interface for short-range data transmission, for example a Bluetooth interface, a BLE interface or, preferably, an NFC interface, which is provided primarily for communicating the adjustment module with an external adjustment device.

It is further proposed that the sensor module includes a configuration element, such as a QR code, bar code, NFC interface, or the like, which can be read, scanned, or used to provide control via an external configuration device to initiate configuration of the sensor module , primarily the initial configuration of the sensor module and/or reconfiguration of the sensor module.

This makes it possible to achieve a high degree of user convenience in an advantageous manner. The advantage is that the risk of incorrect installation is reduced. In this way, high reliability and/or high quality of the sensor data is advantageously ensured. First of all, after reading, scanning and/or issuing a control action by the setting element, the installer goes through a controlled, at least partially automated installation process, during which the external setting unit communicates with the sensor module, preferably via a wireless interface, for example an NFC interface, and during which configuration data is preferably sent from an external configuration device to the sensor module or vice versa. First of all, the setup process is controlled by the application software (application) installed on the external setup device. First of all, the installer guides the installation process using a mobile application. First of all, at least part of the data exchanged between the external tuner and the sensor module, and/or at least part of the configuration data of the sensor module can be automatically and wirelessly transmitted to the analysis and/or prediction unit, preferably after successful configuration, especially initial configuration and/or reconfiguration.

First of all, the setup process involves registering the setup company, primarily the company name, and/or registering the setup installer, primarily the installer ID number and/or name. First of all, the setup process includes registering the application area, such as project name, project number, structure designation, and the like. First of all, the setup process involves (fully automatically) obtaining a sensor module identifier, such as a serial or registration number. First of all, the setup process includes obtaining geo-coordinates, for example GPS coordinates of the sensor module, first of all, the location of the sensor module. Preferably, the geocoordinates are obtained using the geolocation function, especially the GPS of the external adjustment device. In general, however, it is also contemplated that the sensor module includes a GPS sensor. To obtain geocoordinates with the highest possible accuracy, during the setup process, when obtaining geocoordinates, the installer may be asked to move the external setup device to a predetermined position relative to the sensor module, for example, in contact with a specified surface of the sensor module. First of all, the setup process involves identifying the time zone, date and/or time. Preferably, the hardware time zone, date and/or time of the external setting device is adopted. First of all, the setup process involves recording the exact installation position of the sensor module on the structure, primarily the exact installation position of the sensor module on the interception and/or stability structure. First of all, the setup process involves registering the exact designation, primarily the type designation, of the structure, primarily the intercepting and/or stability structure, to which the sensor module is attached. First of all, the setup process involves obtaining images, primarily photographs, of the installation situation, primarily the installation position of the sensor module. The images are preferably created using an external adjustment device. Alternatively, however, images can also be created by means of a sensor module camera or an external camera that is in wireless communication with the sensor module. First of all, the setup process involves recording the diameter of the rope of the structure, primarily the intercepting and/or stabilizing structure, to which the sensor module is attached using the connecting device.

In addition, an external network of sensors is proposed, which has several sensor remote monitoring devices covering different application areas, each of which includes sensor modules associated with different application areas, and each of which wirelessly, primarily directly, communicates with a common external unit analysis and/or forecasting, preferably each of which is in wireless direct communication with a common analysis and/or forecasting unit. Due to this, it is possible to obtain, process and/or convert into actions and/or instructions for action comprehensive and/or significant information about the risks of hazardous natural phenomena, primarily in one or more areas of application.

In addition, a structure is proposed, primarily equipment for protection against natural hazards, preferably an intercepting and/or stabilizing structure, such as a rockfall barrier, avalanche protection, rockfall curtain, slope strengthening, mudflow barrier and/or screen, which has at least at least one rope, in particular a tension wire rope, and at least one sensor module of the sensor remote monitoring device, the sensor module being attached to the rope. This makes it advantageous to obtain comprehensive and/or relevant information about the risks of natural hazards to the structure and/or in its immediate vicinity.

First of all, the structure includes at least one other rope. First of all, another sensor module of the sensor remote monitoring device is attached to another rope. It is also contemplated that it is possible that more than two sensor modules of the sensor remote monitoring device are associated with a structure, in particular that more than two sensor modules of the sensor remote monitoring device are attached to the structure.

The analysis and/or prediction method according to the invention and/or the remote sensor monitoring device according to the invention are not limited to the applications and embodiments described above. First of all, the analysis and/or prediction method according to the invention and/or the sensor remote monitoring device according to the invention for performing the mode of operation described herein may have individual elements, components, method steps and assemblies in a number different from the number mentioned herein.

Blueprints

Other advantages can be obtained from the following description of the drawings. The drawings show an exemplary embodiment of the invention. The drawings, description and claims contain numerous features in combination. Based on practical considerations, the specialist also has the opportunity to consider individual characteristics and combine them into other justified combinations.

Shown on:

Fig. 1 - schematic representation of an external sensor network with remote sensor monitoring devices,

Fig. 2 - schematic representation of the zone of application of the sensor remote monitoring device for an external network of sensors, made in the form of a structure,

Fig. 3 is a schematic side view of the sensor module of the sensor remote monitoring device attached to the rope structure,

Fig. 4 is another schematic perspective view of the sensor module of the sensor remote monitoring device,

Fig. 5 - schematic flow diagram of the sensor module setup process,

Fig. 6 is a schematic flow diagram of an analysis and/or prediction process based on an outdoor sensor network for protection against natural hazards, and

Fig. 7 is a schematic flow diagram of a method for near-sensor analysis of sensor data via sensor modules.

Description of the embodiment

In fig. 1 shows a schematic representation of an external network of 12 sensors. The external sensor network 12 is provided to at least record sensor data for the sensor network-based analysis and/or prediction method described below. The external sensor network 12 includes several sensor remote monitoring devices 36 (see FIG. 2). The external sensor network 12 extends over several different application areas 20. The 20 application areas can be located around the world. One sensor remote monitoring device 36 is assigned to each of several application zones 20. Each of the sensor remote monitoring devices 36 includes one or more sensor modules 10, which are thus also permanently assigned to respective application zones 20. In addition, in FIG. 1 shows an external analysis and/or forecasting unit 14, which, first of all, can also be correlated with an external sensor network 12. The external block 14 of analysis and/or forecasting is made in the form of a cloud. Alternatively, however, the external analysis and/or forecasting unit 14 can also be implemented as a single central server or server network. The sensor remote monitoring devices 36, preferably the sensor modules 10 of the corresponding sensor remote monitoring devices 36, communicate wirelessly with the external analysis and/or forecasting unit 14. The sensor remote monitoring devices 36, preferably the sensor modules 10 of the corresponding sensor remote monitoring devices 36, communicate directly with the external analysis and/or forecasting unit 14. The sensor remote monitoring devices 36, preferably the sensor modules 10 of the corresponding sensor remote monitoring devices 36, can be connected to an external analysis and/or forecasting unit 14 via a direct GSM mobile connection. The same external analysis and/or forecasting unit 14 interacts with all sensor modules 10 of all sensor devices 36 for remote monitoring of the external sensor network 12. An external analysis and/or forecasting unit 14 is provided for receiving sensor data from several sensor modules 10, 10', 10'' distributed over different application zones 20, 20', 20''. The external analysis and/or forecasting unit 14 includes communication means (not shown) for communication with the external network 12 of sensors.

The external analysis and/or forecasting unit 14 forms a common external analysis and/or forecasting unit 14 for all sensor modules 10 of the external sensor network 12. The external analysis and/or forecasting unit 14 collects identified sensor data from all sensor modules 10 of the external sensor network 12. The external analysis and/or prediction unit 14 includes a storage device 16 having at least one storage medium. An external analysis and/or forecasting unit 14 is provided for storing the collected sensor data of the sensor modules 10 of the external sensor network 12 in the memory device 16. An external analysis and/or forecasting unit 14 is provided for receiving, collecting and/or storing additional data from sensors external to the network 90 databases. Additional data from databases 90 external to the sensor network includes, among other things, additional information about the application area 20.

The external analysis and/or prediction unit 14 includes a processing unit 88 having at least one processor. The external analysis and/or forecasting unit 14 includes a work program for processing the collected and/or stored data, which can be called and executed by the processing unit 88. The external analysis and/or forecasting unit 14 is provided for analysis and/or processing by the working programs of collected and/or stored data. An external analysis and/or forecasting unit 14 is provided for interrelating the collected and/or stored data with each other using a work program. An external analysis and/or prediction unit 14 is provided to perform pattern recognition using a work program based on the collected and/or stored data.

An external analysis and/or forecasting unit 14 is provided to ensure availability for a group 18 of users of data processed and prepared using the work program and/or raw data received from sensor modules 10. A group of users 18 may, for example, access the analysis and/or forecasting external unit 14, primarily the user portal ("dashboard") of the analysis and/or forecasting external unit 14 using a display device 92, which can be performed primarily in the form of a PC or smartphone. Alternatively, it is also contemplated that the external analysis and/or prediction unit 14 sends data to the user group 18, primarily to the display devices 92 of the user group 18 (eg, in the form of messages). It is further contemplated that it is possible that the user group 18 includes the drone 34.

Some of the application zones 20 are structures 24. At least one of the application zones 20 is a structure 24 consisting of metal parts subject to atmospheric corrosion. The metal parts of the structure 24 are, for example, ropes 56 (cf. FIG. 2), especially tension wire ropes 228. Some of the application zones 20 formed by the structure 24 are equipment 32 for protection against natural hazards. An exemplary application area 20 in FIG. 1 is made in the form of a rockfall barrier 76. The rockfall barrier 76 has a rope 56 to which a sensor module 10 is attached. Another exemplary application area 20 in Fig. 1 is made in the form of an avalanche fortification 78. The avalanche fortification 78 has a rope 56 to which a sensor module is attached. 10. Another exemplary application area 20 in FIG. 1 is designed as a rockfall curtain 80. The rockfall curtain 80 has a rope 56 to which a sensor module 10 is attached. Another exemplary application area 20 in FIG. 1 is made in the form of strengthening the 82 slope. The slope reinforcement 82 has a rope 56 to which the sensor module 10 is attached. Another exemplary application area 20 in FIG. 1 is made in the form of a mudflow barrier 84 and/or a mudflow barrier. The debris flow barrier 84 and/or debris flow barrier includes a rope 56 to which a sensor module 10 is attached. Another exemplary application area 20 in FIG. 1 is made in the form of a screen 86. The screen 86 has a rope 56 to which a sensor module 10 is attached. Some of the application zones 20 formed by the structures 24 differ from the equipment 32 for protection against natural hazards. An exemplary application area 20 in FIG. 1 is designed as a suspension bridge 96. The suspension bridge 96 has a rope 56 to which a sensor module 10 is attached. Another exemplary application area 20 in FIG. 1 is made in the form of a stretcher 98 for the roof of the stadium. The stadium roof guy 98 has a rope 56 to which a sensor module 10 is attached. Another exemplary application area 20 in FIG. 1 is designed as a brace 100 for a wind turbine, in particular as a brace for a wind turbine mast. The wind turbine guy 100, primarily in the form of a wind turbine mast guy, has a rope 56 to which a sensor module 10 is attached. Another exemplary application area 20 in FIG. 1 is in the form of a façade guy 102. The façade guy 102 has a rope 56, to which the sensor module 10 is attached. Another part of the application zones 20' are represented by places without structures, for example, slope 94.

In fig. 2 shows an exemplary schematic view of one of the application zones 20, designed as a structure 24. Shown in FIG. 2, the structure 24 is made in the form of equipment 32 for protection against hazardous natural phenomena. The structure 24 shown in FIG. 2 is designed as an interception and/or stability device 222, primarily as an interception and/or stability structure. Shown in FIG. 2, the structure 24 is made in the form of a rockfall barrier 76. The rockfall barrier 76 includes a wire mesh 226, which, as an example, is made in the form of a ring mesh and is shown in FIG. 2 only in sections. The rings of the ring mesh in this case form the cells 226 of the wire mesh. Thus, the diameter of the ring mesh rings represents the size of the wire mesh mesh 226.

The application area 20, primarily the rockfall barrier 76, includes a sensor remote monitoring device 36. Associated with the application area 20, primarily the rockfall barrier 76, the sensor remote monitoring device 36 includes, for example, three sensor modules 10, 10', 10''. Sensor modules 10, 10', 10'' are respectively attached to different ropes 56, 56', 56'' of the rockfall barrier 76. Sensor modules 10, 10', 10'' are respectively placed in different areas of the rockfall barrier 76. One of the sensor modules 10 is located in the upper left end region of the rockfall barrier 76, as seen in the front view of the rockfall barrier 76. Another of the sensor modules 10' is located in the upper right end area of the rockfall barrier 76, as seen in the front view of the rockfall barrier 76. Another of the sensor modules modules 10'' are located in the lower left end area of the rockfall barrier 76, as seen in the front view of the rockfall barrier 76. Alternative placements of sensor modules 10, 10', 10'' and/or placement of additional sensor modules 10, 10' are contemplated. 10'' on the rockfall barrier 76. The ropes 56, 56', 56'' are respectively the tension wire ropes 228 of the rockfall barrier 76. When an impact body (not shown) strikes the rockfall barrier 76, the ropes 56, 56', 56' ' there are forces in the rope. The sensor modules 10, 10', 10'' are respectively placed on the upper side of the corresponding associated rope 56, 56', 56'', primarily when viewed relative to the gravity direction 126.

In fig. 3 shows a schematic side view of a sensor module 10 attached to a rope 56 of a sensor remote monitoring device 36. The sensor module 10 includes an attachment device 224. The attachment device 224 is provided for directly attaching the sensor module 10 to the rope 56 of the structure 24. The attachment device 224 includes a rope receiving element 104. The rope receiving element 104 for receiving the rope is designed in the form of a U-shaped hook. Connection device 224 includes a tension member 106. Connection device 224 includes another tension member 108. Tension members 106, 108 are in the form of nuts. The rope receiving element 104 has a thread at each end for screwing on the tension elements 106, 108. To attach the sensor module 10 to the rope 56, the rope receiving element 104 is put on the rope 56, directed through the tunnel-shaped recesses 110 inside the sensor module 10 and secured on the side of the sensor module opposite to the rope 56 module 10 by screwing the tension elements 106, 108 onto the rope receiving element 104. The tension elements 106, 108 are screwed to the rope receiving element 104 so tightly that one side of the rope 56 is pressed by the rope receiving element 104 to the outside of the sensor module 10. The connecting device 224 is provided for fastening the sensor module 10 to the rope 56 without slipping relative to the longitudinal axis of the rope 56. The connecting device 224 is provided for attaching the sensor module 10 to the rope 56 without the possibility of rotation relative to the longitudinal axis of the rope 56.

In fig. 4 shows a schematic perspective view of the sensor module 10 of the remote monitoring device 36 (without the connecting element 224), primarily the top surface 120 of the sensor module 10. The illustrated sensor module 10 is provided for use in an external sensor network 12.

Sensor module 10 includes an external corrosion sensor 38 . An external corrosion sensor 38 is provided for obtaining external corrosion measurement data. An external corrosion sensor 38 is provided for measuring the degree of corrosion. An external corrosion sensor 38 is provided to measure the rate of removal of the anti-corrosion layer. The external corrosion sensor 38 is designed as an AFM sensor. External corrosion sensor 38 includes electrodes 112, 114. In the example shown, external corrosion sensor 38 includes exactly five electrodes 112, 114. Electrodes 112, 114 are oriented parallel to each other. Two electrodes 114 are placed respectively above and below the central electrode 112 in a common plane. The central electrode 112 forms the anode. Other electrodes 114 form the cathode. The electrodes 112, 114 have at least substantially identical external shape to each other. The surfaces of the cathode-forming electrodes 114 have a more noble metal than the surface of the anode-forming central electrode 112. In the example shown, the surface of the cathode-forming electrodes 114 is made of steel, and the surface of the anode-forming electrode 114 is made of zinc, primarily a zinc layer of steel wire. The external corrosion sensor 38 in the form of an AFM sensor has an air gap between each of the electrodes 112, 114. The air gap acts as an insulator. Between the cathode electrodes 114 and the anode electrode 112 there is a distance of no more than 0.4 mm, preferably no more than 0.3 mm, and most preferably no more than 0.2 mm. There is also a distance between the cathode electrodes 114 of no more than 0.4 mm, preferably no more than 0.3 mm, and most preferably no more than 0.2 mm. At its lateral ends, the external corrosion sensor 38 has two end caps 116, 118 designed as insulators. The end caps 116, 118 serve as a holder for the electrodes 112, 114. The electrical contacts of the electrodes 112, 114 are directed inside the end caps 116, 118. The end caps 116, 118 and/or the electrical contact inputs of the electrodes 112, 114 into the interior of the housing 44 of the sensor module 10 are at least substantially sealed. In a dry state, due to the air gap, no current passes through the connection from the anode to the cathode. When the external corrosion sensor 38 is wetted, for example, by condensation moisture or precipitation moisture, current can flow through conductive particles dissolved in water, for example ions, the source of which is primarily one of the electrodes 112, 114. Difference in redox potentials different materials of the anode electrode 112 and cathode electrodes 114 leads to the occurrence of such an electric current. When an electric current passes, material is removed from the anode. The strength of the electric current is proportional to the removal of material. The passage of electric current depends on the type and amount of chemicals dissolved in water. For example, increasing the amount of salts, such as sulfates or table salt, leads to an increase in the strength of the electric current. An external corrosion sensor 38 is located on the top surface 120 of the sensor module 10. To measure the corrosion current generated by corrosion, the external corrosion sensor 38 includes at least one charge storage 58. The charge storage 58 is made in the form of a capacitor. The charge store 58 is charged to a maximum level under the influence of an electrical corrosive current. When the charge store 58 is charged to its maximum charge by the electrical corrosion current, the charge store 58 is discharged in a current pulse. The sensor module 10, primarily the external corrosion sensor 38, includes an ammeter 60. The ammeter 60 is provided for measuring the current pulses generated by the discharge current of the charge storage device 58. The sensor module 10 is provided for detecting external corrosion measurement data based on the current pulses generated by the discharge current of the charge storage device 58.

The sensor module 10 has an acceleration sensor 50. The acceleration sensor 50 is located inside the housing 44 of the sensor module. An acceleration sensor 50 is provided for detecting vibrations of the sensor module 10. The sensor module 10 includes an orientation sensor 52. An orientation sensor 52 is provided to detect the relative orientation of the sensor module 10 relative to the gravity direction 126, primarily the relative orientation of the top side 120 of the sensor module 10. The sensor module 10 includes a rope tension sensor 30. The rope tension sensor 30 is provided for detecting a force acting on the rope 56 to which the sensor module 10 is attached. The rope tension sensor 30 includes a strain gauge 54. The sensor module 10 includes a rope contact element 128. The rope tension sensor 30 includes a rope contact element 128 . The rope contact element 128 is located on the outer side, in particular on the underside 130 of the sensor module 10. The strain gauge 54 is provided for indirectly measuring the tension force of the rope through the degree and/or magnitude of deformation caused by the rope 56 of the rope contact element 128 of the sensor module 10. Strain gauge 54 located separately from the rope 56, the force of which is controlled by the rope tension force sensor 30. The strain gauge 54 is located on the side of the rope contact element 128 opposite the rope 56. The strain gauge 54 is located on the inside of the sensor module housing 44, primarily inside the sensor module housing 44. The rope tension force sensor 30 is at least partially integral with the connecting device 224 of the sensor module 10. The surfaces, especially the rope contact surfaces, of the sensor module 10 in the (proximal) region of the rope contact element 128 and in the (proximal) region of the connecting element devices 224 lie in planes that are different from each other, but are nevertheless preferably parallel to each other. The contact surfaces of the rope contact element 128 and the connecting device 224 are located along the longitudinal direction 132 of the sensor module 10 and/or the rope 56. The contact surfaces of the rope 56 and the rope contact element 128 and/or the sensor module 10 are spaced apart. As a result of the contact of the rope 56 to the sensor module 10 in the area of the contact element 128 of the rope and in the area of the connecting device 224, the rope 56 is deviated from the straight direction.

To partially deflect the rope 56, a connecting device 224 and/or a rope contact element 128 are provided. Since the connecting device 224 makes a significant contribution to the deflection of the rope 56, the connecting device 224, especially its rope receiving element 104, forms a significant part of the rope tension force sensor 30. Under the action of the rope tension force applied to the rope 56, primarily the pulling force, the rope 56, preferably deflected by means of the rope contact element 128 and the connecting device 224, is deflected back out of deflection. Under the action of the rope tension force applied to the rope 56, primarily the pulling force, the rope contact element 128 is subject to bending. In the illustrated embodiment of the invention, the rope contact element 128 is made in the form of a metal, especially aluminum plate. The strain gauge 54 located on the rope contact element 128, especially on the inner side of the rope contact element 128, is subject to tension or compression (unevenly) when the rope contact element 128 is bent. Based on the tension of the strain gauge 54, the rope tension force sensor 30 detects the force that caused the rope contact element 128 to bend.

Sensor module 10 includes an energy storage device 124. The energy storage device 124 may be in the form of a battery, most notably a battery with a minimum service life of 10 years under normal conditions. However, in the example shown in FIG. 4, the energy storage device 124 is configured as a battery 62. The energy storage device 124 is configured to supply energy to at least one component of the sensor module 10, such as at least one of the sensors of the sensor module 10 and/or to at least one computing unit 66 of the sensor module 10. In the example shown, the electrical corrosion current of the external corrosion sensor 38 serves as a charging current to electrically charge the battery 62. The sensor module 10 includes an energy harvesting unit 68 to generate the current From the temperature difference inside the sensor module 10, preferably inside the sensor module housing 44, an energy harvesting unit 68 is provided. The energy harvesting unit 68 includes a thermoelectric generator for generating electricity.

Sensor module 10 includes an environmental sensor unit 122. The environmental sensor assembly 122 includes at least one environmental sensor 40, preferably multiple environmental sensors 40, such as a thermometer, hygrometer, ombrometer, pyranometer, anemometer, barometer, and/or at least additional sensors. devices such as measuring devices for detecting trace gases, salt concentrations or aerosol concentrations and the like. An environmental state unit 122, primarily an environmental state sensor 40, is provided for obtaining measurement data of tropospheric parameters. The housing of the sensor module 44 is hermetically sealed. The sensor module housing 44 is provided to seal the interior of the sensor module housing 44 from the environment. At least one of the environmental sensors 40 includes a sensing element (not shown) that extends from the sensor module housing 44 of the sensor module 10. The sensing element is hermetically sealed to maintain a sealed seal. The housing 44 of the sensor module is made without cable entries. The housing 44 of the sensor module is made without cable outlets. The housing 44 of the sensor module is made without push-button switches. The housing of the sensor module 44 is made without mechanical switches. The housing of the sensor module 44 is made without external antennas.

The sensor module 10 includes a communication unit 42. The communication unit 42 is provided for wireless and/or direct transmission of sensor data, especially the environmental sensor unit 122 and/or the external corrosion sensor 38, to the external analysis and/or prediction unit 14. A communication unit 42 is provided for transmitting sensor data from a corresponding sensor module 10 to a common external analysis and/or prediction unit 14 without detours through one or more sensor data collection points. The communication unit 42 includes a GSM transmission and reception module. The communication unit 42 is equipped with a SIM card that allows the amount of data to be transferred for approximately 10 years of continuous operation of all sensors of the sensor module 10 (about 1 GB). The communication unit 42 does not have external antennas. The communication unit 42 includes a built-in antenna.

The sensor module 10, especially the communication unit 42, includes a wireless camera interface. A wireless camera interface is provided for connection to an external camera 46. The external camera 46 may be configured, for example, as a wildlife camera and/or monitoring a sensor module 10 and/or a surveillance camera structure 24. First of all, the external camera 46 is designed as a Bluetooth camera.

The sensor remote monitoring device 36 and/or the external sensor network 12 includes an external camera 46. In addition, it is contemplated that the communication unit 42 may have an additional communication interface with a reduced transmission range, which, in the event of failure to communicate with the external analysis unit 14 and /or prediction, is provided for transmitting sensor data to another, preferably adjacent, sensor module 10' of the external sensor network 12, which is associated with the same application area 20 or is associated with another, primarily adjacent, application area 20.

The sensor module 10 includes a computing unit 66. The computing unit 66 is configured to monitor, control, and/or regulate internal functions of the sensor module 10, for example, sensors of the sensor module 10, external sensors, such as an external camera 46, for a communication unit 42, for example for the purpose of encrypting sensor data transmitted by the communication unit 42, and the like. The computing unit 66 has its own specially developed operating system, not based on existing operating systems.

The sensor module 10 has a preliminary analysis unit 64. A preliminary analysis unit 64 is integral with the computing unit 66. A preliminary analysis unit 64 is provided for performing a preliminary analysis of measurement data, especially raw measurement data, of at least one of the sensors of the sensor module 10. A preliminary analysis unit 64 is provided for performing a preliminary analysis measurement data, especially raw measurement data, of at least one external sensor connected to the sensor module 10, such as an external camera 46. A pre-analysis unit 64 is provided for independently selecting which portion of the sensor measurement data set is to be transmitted via the communication unit 42. A pre-analysis unit 64 is provided for independently selecting whether or not to transmit a set of sensor measurement data via the communication unit 42 . A preliminary analysis unit 64 is provided for establishing an interval between transmissions of the communication unit 42 based on measurement data from at least one sensor of the sensor module 10 and/or at least one external sensor connected to the sensor module 10, for example an external camera 46. A preliminary analysis unit 64 is provided for establishing, based on the measurement data of at least one sensor of the sensor module 10 and/or at least one external sensor connected to the sensor module 10, for example an external camera 46, control of the waiting phases and/or measurement intervals of at least this sensor and/or at least one other sensor.

The sensor remote monitoring device 36 includes an external activation and/or deactivation element 48. The external activation and/or deactivation element 48 is provided to activate and/or deactivate the sensor module 10 depending on the orientation of the external activation and/or deactivation element 48 relative to the housing 44 sensor module. The external activating and/or deactivating element 48 is made in the form of an external activating and/or deactivating magnet, which, due to magnetic force, is attracted by at least part of the housing 44 of the sensor module and/or due to magnetic force attracts at least part of the housing 44 sensor modules. The sensor module housing 44 includes an activation and/or deactivation surface 136. The activation and/or deactivation surface 136 is composed of a magnetic material, preferably a ferromagnetic material. While the activation and/or deactivation element 48 is located in the region of the activation and/or deactivation surface 136 on the sensor module body 44, the sensor module 10 is in a deactivated state. As long as the activation and/or deactivation element 48 is located outside the region of the activation and/or deactivation surface 136 on the sensor module housing 44 and/or while the activation and/or deactivation element 48 is completely removed from the sensor module housing 44, the sensor module 10 is in an activated state.

It goes without saying that the reverse mode of action is also assumed to be possible. Depending on whether the activating and/or deactivating element 48, especially the activating and/or deactivating magnet, is placed in the region of the activating and/or deactivating surface 136 or not, the sensor module is in an activated state or in a deactivated state (or vice versa).

The sensor module 10 includes a tuning module 70. The setting module 70 is provided for wireless communication with an external installer setting device 72, such as a smartphone, to configure the sensor module 10. The sensor module 10, especially the setting module 70, includes a setting element 74 that is readable or used to issue a control action by external configuration device 72 to initiate configuration of the sensor module 10. In the shown in FIG. In example 4, setting element 74 is made in the form of a QR code. In the case shown, a QR code is applied to the housing of the sensor module 44. The configuration module 70 is provided primarily for performing an at least partially automated configuration process 134 (cf. FIG. 5) in cooperation with an external configuration device 72.

In fig. 5 shows a schematic flow diagram of an at least partially automated configuration process 134. In at least one setup step 138, the sensor module 10 is delivered to the application area 20 and installed in the application area 20. In at least one other setting step 140, the sensor module 10 is activated. For example, to activate, in a setting step 140, the activation and/or deactivation element 48 is removed from the region of the activation and/or deactivation surface 136. In at least one subsequent setting step 142 Setting element 74 is read. At setup step 142, for example, a QR code applied to the sensor module housing 44 is scanned by an external setup device 72. It is conceivable that the setting element 74 already contains the basic data of the sensor module 10, which is automatically transferred to the setting process 134 carried out by the setting module 70. At least one other setup step 144 on the external setup device 72 automatically opens the application. At setup step 144, the basic data of the sensor module 10 (eg, serial number, sensor module type, etc.) already obtained from the setup item 74 is automatically transferred to the application. At least one other configuration step 146 starts an application-driven configuration process, primarily a step-by-step configuration process. The application-guided configuration process 134 records the characteristics of the sensor module 10, installer, application area 20, and the like, already described above. In at least one other tuning step 148, the tuning process is completed and the recorded data is transmitted (directly and wirelessly) from the communication unit 42 and/or from the external tuning device 72 to the external analysis and/or prediction unit 14.

In fig. 6 shows a schematic flow diagram of a sensor network-based analysis and/or prediction method for protection against natural hazards.

In at least one step 182, sensor modules 10, 10', 10'' of the external sensor network 12 are installed in the application area 20 in anticipation of the installation of natural hazard protection or in anticipation of a planned construction event. In this case, sensor modules 10, 10', 10'' of the external sensor network 12 can be installed to identify a local need for safety measures in the vicinity of the application area 20, for example on a slope 94, which previously lacked safety measures with respect to natural hazards. Alternatively or additionally, in at least one other step 184, the sensor modules 10, 10', 10'' of the external sensor network 12 are installed in the application area 20, designed as an already built structure 24. In this case, sensor modules 10, 10', 10'' of the external sensor network 12 are attached to the structure 24, primarily to the ropes 56 of the structure 24.

In at least one other method step 150, electronic sensor data from distributed sensor modules 10, 10', 10'' of the external sensor network 12 is supplied to an external analysis and/or forecasting unit 14. The external analysis and/or forecasting unit 14 collects the received sensor data. The acquired and collected sensor data includes at least external corrosion measurement data, impact sensor data, rope tension sensor data, and troposphere measurement data. The tropospheric measurements data are geographically referenced to a corrosion data set, an impact sensor data set, and a rope tension sensor data set. In at least one other method step 152, the received and collected sensor data from the external sensor network 12 is stored in a storage device 16 of a common external analysis and/or forecasting unit 14. In at least one other step of the method 154, the received, collected and stored sensor data of the external sensor network 12 is analyzed by an external analysis and/or forecasting unit 14 to identify the risk of a natural hazard in the respective sensor module application zones 20, 20', 20''. 10, 10', 10'' external network 12 sensors. The sensor data analysis performed at method step 154 also directly inputs at least one additional information about the respective application area 20 that is different from external corrosion measurement data, from impact sensor data, from rope tension sensor data, and from troposphere measurement data. .

At least one other method step 156 identifies the risk of a natural hazard based on analysis of sensor data from the external sensor network 12 in combination with additional information about application zones 20, 20', 20''. Additional information about the application area 20 that is directly included in the analysis performed at method step 154 may be the degree of wildlife activity and/or human activity, such as tourist activity, in the vicinity of the application area 20. Increased activity of wild animals and/or increased anthropogenic activity may lead to an increase in the risk of a hazardous natural phenomenon identified in step 156. Other additional information about application zone 20 that is directly included in the analysis performed in method step 154 may be air quality data from the immediate vicinity of application zone 20. An increase in the concentration of identified air pollutants leads to an increase in the risk of the hazardous natural phenomenon identified in step 156.

In at least one other method step 158, the risk of a natural hazard identified by the external analysis and/or forecasting unit 14 is made available to an authorized user group 18. The risk of a hazardous natural phenomenon identified at method step 156 and made available at method step 158 includes the remaining service life of structures 24 identified on the basis of sensor data. Identified at method step 156 and made available at method step 158, the risk of a hazardous natural phenomenon includes the identified based on the sensor data, the rate of removal of the anti-corrosion layer of metal parts with an anti-corrosion layer, such as wire ropes 228. At least one other method step 160 determines, taking into account the detected rate of removal of the anti-corrosion layer, a corrosion classification of the geographic environment of the zone 20, 20', 20 '' application, especially the external environment of each sensor module 10 installed in the corresponding application zone 20. To do this, based on real external corrosion measurement data obtained over a long period of time (for example, at least one month, at least one year or at least two years) determine the average rate of removal of the protective layer, which is compared with the normalized rates of removal of the protective layer identified for corrosion classifications (for example, ISO 12944-1:2019-01), which allows assigning the appropriate corrosion class.

In at least one other step 162, methods determine natural hazard risks, which include predictions of natural hazard risks. At method step 162, risk forecasts for natural hazards are generated based on historically identified sensor data indicators. Alternatively or additionally, at method step 162, natural hazard risk forecasts are generated based on additional information about the application area 20 identified in the past. At method step 162, based on the sensor data and/or additional information, pattern recognition is performed to determine individual sensor data scores and/or correlations of data scores from different sensors that indicate an increase or decrease in the risk of a natural hazard, such as the risk of a rockfall. At method step 162, for example, pattern recognition is performed primarily based on impact data from impact sensor 28 and/or based on data from rope force sensors 30 of sensor module 10, together with a series of troposphere measurement data measurements from sensor module 10 and/or or together with additional information about the application zone 20, on the basis of which a risk forecast of a hazardous natural phenomenon, performed as an impact forecast, is identified. At method step 162, the sensor data collected and stored by the analysis and/or forecasting unit 14 is analyzed, preferably in combination with additional information about the application areas 20 collected and stored by the analysis and/or forecasting unit 14.

In at least one other method step 186 in the application area 20, which has sensor modules 10 installed in method step 182, and in which protection against a natural hazard has not previously been installed, the need to install protection against a natural hazard is assessed. dangerous natural phenomenon depending on the method of risk of a dangerous natural phenomenon identified, first of all, at step 156 and/or on the method of predicting the risk of a dangerous natural phenomenon, identified, first of all, at step 162.

Depending on the identified risk of a natural hazard, at least one other method step 188 adapts an already planned construction event, including the installation of wire mesh 226 and/or wire rope 228. At least one partial method step 190 of the step 188 of the method, the selection of the type of anti-corrosion layer of wire mesh 226 and/or wire rope 228 is made based on the identified risk of a natural hazard, primarily based on the identified removal rate of the anti-corrosion layer. In at least one partial method step 192 of method step 188, the thickness of the anti-corrosion layer of the wire mesh 226 and/or wire rope 228 is selected based on the identified risk of a natural hazard, primarily based on the identified removal rate of the anti-corrosion layer.

In at least one partial method step 194 of method step 188, the thickness of the wire mesh 226 and/or wire rope 228 is selected based on the identified risk of the natural hazard, primarily based on the identified forecast of the risk of the natural hazard (e.g., expected frequency and/or extent of events). In at least one partial method step 196 of method step 188, selection of the wire mesh 226 and/or wire rope 228 material is made based on the identified risk of the natural hazard, primarily based on the identified forecast of the risk of the natural hazard (e.g., expected frequency and/or extent of events). In at least one partial method step 198 of method step 188, the size of the wire mesh 226 is selected based on the identified risk of the natural hazard, primarily based on the identified forecast of the risk of the natural hazard (eg, expected locations of events). In at least one partial method step 200 of method step 188, the mesh size of the wire mesh 226 is selected based on the identified risk of the natural hazard, primarily based on the identified prediction of the risk of the natural hazard (eg, event type).

In at least one other method step 22, based on the natural hazard risk identified in step 156, a maintenance plan is created for the application area 20, preferably for the structure 24. The maintenance plan is determined depending on the identified remaining service life of the structure 24, primarily specified parts of the structure 24. At step 22 of the method, the sequence of maintenance of several separately located structures 24 is determined. The sequence of maintenance is determined based on the ranking of various structures 24 determined by the state of corrosion of the structure 24 and/or the remaining service life of the structure 24. At step 22 of the method, the technical date is also determined maintenance of structure 24. The maintenance date is determined based on the measured corrosion status of structure 24 and/or the measured remaining life of structure 24. The maintenance date can be flexibly adjusted depending on the measured corrosion status of structure 24 and/or the measured remaining life of structure 24 , if significant changes in these quantities occur over time.

At least one partial method step 164 of method step 22 organizes maintenance personnel based on identified natural hazard risks in multiple application areas 20. In this case, the specified maintenance dates are distributed among the maintenance personnel in such a way that allows for the most uniform workload of the maintenance personnel to be ensured. In this case, the specified maintenance dates are distributed among the maintenance personnel of various maintenance bases in a manner that allows for the minimum possible total travel time to the serviced facilities 24. In this case, the specified maintenance assignments are distributed among the maintenance personnel in a manner that allows for exact compliance maintenance procedures performed and the individual skills of the operating personnel. At least one other partial method step 166 of method step 22 organizes equipment for maintenance based on identified risks of a natural hazard in multiple application areas 20.

In this case, the available maintenance equipment is distributed over specified maintenance periods in such a way that the capacity utilization of the maintenance equipment is as uniform as possible. In this case, the available maintenance equipment is distributed among the various maintenance bases in a manner that allows for the minimum possible downtime of the maintenance equipment, for example for travel to the structures to be maintained 24. At the same time, the individual skills of the maintenance personnel in the operation of the relevant maintenance equipment taken into account when distributing available maintenance equipment among available maintenance personnel. At least one other partial method step 168 of method step 22 organizes consumables based on identified natural hazard risks in multiple application zones 20. In this way, the ordering and/or delivery of consumables can be tailored to identified maintenance deadlines in a manner that allows for the lowest possible inventory. In this case, the distribution of consumables among service personnel can be adjusted to upcoming service dates in such a way that the total number of consumables transported for one service is as small as possible.

In at least one method step 170, the impact signal indicating the impact of the impact body is detected by at least one impact sensor 28 of the sensor module 10, which is associated with the application area 20 configured as a rockfall barrier 76. Alternatively, in at least one method step 172, a rope tension signal indicating a backfill event, primarily a debris flow, can be detected by at least one rope tension sensor 30 of the sensor module 10, which is correlated with the anti-debris flow. barrier 84 zone 20 application. In at least one other method step 174, after detecting an impact in method step 170 and/or after detecting a backfilling event in method step 172, a preferably automated decision is made depending on the degree and/or type of impact and/or backfilling event, primarily , through analysis and/or prediction unit 14, as to whether a maintenance order or immediate repair will be initiated. At least one other method step 176 initiates a maintenance order. A maintenance order is initiated if the force of the impact and/or backfill event measured by the sensor modules 10 indicates that the rockfall barrier 76 and/or debris flow barrier 84 were not seriously damaged by the impact and/or backfill event and/or were damaged only to that extent that a sufficient protective effect against possible further events still exists. A maintenance order is initiated if the degree of impact and/or backfill measured by the sensor modules 10, that is, for example, the sensor data received during the event indicates that the rockfall barrier 76 and/or mudflow barrier 84 were not severely damaged by the impact and/or or by a backfill event and/or were damaged only to such an extent that a sufficient protective effect against possible further events still exists. At least one other method step 178 initiates an immediate repair order. An immediate repair order is initiated if the force of the impact and/or backfill event measured by the sensor modules 10 indicates that the rockfall barrier 76 and/or debris flow barrier 84 have been severely damaged by the impact and/or backfill event and/or damaged to such an extent that that a sufficient protective effect against possible further events no longer exists. An immediate repair order is initiated if the type of impact event and/or backfill event measured by the sensor modules 10, that is, for example, the received sensor data during the event indicates that the rockfall barrier 76 and/or mudflow barrier 84 were severely damaged by the impact and/or or a backfill event and/or damaged to such an extent that a sufficient protective effect against possible further events no longer exists.

At at least one other method step 180, which may be used primarily to support the decision-making process at method step 174 or which may also be performed at any other time, depending on the outcome and/or value of the identified natural hazard risk phenomena trigger the deployment of the drone 34. The drone 34 may be configured as a maintenance drone or as a reconnaissance drone. At method step 180, depending on the degree and/or type of impact on the rockfall barrier 76 and/or on the backfill event in the mudflow barrier 84, a decision is made, preferably automated, primarily through analysis and/or forecasting unit 14, to initiate deployment drone or about abandoning it.

In at least one other method step 202, based on the natural hazard risk method identified in step 156, a corrosion map is created containing corrosion data and including at least one application zone 20. To do this, at method step 202, the coordinates of the location of the corresponding sensor modules 10 installed in the application zone 20 are entered as additional information about the application zone 20. The corrosion map shows the distribution of corrosion data, primarily the corrosion intensity, over the geographical extent of the application zone 20 and/or the length of the structure 24 forming the application zone 20. In at least one other method step 26, the corrosion map is transferred to a building information modeling (BIM) system for implementation, for example, as equipment 32 for protection against natural hazards of the application zone 20. In at least one other method step 204, based on the identified corrosion map, a primarily local optimization is carried out, for example, as equipment 32 for protection against natural hazards of the application zone 20. At method step 204, for example, a portion of the rockfall barrier 76, slope reinforcement 82, or the like is reinforced. For example, a portion of the rockfall barrier 76, slope reinforcement 82, or the like is provided with wire mesh 226 and/or wire rope 228 with increased tensile strength, increased anti-corrosion coating thickness, increased wire thickness, and the like. In at least one other method step 206, the corrosion map is populated with simulated corrosion data outside the surrounding area of the application zone 20, that is, primarily in the area without sensor modules 10, 10', 10'' of the external sensor network 12. At method step 206, corrosion data in areas of the corrosion map that extend beyond the surrounding area of the application zone 20, that is, that are primarily free from the sensor modules 10, 10', 10'' of the external sensor network 12, is determined based on sensor data from sensor modules 10, 10', 10'' in adjacent application zones 20'. Alternatively or additionally, at method step 206, corrosion data in areas of the corrosion map that extend beyond the surrounding area of the application zone 20, that is, that are primarily free from the sensor modules 10, 10', 10'' of the external sensor network 12 , is determined based on sensor data from sensor modules 10, 10', 10'' in geographically and/or climatically similar application zones 20''.

In fig. 7 shows a schematic flow diagram of a method for near-sensor (pre-)analysis of sensor data by sensor modules 10. At least one method step 208 records raw measurement data from the sensors of the sensor module 10. Method step 208 also records raw measurement data from connected to the sensor module 10 by external sensors, for example from an external camera 46. In at least one other method step 210, the raw measurement data is analyzed in terms of data processing by a pre-analysis unit 64 within the sensor module. In at least one partial method step 212 of method step 210, pre-analysis unit 64 uses analysis of the raw measurement data to independently select what portion of the raw measurement data is to be sent to analysis and/or prediction unit 14. In at least one partial method step 212, for each raw measurement data point and/or for each raw measurement data set, a decision is made as to whether the raw measurement data point and/or each raw measurement data set is to be sent to analysis unit 14 and /or forecasting. In at least one other partial method step 214 of method step 210, based on the analysis of the raw measurement data, the transmission interval is determined in which the communication unit 42 establishes a connection with the analysis and/or prediction unit 14 to transmit data. In at least one other partial method step 216 of method step 210, the measurement interval of one or more sensors of the sensor module 10 is determined based on the analysis of raw measurement data. In at least one other partial method step 218 of method step 210, based on the analysis raw measurement data determines the duration of the sleep phases of one or more sensors of the sensor module 10. At least one other partial method step 220 of the method step 210, based on the analysis within the sensor module of the images of the external camera 46, determines the need to detect the transmission of the corresponding images to the analysis unit 14 and/or forecasting. In partial method step 220, the newly acquired images are compared with reference images, for example, with previously acquired images of the same image region. If the new image differs significantly from the reference image, the new image is transmitted to analysis and/or prediction unit 14. Thus, in the case of a significant coincidence of the new image with the reference one, the new image is not transmitted to the analysis and/or prediction unit 14.

REFERENCE SYMBOLS

10 Sensor module

12 External sensor network

14 Analysis and/or forecasting block

16 Storage device

18 User group

20 Application area

22 step method

24 Construction

26 step method

28 Shock sensor

30 Rope tension sensor

32 Equipment for protection against natural hazards

34 Drone

36 Sensor remote monitoring device

38 External corrosion sensor

40 Environmental sensor

42 Communication block

44 Sensor module housing

46 External camera

48 Activating and/or deactivating element

50 Acceleration sensor

52 Orientation sensor

54 Strain gauge

56 Rope

58 Charge storage

60 Ammeter

62 Battery

64 Pre-analysis block

66 Computing unit

68 Energy harvesting device

70 Setting module

72 External setting device

74 Setting item

76 Anti-rockfall barrier

78 Avalanche protection

80 Anti-rockfall curtain

82 Strengthening the slope

84 Anti-mudflow barrier

86 Screen

88 Processing unit

90 Database external to the sensor network

92 Display device

94 Slope

96 Suspension Bridge

98 Stretching for the stadium roof

100 Stretching for wind turbine

102 Facade extension

104 Rope receiving element

106 Tension element

108 Other tension element

110 Notch

112 Electrode

114 Electrode

116 End cap

118 End cap

120 Top side

122 Environmental sensor block

124 Energy storage

126 Direction of gravity

128 Rope contact element

130 Bottom side

132 Longitudinal direction

134 Setup process

136 Activating and/or deactivating surface

138 Setting step

140 Setting step

142 Setting step

144 Setting step

146 Setting step

148 Setting step

150 step method

152 Method step

154 Method step

156 Method step

158 Method step

160 step method

162 Method step

164 Partial method step

166 Partial method step

168 Partial method step

170 step method

172 Method step

174 Method step

176 Method step

178 Method step

180 step method

182 Method step

184 Method step

186 Method step

188 Method step

190 Partial method step

192 Partial method step

194 Partial method step

196 Partial method step

198 Partial method step

200 Partial method step

202 Method step

204 Method step

206 Method step

208 Method step

210 Method step

212 Partial method step

214 Partial method step

216 Partial method step

218 Partial method step

220 Partial method step

222 Intercepting and/or stability device

224 Connecting element

226 Wire Mesh

228 Wire rope.

Claims (47)

1. A method of analysis and/or forecasting based on a network of sensors for protection against hazardous natural phenomena, including at least the steps of the method (150, 152, 154, 156, 158): - receiving and collecting electronic sensor data from distributed sensor modules (10, 10', 10'') of an external network (12) of sensors in an external analysis and/or forecasting unit (14), wherein the sensor data includes at least external corrosion measurement data, impact sensor data, and/or rope tension sensor data, wherein the sensor data includes at least troposphere measurement data, and wherein at least one data set is associated with each external corrosion measurement data set measurements of troposphere parameters, - saving the received data from external network sensors (12) sensors in the storage device (16) of the external analysis and/or forecasting unit (14), - analysis of the received data from sensors of the external network (12) of sensors to identify the risk of a dangerous natural phenomenon in the relevant zones (20, 20', 20'') of the use of sensor modules (10, 10', 10'') of the external network (12) of sensors by external block (14) of analysis and/or forecasting, and the analysis to identify the risk of a dangerous natural phenomenon directly receives at least one additional information about the zone (20, 20', 20'', different from the external corrosion measurement data and the tropospheric parameter measurement data ) applications, and - providing the analysis and/or forecasting of the risk of a dangerous natural phenomenon identified through an external block (14) to a group (18) of users, characterized in that, based on the identified risk of a dangerous natural phenomenon, a maintenance plan is drawn up for the zone (20, 20', 20'') of application and/or after detection of an impact, and/or after detection of a backfill event, depending on the degree and/or type of impact and/or backfill event, initiate a maintenance order or immediate repair. 2. The method of analysis and/or forecasting according to claim 1, characterized in that at least one of the application zones (20, 20', 20'') is a structure (24) consisting of metal parts subject to atmospheric corrosion, and that The risk of a hazardous natural phenomenon presented to a group (18) of users includes the remaining service life of the structure (24) identified on the basis of sensor data. 3. The method of analysis and/or forecasting according to claim 1 or 2, characterized in that the provided risk of a dangerous natural phenomenon includes the rate of removal of the corrosion protection layer of metal parts with an anti-corrosion layer, identified on the basis of sensor data. 4. The method of analysis and/or forecasting according to claim 3, characterized in that the corrosion classification of the geographic external environment of the zone (20, 20', 20'') of application is set taking into account the identified rate of removal of the anti-corrosion layer. 5. The method of analysis and/or forecasting according to one of the previous paragraphs, characterized in that in at least one zone (20, 20', 20'') of use there are sensor modules (10, 10', 10'') of the external network ( 12) sensors are installed before installation of means of protection against a dangerous natural phenomenon, and that the assessment of the need to install means of protection against a dangerous natural phenomenon is subsequently carried out depending on the identified risk of a dangerous natural phenomenon. 6. A method of analysis and/or forecasting according to one of the previous paragraphs, characterized in that in at least one zone (20, 20', 20'') of use there are sensor modules (10, 10', 10'') of the external network ( 12) sensors are installed before the planned construction event, and that the planned construction event is subsequently adapted depending on the identified risk of a hazardous natural phenomenon. 7. The method of analysis and/or forecasting according to claim 6, characterized in that the construction event includes the installation of wire mesh (226) and/or wire rope (228), and the choice of the type and/or thickness of the anti-corrosion layer of the wire mesh (226 ) and/or wire rope (228) is carried out based on the identified risk of a hazardous natural phenomenon. 8. The method of analysis and/or forecasting according to claim 6 or 7, characterized in that the construction event includes the installation of wire mesh (226) and/or wire rope (228), and the choice of the thickness of the wire and/or material of the wire mesh ( 226) and/or wire rope (228) is carried out on the basis of the identified risk of a hazardous natural phenomenon and/or the selection of the size of the wire mesh (226) and/or the size of the cells of the wire mesh (226) is carried out on the basis of the identified risk of a hazardous natural phenomenon. 9. Method of analysis and/or forecasting according to one of the preceding paragraphs, characterized in that additional information about the zone (20, 20', 20'') of application includes at least the location coordinates of the corresponding ones installed in the zone (20, 20', 20'') application of sensor modules (10, 10', 10''), and that the risk of a hazardous natural phenomenon is identified taking into account these location coordinates, and the risk of a hazardous natural phenomenon is formed in the form of a corrosion map displaying corrosion data, at least zones (20, 20', 20'') of application. 10. The method of analysis and/or forecasting according to claim 9, characterized in that the corrosion map is transferred to a building information modeling (BIM) system, primarily designed as equipment (32) for protecting the zone (20, 20', 20'') applications. 11. The method of analysis and/or prediction according to claim 9 or 10, characterized in that, based on the identified corrosion map, primarily local optimization is carried out as equipment (32) to protect the zone (20, 20', 20'') applications. 12. Method of analysis and/or forecasting according to one of paragraphs. 9-11, characterized in that the corrosion map is filled with simulated corrosion data for the area adjacent to the application zone (20), while the corrosion data in the external network (12) free from sensor modules (10, 10', 10'') sensor areas, corrosion maps are identified at least on the basis of data from sensor modules (10, 10', 10'') in other areas (20', 20'') of application, especially in adjacent areas (20') of application and/ or in geographically and/or climatically similar zones (20'') of application. 13. Method of analysis and/or forecasting according to one of the preceding paragraphs, characterized in that additional information about the zone (20, 20', 20'') of application includes at least the degree of activity of wild animals and/or anthropogenic activity , for example, tourist activity, in close proximity to the zone (20, 20', 20'') of application. 14. A method of analysis and/or forecasting according to one of the preceding paragraphs, characterized in that additional information about the zone (20, 20', 20'') of application includes at least data on air quality in the immediate vicinity of the zone (20, 20', 20'') applications. 15. A method of analysis and/or forecasting according to one of the preceding paragraphs, characterized in that the identified risks of a dangerous natural phenomenon include forecasts of the risks of a dangerous natural phenomenon, which are created on the basis of past indicators of sensor data and, above all, on the basis of previously identified additional information about the zone (20, 20', 20'') of application. 16. Method of analysis and/or forecasting according to one of the previous paragraphs, characterized in that at least one sensor module (10, 10', 10'') of the external network (12) of sensors is correlated with the one designed as intercepting and/or providing stability device (222) for rocks, stones, avalanches, mudflows, landslides or the like with a zone (20, 20', 20'') of application, with at least one sensor module (10, 10', 10'') of an external network (12) sensors has a shock sensor (28) for detecting impacts on the intercepting and/or stability device (222), and based on data from the shock sensor (28) and/or based on data from the sensor (30) rope tension force of the sensor module (10, 10', 10''), together with a series of measurements of the tropospheric parameters of the sensor module (10, 10', 10''), and above all together with additional information about the area (20, 20', 20'' ) application, carry out an analysis, primarily pattern recognition, and, on the basis of this analysis, a forecast of the risk of a dangerous natural phenomenon, performed as an impact forecast, is identified. 17. The method of analysis and/or forecasting according to claim 1, characterized in that, based on the identified risks of hazardous natural phenomena of several zones (20, 20', 20'') of application, the organization of service personnel, the organization of service equipment and/or the organization of consumables are carried out materials. 18. A method of analysis and/or forecasting according to one of the previous paragraphs, characterized in that, depending on the result and/or the magnitude of the identified risk of a dangerous natural phenomenon, the deployment of a drone (34), primarily a service drone and/or a reconnaissance drone, is initiated. 19. Sensor remote monitoring device (36) comprising at least one sensor module (10) for an external network (12) of sensors, provided in particular for recording and providing sensor data when implementing a network-based analysis and/or forecasting method sensors according to one of the previous paragraphs, and having at least one external corrosion sensor (38), at least one environmental sensor (40) for detecting measurement data of tropospheric parameters and at least one communication unit (42) for data transmission sensors to an external unit (14) of analysis and/or forecasting, characterized in that the sensor module (10) has at least an essentially hermetically sealed housing (44) of the sensor module, made without cable inputs, without cable outputs, without push-button switches and without external antennas. 20. Sensor remote monitoring device (36) according to claim 19, characterized in that the sensor module (10) includes a wireless camera interface for connection with an external camera (46). 21. Sensor remote monitoring device (36) according to claim 19 or 20, characterized by the presence of an external activating and/or deactivating element (48) for activating and/or deactivating the sensor module (10) depending on the position of the external activating and/or deactivating element (48) relative to the housing (44) of the sensor module (10). 22. Device (36) sensor remote monitoring according to one of paragraphs. 19-21, characterized in that the communication unit (42) is provided for transmitting sensor data directly, primarily without detours through one or more sensor data collection points, to an external analysis and/or forecasting unit (14), wherein the external unit ( 14) analysis and/or forecasting is provided for receiving sensor data from several sensor modules (10, 10', 10'') distributed over different zones (20, 20', 20''). 23. The sensor remote monitoring device (36) according to claim 22, characterized in that the communication unit (42), in the event of the unavailability of the external analysis and/or forecasting unit (14), is provided for transmitting sensor data to, preferably an adjacent, other sensor module (10') of external network (12) of sensors. 24. Device (36) sensor remote monitoring according to one of paragraphs. 19-23, characterized in that the sensor module (10) includes at least one acceleration sensor (50). 25. Device (36) sensor remote monitoring according to one of paragraphs. 19-24, characterized in that the sensor module (10) includes at least one orientation sensor (52). 26. Device (36) sensor remote monitoring according to one of paragraphs. 19-25, characterized in that the sensor module (10) includes at least one rope tension force sensor (30). 27. Sensor remote monitoring device (36) according to claim 26, characterized in that the sensor (30) for measuring the rope tension force includes at least one strain gauge (54), which is located, preferably, separately from the rope (56, 56', 56''), the force in the rope is controlled by the rope tension force sensor (30). 28. Sensor remote monitoring device (36) according to claim 26 or 27, characterized in that the rope tension force sensor (30) is at least partially made integral with the connecting device (224) of the sensor module (10), wherein a connecting device (224) is provided for directly attaching the sensor module (10) to the structure (24), preferably to the rope (56, 56', 56'') of the structure (24). 29. Device (36) sensor remote monitoring according to one of paragraphs. 19-28, characterized in that the external corrosion sensor (38) is based on measuring the electrical corrosion current resulting from corrosion, wherein the external corrosion sensor (38) includes at least one charge storage (58), which is charged by means of the electrical corrosion current to the maximum charge, after which the charge store (58) is discharged again, and wherein the sensor module (10) has an ammeter (60), which is provided for measuring the discharge current of the charge store (58) to detect external corrosion measurement data. 30. Device (36) sensor remote monitoring according to one of paragraphs. 19-29, characterized in that the external corrosion sensor (38) is based on measuring the electrical corrosion current resulting from corrosion, wherein the sensor module (10) includes at least one designed to power at least one component of the sensor module (10 ) the battery (62), and wherein the electrical corrosion current of the external corrosion sensor (38) serves as a charging current for electrically charging the battery (62). 31. Device (36) sensor remote monitoring according to one of paragraphs. 19-30, characterized in that the sensor module (10) includes a preliminary analysis unit (64), which is provided for performing at least one preliminary analysis of measurement data, especially raw measurement data, close to the sensor, at least one from sensors of the sensor module (10) and/or at least one external sensor connected to the sensor module (10), for example an external camera (46). 32. Sensor remote monitoring device (36) according to claim 31, characterized in that the preliminary analysis unit (64) provides an independent choice of which part of the sensor measurement data set is transmitted by the communication unit (42) and/or whether the sensor measurement data set is transmitted communication block (42) or not. 33. Sensor remote monitoring device (36) according to claim 31 or 32, characterized in that the preliminary analysis unit (64) is provided for establishing the interval between transmissions of the communication unit (42) based on measurement data of at least one sensor of the sensor module (10 ) and/or at least one external sensor connected to the sensor module (10). 34. Device (36) sensor remote monitoring according to one of paragraphs. 31-33, characterized in that the preliminary analysis unit (64) is provided for establishing, on the basis of measurement data, at least one sensor of the sensor module (10) and/or at least one external sensor for controlling the waiting phases connected to the sensor module (10) and/or measurement intervals of at least this sensor and/or at least one other sensor. 35. Device (36) sensor remote monitoring according to one of paragraphs. 19-34, characterized in that the sensor module (10) includes a computing unit (66) with a specially designed operating system that is not based on existing operating systems. 36. Device (36) sensor remote monitoring according to one of paragraphs. 19-35, characterized in that the sensor module (10) includes an energy harvesting unit (68) provided for generating current from a temperature difference, primarily inside the sensor module housing (44). 37. Device (36) sensor remote monitoring according to one of paragraphs. 19-36, characterized by the presence of at least one other sensor module (10'), which is associated with the same application area (20) as the sensor module (10). 38. Device (36) sensor remote monitoring according to one of paragraphs. 19-37, characterized in that the sensor module (10) for configuring the sensor module (10) includes a configuration module (70) provided for wireless communication with an external installer configuration device (72), for example a smartphone. 39. Sensor remote monitoring device (36) according to claim 38, characterized in that the sensor module (10) includes a setting element (74), for example a QR code, barcode and/or NFC interface, which is readable or used to issue a control action via an external configuration device (72) to initiate configuration of the sensor module (10). 40. An external network (12) of sensors, having several sensor remote monitoring devices (36) covering different zones (20, 20', 20'') of use according to one of paragraphs. 19-39, each of which includes sensor modules (10, 10', 10'') assigned to different application zones (20, 20', 20''), and each of which wirelessly, especially directly, carries out communication with a common external unit (14) of analysis and/or forecasting. 41. A structure (24) having at least one rope (56, 56', 56'') and at least one sensor module (10, 10', 10'') of the sensor remote monitoring device (36) according to one of pp. 19-39, with the sensor module (10, 10', 10'') attached to the rope (56, 56', 56''). 42. The structure (24) according to clause 41, made in the form of equipment (32) for protection from hazardous natural phenomena, such as a rockfall barrier (76), avalanche protection (78), rockfall curtain (80), slope strengthening (82) , mudflow barrier (84) and/or screen (86).