CN114968623A - Real-time equipment operation situation sensing system based on GIS map and object model - Google Patents

Real-time equipment operation situation sensing system based on GIS map and object model Download PDF

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CN114968623A
CN114968623A CN202210609060.8A CN202210609060A CN114968623A CN 114968623 A CN114968623 A CN 114968623A CN 202210609060 A CN202210609060 A CN 202210609060A CN 114968623 A CN114968623 A CN 114968623A
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equipment
operation situation
module
alarm
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周斌
胡章元
朱晨鸣
张永民
王龙
陈汝鹏
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China Information Consulting and Designing Institute Co Ltd
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China Information Consulting and Designing Institute Co Ltd
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Abstract

The invention discloses a GIS map and object model based equipment operation situation real-time sensing system which comprises a task scheduling platform, a websocket server and a websocket client, wherein the task scheduling platform is used for acquiring multi-source heterogeneous equipment data, cleaning the data, generating equipment operation situation data and sending the equipment operation situation data to the websocket server; the websocket server is used for receiving the equipment operation situation data and pushing the equipment operation situation data to the websocket client; and the websocket client is used for receiving the equipment operation situation data and dynamically plotting the equipment operation situation on the GIS map in real time. The system can sense the operation situation of the whole network equipment in real time, intuitively, comprehensively and accurately, and comprehensively promotes the intelligent, intelligent and refined management level.

Description

Real-time equipment operation situation sensing system based on GIS map and physical model
Technical Field
The invention belongs to the technical field of emerging information, and particularly relates to a GIS (geographic information system) map and object model based real-time equipment operation situation sensing system.
Background
With the rapid development of new ICT technologies such as the Internet of things, intelligent integration, big data, cloud computing and the like, the intelligentization and Internet of things application of all walks of life is becoming more extensive, and full interconnection, deep fusion and smart integration are imminent; meanwhile, the new infrastructure promotes the intelligentization and rapid transformation of infrastructure, such as the intelligentization and intelligentization upgrading of traditional facilities of smart cities, smart parks, smart scenic spots, smart agriculture, smart campuses, smart buildings and the like. Based on the isomerization network, isomerization equipment, isomerization application and isomerization data, the operation situation of one network management and one graph overview whole network equipment is more and more important.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to solve the technical problem of providing a real-time equipment operation situation sensing system based on a GIS map and an object model aiming at the defects of the prior art.
In order to solve the technical problems, the invention discloses a GIS map and object model based equipment operation situation real-time perception system, which comprises a task scheduling platform, a websocket server and a websocket client,
the task scheduling platform is used for acquiring multi-source heterogeneous equipment data, cleaning the data, generating equipment operation situation data and sending the equipment operation situation data to the websocket server;
the websocket server is used for receiving the equipment operation situation data and pushing the equipment operation situation data to the websocket client;
the websocket client is used for receiving the device operation situation data and dynamically plotting the device operation situation on a GIS (Geographic Information System) map in real time.
Further, the task scheduling platform comprises a data acquisition module, a cleaning module, a convergence storage module, a model conversion module, a first message queue module and a second message queue module;
the data acquisition module is used for acquiring and analyzing multi-source heterogeneous equipment data and transmitting the analyzed equipment data to the cleaning module through the first message queue module;
the cleaning module is used for receiving various equipment data transmitted by the data acquisition module, cleaning dirty data, judging whether equipment alarm data are generated or not through a Drools (JBoss Rules, open source business rule engine) rule engine after cleaning is finished, and finally transmitting the cleaned equipment data and the generated equipment alarm data to the convergence storage module;
the convergence storage module is used for storing the cleaned equipment data and the generated equipment alarm data into an InfluxDB time sequence library; the InfluxDB is a database service integrating time sequence data efficient reading and writing, compression storage and real-time calculation, and has the characteristics of high-performance reading, high-performance writing, storage and the like;
the model conversion module is used for generating the device operation situation data and storing the device operation situation data into the second message queue module in a JSON (JavaScript Object Notation) Object format;
and the second message queue module is used for storing the operation situation data of the equipment in the JSON object format, and allowing the websocket server to subscribe and send the data to the websocket server.
Furthermore, the websocket server comprises a pushing module, and the websocket client comprises a receiving module and a dynamic plotting module;
the pushing module is used for receiving the device operation situation data in the JSON object format and pushing the device operation situation data in the JSON object format to the receiving module in real time through a websocket protocol;
the receiving module is used for storing the received device operation situation data in the JSON object format into a front-end cache in real time;
and the dynamic plotting module is used for dynamically plotting the equipment operation situation on the GIS map in real time according to the equipment operation situation data in the JSON object format.
Furthermore, the data acquisition module is directly connected with the internet of things gateway, equipment and an intelligent system based on Apache Camel multi-protocol adaptation integration capability, so that the acquisition and analysis of multi-source heterogeneous equipment data are realized, the equipment data are obtained, and the equipment data are reported to the cleaning module; the device data comprises device basic data, device state data, device operation perception data, device original alarm data and device cruising track data.
Further, the device basic data attributes include a device number, a device name, a device type, a type name, a current longitude, a current latitude, a legend type (static, dynamic), a dynamic legend shape (straight line, broken line, arc, triangle, rectangle, circle, character, etc.), a static legend number, and device address information;
the device state data attribute comprises the state of the device, and dictionary values of the device state data attribute comprise online, offline, alarm and fault;
the device operation perception data attribute depends on different types of devices, and the operation perception data attribute of the video device comprises a video stream playing URL (Uniform Resource Locator); the operation perception data attribute of the broadcast power amplifier equipment comprises volume and the task of current power amplifier playing; the operation perception data attributes of the lamp comprise a switch state, light intensity and energy consumption; operational awareness data attributes of the environmental devices include monitored temperature, humidity, and PM 25;
the original alarm data attribute of the equipment comprises alarm time, alarm type, alarm level and alarm content; reporting original alarm data of the equipment by an Internet of things platform, Internet of things equipment or an intelligent system;
the device cruise track data is an ordered set of longitude, latitude, direction, and speed for the in-flight device.
Furthermore, the cleaning module cleans the dirty data by discarding partial data, completing missing values and setting default values to clean the device data which do not meet the requirements, so as to ensure the completeness and effectiveness of the data. The unsatisfactory device data comprises incomplete, erroneous, or duplicate data; discarding partial data, namely directly deleting row records or column fields with missing values to reduce the influence of trend data records on the whole data, thereby improving the accuracy of the data; the completion missing value is the data which is lost by the completion, and a complete data record is formed; setting a default value is to set a default value for the equipment to prevent subsequent data analysis and calculation from being abnormal;
the judging whether to generate the device alarm data through the Drools rule engine includes:
acquiring abnormal data in equipment state data and equipment operation perception data; and inputting the abnormal data into a Drools rule engine, matching the Drools rule engine based on the input data and preset rule conditions, and determining whether to generate equipment alarm data according to a matching result by virtue of a Rete algorithm, wherein the equipment alarm data attributes comprise alarm time, alarm type, alarm level and alarm content.
Further, the model conversion module acquires the cleaned device data and device alarm data from the infiluxdb time sequence library, generates device operation situation data according to the object model tsl (sitting Specification language) definition standard, and stores the device operation situation data in the second message queue module in the JSON object format;
the object model TSL defines a standard, defines a device operation situation in a physical space from the dimensions of a device identity identification Schema, a connection state link, description information profile, basic information basicInfo, device attribute properties, device service services, device event events and device cruise track levelPath, and is described by adopting a JSON Schema. The device attributes (properties) are described, and the attribute types comprise seven data types of integer type, character type, floating point type, Boolean type, enumeration type, time type and structure body, and the value range, step length and the like of the attributes; the device event (events) description comprises an event identifier, an event time, an event name, an event type (such as temperature and humidity exceeding threshold alarm, perimeter intrusion alarm and the like), an event level (general, severe, urgent and very urgent), an event description and the like. In the prior art, the TSL schema only describes properties, events and services objects, and the application is expanded and added with travelPaths and basicInfo objects, so that an entity in motion, such as an unmanned vehicle in driving and the like, can be sensed in real time
Further, the second message queue module realizes real-time storage and pushing of equipment operation situation data in all JSON object formats and subscription and real-time consumption of the pushing module based on a high-throughput distributed publish-subscribe message system kafka; by creating a subscription object and a consumption group, real-time pushing of equipment operation situation data based on a material model TSL definition standard is realized; the push module consumes and analyzes the subscribed equipment operation situation data in real time through a message user (consumer), and pushes the subscribed equipment operation situation data to the receiving modules of all connected websocket clients in real time through a websocket protocol.
Furthermore, the receiving module is connected to the pushing module in a long connection mode, receives the device operation situation data in the JSON object format in real time through a websocket protocol, analyzes and converts the device operation situation data, and finally stores the device operation situation data in the JSON object format into a front-end cache; the front-end cache adopts a javaScript Array object for storing a plurality of values in a single variable, and adopts push () and pop () methods to store and fetch cache data, so that the data is ensured to be ordered and not lost.
Further, the dynamic plotting module acquires device running situation data in a JSON object format from a front-end cache by starting a javaScript working thread, dynamically draws a dynamic combination icon on Canvas through the javaScript, marks the icon on a GIS map according to longitude and latitude information of the device, and displays various device running situations in real time; the drawn icons comprise straight lines, broken lines, arc lines, rectangles, triangles, circles, characters, combined icons and inserted pictures; distinguish device states by line color of the icon, such as: green represents normal operation of the equipment, grey represents offline of the equipment, orange represents alarm of the equipment, and red represents fault of the equipment; meanwhile, index values of equipment monitoring, such as temperature and humidity, volume, light intensity and the like, are drawn on the upper right of the equipment icon by means of equipment operation sensing data; aiming at equipment in driving, such as an unmanned vehicle, a route track, the current position of an equipment icon, the driving direction (0-360 degrees), the speed and the like of the equipment are marked on a map, and the running situation of various kinds of equipment is sensed in a one-map mode in real time.
Has the advantages that:
according to the method and the device, the operation situation of various devices under the heterogeneous network can be sensed in real time, and based on an event-driven mode, the operation situation of the devices is plotted on a GIS map in real time, intuitively, comprehensively and accurately, so that the intelligent, intelligent and fine management level is comprehensively improved. By applying new ICT technologies such as Internet of things, intelligent integration, big data and cloud computing and by means of Apache Camel multiprotocol adaptation integration heterogeneous network equipment capacity, the operation situation of 'one-network management and one-graph overview' whole network equipment is constructed; the heterogeneous network equipment and the intelligent system are deeply fused, so that 'data full fusion, situation full visibility and event full management' are realized, the intelligent and fine management levels are comprehensively improved, continuous and excellent operation capacity is provided for managers, and cost reduction and efficiency improvement are realized.
Drawings
The foregoing and/or other advantages of the invention will become further apparent from the following detailed description of the invention when taken in conjunction with the accompanying drawings.
Fig. 1 is a schematic structural diagram of a system for sensing an operation situation of a device in real time based on a GIS map and an object model according to an embodiment of the present application.
Fig. 2 is a data flow diagram of a device operation situation real-time perception system based on a GIS map and an object model according to an embodiment of the present application.
Detailed Description
Embodiments of the present invention will be described below with reference to the accompanying drawings.
The real-time equipment operation situation sensing system based on the GIS map and the object model is suitable for application scenes such as intelligent integration, management, operation and maintenance, and management and control of heterogeneous, massive and complex network equipment can be more convenient, quicker, more intuitive and easier to maintain by using the system.
As shown in fig. 1, the system for sensing the equipment operation situation in real time based on the GIS map and the object model provided by the embodiment of the application comprises a task scheduling platform, a websocket server and a websocket client, wherein the task scheduling platform is used for acquiring multi-source heterogeneous equipment data, performing data cleaning, generating equipment operation situation data, and sending the equipment operation situation data to the websocket server;
the websocket server is used for receiving the equipment operation situation data and pushing the equipment operation situation data to the websocket client;
and the websocket client is used for receiving the equipment operation situation data and dynamically plotting the equipment operation situation on the GIS map in real time.
The task scheduling platform comprises a data acquisition module, a cleaning module, a convergence storage module, a model conversion module, a first message queue module and a second message queue module;
the data acquisition module is used for acquiring and analyzing multi-source heterogeneous equipment data and transmitting the analyzed equipment data to the cleaning module through the first message queue module;
the cleaning module is used for receiving various equipment data transmitted by the data acquisition module, cleaning dirty data, judging whether equipment alarm data are generated or not through a Drools rule engine after cleaning is finished, and finally transmitting the cleaned equipment data and the generated equipment alarm data to the convergence storage module;
the convergence storage module is used for storing the cleaned equipment data and the generated equipment alarm data into an InfluxDB time sequence library;
the model conversion module is used for generating equipment operation situation data and storing the equipment operation situation data into the second message queue module in a JSON object format;
and the second message queue module is used for storing the operation situation data of the equipment in the JSON object format, and allowing the websocket server to subscribe and send the data to the websocket server.
The websocket server comprises a pushing module, and the websocket client comprises a receiving module and a dynamic plotting module;
the pushing module is used for receiving the device operation situation data in the JSON object format and pushing the device operation situation data in the JSON object format to the receiving module in real time through a websocket protocol;
the receiving module is used for storing the received device operation situation data in the JSON object format into a front-end cache in real time;
and the dynamic plotting module is used for dynamically plotting the equipment operation situation on the GIS map in real time according to the equipment operation situation data in the JSON object format.
As shown in fig. 2, the system specifically includes the following operation steps:
step 1, a protocol adaptation end of a data acquisition module is directly connected with an Internet of things gateway, equipment and an intelligent system based on Apache Camel multi-protocol adaptation integration capability to realize acquisition, analysis and conversion of multi-source heterogeneous equipment data, and the equipment data is reported to a cleaning module through a first message queue module, wherein the main equipment data comprises equipment basic data, equipment state data, equipment operation perception data, equipment original alarm data and equipment cruise track data; in this embodiment, the first message queue module adopts a distributed publish-subscribe message system kafka.
In the step 1, the Apache cache is a rule-based routing and mediation engine, which provides the realization of a Java object (POJO) in an enterprise integration mode, configures routing and mediation rules through a set-up Java Domain Specific Language (DSL), provides hundreds of component libraries, and supports connection protocols such as HTTP, MQTT, CoAP, Modbus, WebSocket, and the like. Southbound communication via application protocols (MQTT/HTTP/WebSocket, etc.), internet of things protocols (LoRa/NB-IoT/Modbus, etc.), transport protocols (TCP/UDP, etc.), and custom protocols; the northbound provides open service capability based on protocol modes such as kafka, WebSocket, restfulAPI, customization and the like. And finally, data acquisition, analysis and conversion of the multi-source heterogeneous network equipment are realized, and the data are reported to the cleaning module according to a standardized data structure.
The device data in step 1 mainly includes five types: the device comprises device basic data, device state data, device operation perception data, device original alarm data and device cruise track data. The basic data of the equipment has the following main attributes: device number, device name, device type, type name, current longitude, current latitude, legend type (static, dynamic), dynamic legend shape (straight line, polyline, arc, triangle, rectangle, circle, character, etc.), static legend number, device address information. The main attributes of the equipment state data are as follows: the state, its dictionary value is: online, offline, alarm, fault, etc. The main attribute of the operation perception data of the equipment depends on different types of equipment, and the attributes of the equipment are different, such as a video stream playing URL of video equipment; broadcasting the volume of the power amplifier equipment, the task of current power amplifier playing and the like; the on-off state, light intensity, energy consumption and the like of the lamp; and ambient equipment monitored temperature, humidity, PM25, etc. The main attributes of the original alarm data of the equipment are as follows: alarm time, alarm type, alarm level, alarm content, etc. The device cruise track data is a set of one or more ordered longitudes, latitudes, directions (0-360 degrees), and speeds, such as a driving route of an unmanned vehicle.
The original alarm data of the equipment in the step 1 is mainly reported by the Internet of things platform, the Internet of things equipment or the intelligent system.
Step 2, the cleaning module is used for receiving various equipment data transmitted by the acquisition module, cleaning the data (dirty data) which do not meet the requirements through a filtering, completion or true value replacement method, judging whether equipment alarm data is generated or not through a Drools rule engine, and finally transmitting all the data (the cleaned equipment data and the generated equipment alarm data) to the convergence storage module;
in the step 2, the dirty data is cleaned by mainly adopting methods of discarding partial data, completing missing values, setting default values and the like, so that incomplete data, wrong data and repeated data are solved, and the completeness and effectiveness of the data are ensured. Discarding partial data, namely directly deleting row records or column fields with missing values to reduce the influence of trend data records on the whole data, thereby improving the accuracy of the data; the completion missing value is the data which is lost by the completion, and a complete data record is formed; the default value is set as a necessary attribute of the equipment, so that abnormal subsequent data analysis and calculation is prevented.
The device alarm data in the step 2 is mainly generated by abnormal data in the device state data and the device sensing data. The alarm information generated by the abnormal equipment state and the abnormal equipment data is mainly realized by an open source Drools rule engine. And matching based on the input data and preset rule conditions, and determining whether to generate equipment alarm data according to a matching result by a tools rule engine through a Rete algorithm. The device alarm data attributes include alarm time, alarm type, alarm level, and alarm content.
Step 3, the aggregation storage module receives the cleaned equipment data and the generated equipment alarm data in real time, and stores the data into an InfluxDB time sequence library in a classified manner, wherein the InfluxDB is a database service integrating efficient reading and writing, compression storage and real-time calculation of time sequence data, and has the characteristics of high-performance reading, high-performance writing, storage and the like;
step 4, the model conversion module acquires basic data, state data, operation perception data, cruise track data and alarm data of the equipment from the InfluxDB time sequence library, generates equipment operation situation data according to the object model TSL definition standard, and stores the equipment operation situation data in a message queue in a JSON object format;
in the step 4, the object model tsl (sitting Specification language) defines a standard, and defines a device operation situation in a physical space from the dimensions of a device identity (Schema), a connection state (link), description information (profile), basic information (basicInfo), device attributes (properties), device services (services), device events (events), and a device cruise track (cruise tracks), and is described by using a JSON Schema. The device attributes (properties) are described, and the attribute types comprise seven data types including an integer type, a character type, a floating point type, a Boolean type, an enumeration type, a time type and a structure body, and the value range, the step length and the like of the attributes; the device event (events) description comprises an event identifier, an event time, an event name, an event type (such as temperature and humidity exceeding threshold alarm, perimeter intrusion alarm and the like), an event level (general, severe, urgent and very urgent), an event description and the like.
An example of the object model TSL definition schema description is shown below.
Figure BDA0003671384170000081
Figure BDA0003671384170000091
Figure BDA0003671384170000101
Figure BDA0003671384170000111
Figure BDA0003671384170000121
Step 5, the second message queue module is based on a high-throughput distributed publishing and subscribing message system kafka, and realizes the JSON data storage and pushing of all equipment real-time operation situation and the line subscription and real-time consumption of a message user (consumer);
in the step 5, a message user (consumer) subscribes and consumes the real-time data. By creating a subscription object and a consumption group, real-time pushing of equipment operation situation data based on a material model TSL grammar rule is realized, and a message user (consumer) consumes subscribed message queue data in real time.
Step 6, the data pushing module is a receiving module which consumes and analyzes the subscribed message queue data in real time through a message user (consumer) and finally pushes the subscribed message queue data to all connected websocket clients in real time through a websocket protocol;
step 7, the receiving module receives JSON data of the equipment operation situation in real time through a websocket protocol by the websocket client, analyzes and converts the JSON data, and finally stores the JSON data into a front-end cache;
in the step 7, the websocket client is connected to the websocket server in a long connection mode and performs real-time two-way communication, the websocket client mainly comprises a receiving module and a dynamic plotting module, and the representation form of the client is as follows: the device comprises a PC end, a mobile phone end, a large screen end and a pad end, so that the running situation of the device can be monitored in real time at the same time by multiple ends.
In the step 7, the front-end cache adopts a javaScript Array object for storing a plurality of values in a single variable, and the cache data is stored and fetched by adopting push () and pop () methods, so that the data is ordered and is not lost.
And 8, the dynamic plotting module acquires JSON data of the equipment running situation from the front-end cache by starting a javaScript working thread, and plots the running situation of each equipment on the GIS map in real time.
In the step 8, the dynamic plotting module obtains JSON data of the equipment operation situation from a front-end cache by starting a javaScript working thread, dynamically draws various complex dynamic combination icons on Canvas by the javaScript, marks the complex dynamic combination icons on a GIS map by latitude and longitude information of the equipment, and displays the various equipment operation situations in real time. The drawn icons mainly include: straight lines, broken lines, arcs, rectangles, triangles, circles, characters, composite icons, and inset pictures, etc.; distinguish device states by line color of the icon, such as: green represents that the equipment runs normally, grey represents that the equipment is off-line, orange represents that the equipment gives an alarm, and red represents that the equipment fails; meanwhile, by means of sensing data of the equipment, index values of equipment monitoring, such as temperature and humidity, volume and light intensity, are drawn on the upper right of the equipment icon; aiming at equipment in driving, such as an unmanned vehicle, a route track, the current position of an equipment icon, the driving direction (0-360 degrees), the speed and the like of the equipment are marked on a map, and the running situation of various kinds of equipment is sensed in a one-map mode in real time.
In a specific implementation, the present application provides a computer storage medium and a corresponding data processing unit, where the computer storage medium is capable of storing a computer program, and the computer program, when executed by the data processing unit, may execute the inventive content of the device operation situation real-time awareness system based on the GIS map and the object model provided by the present invention and some or all of the steps in each embodiment. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a Random Access Memory (RAM), or the like.
It is clear to those skilled in the art that the technical solutions in the embodiments of the present invention can be implemented by means of a computer program and its corresponding general-purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be essentially or partially implemented in the form of a computer program or a software product, which may be stored in a storage medium and includes several instructions to enable a device (which may be a personal computer, a server, a single chip computer, MUU, or a network device) including a data processing unit to execute the method in the embodiments or some parts of the embodiments of the present invention.
The invention provides a real-time perception system of equipment operation situation based on a GIS map and an object model, and a plurality of methods and ways for realizing the technical scheme are provided. All the components not specified in the present embodiment can be realized by the prior art.

Claims (10)

1. A GIS map and object model based real-time perception system for equipment operation situation is characterized by comprising a task scheduling platform, a websocket server and a websocket client,
the task scheduling platform is used for acquiring multi-source heterogeneous equipment data, cleaning the data, generating equipment operation situation data and sending the equipment operation situation data to the websocket server;
the websocket server is used for receiving the equipment operation situation data and pushing the equipment operation situation data to the websocket client;
and the websocket client is used for receiving the equipment operation situation data and dynamically plotting the equipment operation situation on the GIS map in real time.
2. The GIS map and object model-based equipment operation situation real-time perception system according to claim 1 is characterized in that the task scheduling platform comprises a data acquisition module, a cleaning module, a convergence storage module, a model conversion module, a first message queue module and a second message queue module;
the data acquisition module is used for acquiring and analyzing multi-source heterogeneous equipment data and transmitting the analyzed equipment data to the cleaning module through the first message queue module;
the cleaning module is used for receiving various equipment data transmitted by the data acquisition module, cleaning dirty data, judging whether equipment alarm data are generated or not through a Drools rule engine after cleaning is finished, and finally transmitting the cleaned equipment data and the generated equipment alarm data to the convergence storage module;
the convergence storage module is used for storing the cleaned equipment data and the generated equipment alarm data into an InfluxDB time sequence library;
the model conversion module is used for generating equipment operation situation data and storing the equipment operation situation data into the second message queue module in a JSON object format;
and the second message queue module is used for storing the operation situation data of the equipment in the JSON object format, and allowing the websocket server to subscribe and send the data to the websocket server.
3. The GIS map and object model-based equipment operation situation real-time perception system according to claim 2 is characterized in that the websocket server comprises a push module, and the websocket client comprises a receiving module and a dynamic plotting module;
the pushing module is used for receiving the device operation situation data in the JSON object format and pushing the device operation situation data in the JSON object format to the receiving module in real time through a websocket protocol;
the receiving module is used for storing the received device operation situation data in the JSON object format into a front-end cache in real time;
and the dynamic plotting module is used for dynamically plotting the equipment operation situation on the GIS map in real time according to the equipment operation situation data in the JSON object format.
4. The GIS map and object model based equipment operation situation real-time perception system according to claim 3 is characterized in that the data acquisition module is based on Apache Camel multiprotocol adaptation integration capability, directly connects the Internet of things gateway, the equipment and the intelligent system, realizes acquisition and analysis of multi-source heterogeneous equipment data, obtains the equipment data, and reports the equipment data to the cleaning module; the device data comprises device basic data, device state data, device operation perception data, device original alarm data and device cruising track data.
5. The GIS map and object model-based real-time equipment operation situation awareness system according to claim 4, wherein the equipment basic data attributes comprise equipment number, equipment name, equipment type, type name, current longitude and latitude, legend type, dynamic legend shape, static legend number and equipment address information;
the device state data attribute comprises the state of the device, and dictionary values of the device state data attribute comprise online, offline, alarm and fault;
the device operation perception data attribute depends on different types of devices, and the operation perception data attribute of the video device comprises a video stream playing URL; the operation perception data attribute of the broadcast power amplifier equipment comprises volume and the task of current power amplifier playing; the operation perception data attributes of the lamp comprise a switch state, light intensity and energy consumption; operational awareness data attributes of the environmental devices include monitored temperature, humidity, and PM 25;
the original alarm data attribute of the equipment comprises alarm time, alarm type, alarm level and alarm content; reporting original alarm data of the equipment by an Internet of things platform, Internet of things equipment or an intelligent system;
the device cruise track data is an ordered set of longitude, latitude, direction, and speed for a device in motion.
6. The GIS map and object model-based real-time perception system for device operation situation according to claim 5, wherein the cleaning module performs dirty data cleaning including cleaning of unsatisfactory device data including incomplete, erroneous or repetitive data by discarding partial data, completing missing values and setting default values; discarding partial data, namely directly deleting row records or column fields with missing values; the completion missing value is the data which is lost by the completion, and a complete data record is formed; setting a default value is to set a default value for the equipment; the judging whether to generate the device alarm data through the Drools rule engine includes:
acquiring abnormal data in equipment state data and equipment operation perception data; and inputting the abnormal data into a Drools rule engine, matching the Drools rule engine based on the input data and preset rule conditions, and determining whether to generate equipment alarm data according to a matching result by virtue of a Rete algorithm, wherein the equipment alarm data attributes comprise alarm time, alarm type, alarm level and alarm content.
7. The GIS map and object model-based real-time device operation situation awareness system according to claim 6, wherein the model conversion module obtains cleaned device data and device alarm data from an InfluxDB time sequence library, generates device operation situation data according to object model TSL definition standards, and stores the device operation situation data in a JSON object format in the second message queue module;
the object model TSL defines a standard, defines a device operation situation in a physical space from the dimensions of a device identity identification Schema, a connection state link, description information profile, basic information basicInfo, device attribute properties, device service services, device event events and device cruise track levelPath, and is described by adopting a JSON Schema.
8. The GIS map and object model-based device operation situation real-time sensing system according to claim 7, wherein the second message queue module realizes real-time storage and push of all JSON object format device operation situation data and subscription and real-time consumption of message users of the push module based on a high-throughput distributed publish-subscribe message system kafka; by creating a subscription object and a consumption group, real-time pushing of equipment operation situation data based on a material model TSL definition standard is realized; the push module consumes and analyzes the subscribed equipment operation situation data in real time through a message user, and pushes the subscribed equipment operation situation data to the receiving modules of all connected websocket clients in real time through a websocket protocol.
9. The GIS map and object model-based device operation situation real-time sensing system according to claim 8, wherein the receiving module is connected to the pushing module in a long connection manner, receives device operation situation data in a JSON object format in real time through a websocket protocol, analyzes and converts the device operation situation data, and finally stores the device operation situation data in the JSON object format in a front-end cache; the front-end cache adopts a javaScript Array object which is used for storing values in a single variable and adopts push () and pop () methods to store and fetch cache data.
10. The GIS map and object model-based real-time equipment operation situation awareness system according to claim 9, wherein the dynamic plotting module obtains JSON object format equipment operation situation data from a front-end cache by starting a javaScript worker thread, dynamically draws a dynamic combination icon on a Canvas by the javaScript, and labels the icon on the GIS map according to longitude and latitude information of the equipment; distinguishing the equipment states through the line color of the icons; meanwhile, drawing an index value monitored by the equipment on the upper right of the equipment icon by means of the operation perception data of the equipment; and marking a route track, the current position of an equipment icon, the running direction and the running speed of the equipment on the map aiming at the equipment in running, and sensing the running situation of various equipment in real time in a graph mode.
CN202210609060.8A 2022-05-31 2022-05-31 Real-time equipment operation situation sensing system based on GIS map and object model Pending CN114968623A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115237415A (en) * 2022-09-22 2022-10-25 南京雷电信息技术有限公司 Method for realizing situation duplication under GIS platform

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115237415A (en) * 2022-09-22 2022-10-25 南京雷电信息技术有限公司 Method for realizing situation duplication under GIS platform
CN115237415B (en) * 2022-09-22 2022-12-16 南京雷电信息技术有限公司 Method for realizing situation duplication under GIS platform

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