CN115551060B - Low-power-consumption data monitoring method - Google Patents
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- CN115551060B CN115551060B CN202211283949.8A CN202211283949A CN115551060B CN 115551060 B CN115551060 B CN 115551060B CN 202211283949 A CN202211283949 A CN 202211283949A CN 115551060 B CN115551060 B CN 115551060B
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 94
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000001514 detection method Methods 0.000 claims abstract description 70
- 238000010586 diagram Methods 0.000 claims description 17
- 230000002035 prolonged effect Effects 0.000 abstract description 3
- 230000008901 benefit Effects 0.000 description 3
- 238000005265 energy consumption Methods 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
- H04W52/0225—Power saving arrangements in terminal devices using monitoring of external events, e.g. the presence of a signal
- H04W52/0248—Power saving arrangements in terminal devices using monitoring of external events, e.g. the presence of a signal dependent on the time of the day, e.g. according to expected transmission activity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The application discloses a low-power-consumption data monitoring method, which comprises the following steps: dividing a building project to be monitored into a plurality of monitoring areas; a plurality of wireless sensors are arranged in each monitoring area; the background server generates a corresponding data acquisition strategy for each monitoring area and sends the data acquisition strategy to each wireless sensor in the corresponding monitoring area; each wireless sensor executes the received corresponding data monitoring strategy, and one of the plurality of wireless sensors in each monitoring area performs data acquisition and sends the acquired detection data to a background server at each data uploading time node; and the background server executes alarm operation when one of the received detection data is greater than or equal to an alarm value. According to the low-power-consumption data monitoring method, one wireless sensor is arranged in the same monitoring area to work in one data uploading time node, so that the service time of the wireless sensor can be greatly prolonged.
Description
Technical Field
The application belongs to the technical field of building data monitoring, and particularly relates to a low-power-consumption data monitoring method.
Background
Along with the continuous progress of science and technology, the digital degree of society is continuously improved, and risk monitoring of building projects is gradually converted into automatic monitoring through some automatic detection equipment and cloud platforms, and mainly related data acquisition is carried out on a building through sensors such as vibration sensors, inclination sensors or pressure sensors at different positions of the building projects, and then the data are uploaded to the cloud platform, and automatic processing analysis is carried out on the data through the cloud platform to identify whether the building has risks. This has greatly saved the human cost, and is more timely effective to the discernment of risk.
In the existing detection method, the adopted detection equipment is generally wireless equipment. The advantage of selecting a wireless detection device is that no network data lines need to be routed for the detection device. But this requires the detection device to be powered from a power supply, resulting in a significant limitation of the lifetime of the detection device.
Disclosure of Invention
The application provides a low-power-consumption data monitoring method for solving the technical problems, which adopts the following technical scheme:
a low-power consumption data monitoring method comprises the following steps:
dividing a building item to be monitored into a plurality of monitoring areas which are not overlapped with each other;
a plurality of wireless sensors are arranged in each monitoring area to collect detection data;
the background server generates a corresponding data acquisition strategy for each monitoring area and sends the generated data acquisition strategies to each wireless sensor in the corresponding monitoring area respectively, wherein the data acquisition strategies define the sequence of acquiring uploading data by the plurality of wireless sensors in each monitoring area;
each wireless sensor executes the received corresponding data monitoring strategy, and one of the plurality of wireless sensors in each monitoring area performs data acquisition and sends the acquired detection data to a background server at each data uploading time node;
and the background server executes alarm operation when one of the received detection data is greater than or equal to an alarm value.
Further, the low-power consumption data monitoring method further comprises the following steps:
when one of the received detection data is larger than or equal to the early warning value and smaller than the alarm value, the background server sends a continuous acquisition instruction to a wireless sensor with the acquired detection data larger than or equal to the early warning value and smaller than the alarm value;
the wireless sensor which receives the continuous acquisition instruction continuously performs data acquisition uploading operation on the next first number of data uploading time nodes;
if at least one of the first quantity of detection data uploaded by the wireless sensor which subsequently receives the continuous acquisition instruction is larger than or equal to the early warning value and smaller than the warning value, the background server executes early warning operation.
Further, the low-power consumption data monitoring method further comprises the following steps:
generating a correlation diagram for a plurality of wireless sensors in each monitoring area through a background server, wherein each wireless sensor is used as a connecting node in the correlation diagram, and each connecting node is connected with at least one other connecting node;
when one of the received detection data is larger than or equal to the early warning value and smaller than the alarm value, taking the wireless sensor with the acquired detection data larger than or equal to the early warning value and smaller than the alarm value as a main sensor, taking the wireless sensor directly connected with the main sensor in the association diagram as an association sensor, and sending a supplementary acquisition instruction to the main sensor and a plurality of association sensors by a background server;
the main sensor and the associated sensor which receive the continuous acquisition instruction perform data acquisition uploading operation on a next data uploading time node;
if the detection data uploaded by the main sensor is still greater than or equal to the early warning value and smaller than the alarm value, and meanwhile, the detection data uploaded by at least one of the plurality of related sensors is greater than or equal to the early warning value and smaller than the alarm value, and the background server executes early warning operation.
Further, the specific method for the background server to execute the early warning operation is as follows:
determining a first weight value according to the number of associated sensors corresponding to the main sensor;
determining a second weight value according to the number of the related sensors with the uploaded detection data being larger than or equal to the early warning value and smaller than the warning value;
determining an early warning level according to the first weight value and the second weight value;
and executing corresponding early warning operation according to the early warning level.
Further, the specific method for the background server to execute the alarm operation when one of the received plurality of detection data is greater than or equal to the alarm value is as follows:
sending alarm information to mobile equipment of a first risk manager;
the specific method for executing the corresponding early warning operation according to the early warning level comprises the following steps:
when the early warning level reaches a preset level, sending alarm information to mobile equipment of a first risk manager;
and when the early warning level does not reach the preset level, sending early warning information to the mobile equipment of the second risk manager.
Further, the specific method for generating the association graph for the plurality of wireless sensors in each monitoring area through the background server is as follows:
acquiring the distance between each wireless sensor in the monitoring area;
setting a distance threshold;
and using each wireless sensor as a connecting node, and connecting the connecting nodes represented by the wireless sensors with the distances smaller than or equal to the distance threshold value with each other through connecting wires to form a correlation diagram.
Further, the specific method for acquiring the distance between each wireless sensor in the monitoring area is as follows:
establishing a 3D model according to the building project to be monitored;
corresponding marks are carried out in the 3D model according to the actual positions of the wireless sensors in the building project;
and obtaining the distance values of the two wireless sensors in the 3D model and the scaling of the 3D model to calculate the distance between the two wireless sensors.
Further, the range of the ratio of the early warning value to the alarm value is more than or equal to 0.9 and less than 1.
Further, the low-power consumption data monitoring method further comprises the following steps:
the background server also acquires temperature information of the area where the building project to be monitored is located, and corrects the received detection data according to the temperature information.
Further, the wireless sensor enters a low power sleep mode during non-operation.
The low-power-consumption data monitoring method provided by the application has the advantages that the building projects to be monitored are subjected to partition management, the plurality of wireless sensors in the same monitoring area are subjected to data acquisition and uploading work in turn, one wireless sensor is arranged in the same monitoring area to work in one data uploading time node, the energy consumption of the rest wireless sensors is greatly saved, and the using time of the wireless sensors is prolonged.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic diagram of a low power data monitoring method of the present application;
fig. 2 is a schematic diagram of a correlation diagram.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The application discloses a low-power-consumption data monitoring method which is used for monitoring building projects in real time. It is understood that the monitoring of data for a building includes, but is not limited to, detecting vibration data by vibration sensors, detecting tilt data by tilt sensors, detecting force data by pressure sensors, and the like. At least one of the sensors may be selected for data detection according to the specific needs of the building project.
As shown in fig. 1, the low power consumption data monitoring method includes the following steps: s1: the building item to be monitored is divided into a plurality of monitoring areas which do not overlap each other. S2: a plurality of wireless sensors are provided in each monitoring area to collect detection data. S3: the background server generates a corresponding data acquisition strategy for each monitoring area and sends the generated data acquisition strategies to each wireless sensor in the corresponding monitoring area respectively, and the data acquisition strategies define the sequence of acquiring uploading data by the plurality of wireless sensors in each monitoring area. S4: each wireless sensor executes the received corresponding data monitoring strategy, and at each data uploading time node, one of the plurality of wireless sensors in each monitoring area performs data acquisition and sends the acquired detection data to a background server. S5: and the background server executes alarm operation when one of the received detection data is greater than or equal to an alarm value. Through the steps, the low-power-consumption data monitoring method disclosed by the application is used for carrying out partition management on the building project to be monitored. The wireless sensors in the same monitoring area alternately perform data acquisition and uploading, and in one data uploading time node, only one wireless sensor in the same monitoring area works, so that the energy consumption of the rest wireless sensors can be greatly saved, and the using time of the wireless sensors is prolonged. The above steps are specifically described below.
For step S1: the building item to be monitored is divided into a plurality of monitoring areas which do not overlap each other.
The division of the monitoring area may be selected based on the specific structure of the building project. The plurality of monitoring areas cover key monitoring areas of the building project to be monitored.
For step S2: a plurality of wireless sensors are provided in each monitoring area to collect detection data.
The wireless sensors are spaced apart from each other by a distance and cover each monitoring area as uniformly as possible.
For step S3: the background server generates a corresponding data acquisition strategy for each monitoring area and sends the generated data acquisition strategies to each wireless sensor in the corresponding monitoring area respectively, and the data acquisition strategies define the sequence of acquiring uploading data by the plurality of wireless sensors in each monitoring area.
For step S4: each wireless sensor executes the received corresponding data monitoring strategy, and at each data uploading time node, one of the plurality of wireless sensors in each monitoring area performs data acquisition and sends the acquired detection data to a background server.
After the wireless sensor is deployed, the acquired detection data is sent to a background server. In the present application, in order to reduce the loss of the wireless sensor, the entire construction project is divided into a plurality of monitoring areas. At a data upload time node, one wireless sensor is selected from each monitoring area to perform data detection upload, and the remaining wireless sensors are not operated. The status of its corresponding monitoring area is approximated by the status of one wireless sensor. Meanwhile, for a monitoring area, the wireless sensors selected each time are different, so that when the wireless sensor of the monitoring area works for one round, each sensor works only once, but detection data obtained by a background server basically reflects the situation of all positions of the monitoring area.
As a preferred embodiment, to further improve the energy saving effect, the wireless sensor enters a low power sleep mode during non-operation.
For step S5: and the background server executes alarm operation when one of the received detection data is greater than or equal to an alarm value.
Preferably, the specific method for executing the alarm operation by the background server when one of the received plurality of detection data is greater than or equal to the alarm value is as follows: and sending alarm information to the mobile equipment of the first risk management personnel.
It can be understood that, in order to determine whether the alarm information is processed in time, after the alarm information is sent to the mobile device of the first risk manager, the positioning information sent by the mobile device of the first risk manager is periodically received within a preset time, and the positioning information is compared with the position of the building project, so as to determine whether the first risk manager reaches the location of the building project within the preset time. The first risk manager arrives at the building to check the problem and upload the processing report.
As a preferred embodiment, the low power consumption data monitoring method of the present application further comprises:
when one of the received detection data is greater than or equal to the early warning value and smaller than the alarm value, the background server sends a continuous acquisition instruction to a wireless sensor with the acquired detection data greater than or equal to the early warning value and smaller than the alarm value.
And the wireless sensor receiving the continuous acquisition instruction continuously performs data acquisition uploading operation on the next first number of data uploading time nodes.
If at least one of the first quantity of detection data uploaded by the wireless sensor which subsequently receives the continuous acquisition instruction is larger than or equal to the early warning value and smaller than the warning value, the background server executes early warning operation.
It will be appreciated that setting the alarm value too large may result in a potential risk not being effectively identified. The alarm value is set too small, so that the defending is too proper, and the events which are not required to be concerned originally are concerned excessively, so that the waste of human resources is caused.
In the application, an early warning value is set under the condition that an alarm value is set. Generally, the range of the ratio of the early warning value to the alarm value is more than or equal to 0.9 and less than 1. In the application, the ratio of the early warning value to the alarm value is 0.95. When the detection data of a certain wireless sensor is between the early warning value and the alarm value, other wireless sensors in the monitoring area execute the original data monitoring strategy. The background server further collects the detection data of the wireless sensor continuously. And in the collection data of the preset quantity (first quantity), if one detection data is larger than or equal to the early warning value and smaller than the warning value, judging that the risk exists, and carrying out early warning operation.
As another preferred embodiment, the low power consumption data monitoring method may further include:
an association graph is generated for a plurality of wireless sensors within each monitored area by a background server. As shown in fig. 2, in the association diagram, each wireless sensor serves as a connection node, and each connection node is connected to at least one other connection node.
When one of the received detection data is larger than or equal to the early warning value and smaller than the alarm value, the wireless sensor with the acquired detection data larger than or equal to the early warning value and smaller than the alarm value is used as a main sensor, the wireless sensor directly connected with the main sensor in the association diagram is used as an association sensor, and the background server sends a supplementary acquisition instruction to the main sensor and a plurality of association sensors.
And the main sensor and the associated sensor which receive the continuous acquisition instruction perform data acquisition uploading operation at a next data uploading time node.
If the detection data uploaded by the main sensor is still greater than or equal to the early warning value and smaller than the alarm value, and meanwhile, the detection data uploaded by at least one of the plurality of related sensors is greater than or equal to the early warning value and smaller than the alarm value, and the background server executes early warning operation.
It will be appreciated that in this embodiment, a number of associated wireless sensors are provided for each wireless sensor. The determination of risk situations is aided by these associated sensors.
When the detection data of a certain wireless sensor is between the early warning value and the alarm value, other wireless sensors in the monitoring area execute the original data monitoring strategy. The background server also performs one data acquisition on the main sensor and all corresponding associated sensors in the subsequent data acquisition. In this data acquisition, if the main sensor is still between the early warning value and the alarm value and at least one of the associated sensors is also between the early warning value and the alarm value, the risk is judged to exist, and early warning operation is performed.
As a preferred implementation manner, the specific method for the background server to execute the early warning operation is as follows:
and determining a first weight value according to the number of the associated sensors corresponding to the main sensor. It will be appreciated that the more associated sensors of a wireless sensor, the more important it can be to indicate where it is. In order to embody such a difference, the present application determines a first weight value according to the number of associated sensors corresponding to the main sensor.
And determining a second weight value according to the number of the associated sensors with the uploaded detection data being larger than or equal to the early warning value and smaller than the warning value.
And determining the early warning level according to the first weight value and the second weight value. In the application, the first weight value and the second weight value are selected to be multiplied, and then the early warning level is determined according to the multiplied result.
And executing corresponding early warning operation according to the early warning level. For example, let us now assume that a primary sensor corresponds to 10 associated sensors, and that the first weight value corresponds to 10. Among the 10 associated sensors, the number of sensors with detection data between the early warning value and the alarm value is 5, and the corresponding second weight value is 5. The final calculated value was 50. Further, the ranking may be performed according to the magnitude of the calculated value.
And when the early warning level reaches a preset level, sending alarm information to the mobile equipment of the first risk management personnel. And when the early warning level does not reach the preset level, sending early warning information to the mobile equipment of the second risk manager. It will be appreciated that the second risk manager is at a lower level than the first risk manager. In general, only the second risk manager needs to be warned. The first risk manager is only notified when the risk is relatively large.
Similarly, in order to determine whether the early warning information is processed in time, after the early warning information is sent to the mobile device of the second risk manager, the positioning information sent by the mobile device of the second risk manager is periodically received within a preset time, and the positioning information is compared with the position of the building project to determine whether the second risk manager reaches the location of the building project within the preset time. And the second risk manager reaches the building to check the problem and upload the processing report.
It will be appreciated that the association graph may be generated by manually setting the associated sensor for each wireless sensor and then connecting the associated sensors one to one.
However, in this way, manual setting is required one by one. When the association diagram needs to be modified, corresponding modification is also needed manually. In order to avoid this.
In the application, another more preferable mode is adopted, and the specific method for generating the association diagram for the plurality of wireless sensors in each monitoring area through the background server is as follows:
the distance between each wireless sensor in the monitoring area is obtained.
A distance threshold is set. The distance threshold may be set according to the actual situation.
And using each wireless sensor as a connecting node, and connecting the connecting nodes represented by the wireless sensors with the distances smaller than or equal to the distance threshold value with each other through connecting wires to form a correlation diagram.
It will be appreciated that the closer the sensors are to each other, the greater their relevance. In this way, the associated sensor corresponding to each sensor can be quickly identified by the distance between the sensors. The generation of the association graph only needs to set a proper distance threshold value by a manager. And the distance threshold can be adjusted at any time according to the needs. After the distance threshold value is adjusted, a new association diagram can be quickly and automatically generated.
As a preferred embodiment, the specific method for acquiring the distance between each wireless sensor in the monitoring area is as follows: and establishing a 3D model according to the building project to be monitored. Corresponding marks are made in the 3D model according to the actual positions of the wireless sensors in the building project. And obtaining the distance values of the two wireless sensors in the 3D model and the scaling of the 3D model to calculate the distance between the two wireless sensors.
In a more preferred embodiment, in the step of forming the association graph by connecting the connection nodes represented by the wireless sensors having a distance between each other equal to or smaller than the distance threshold value through the connection lines, the distance weight between the two wireless sensors is represented by the side length of the connection lines. I.e. the association diagram also contains distance weight information. The smaller the distance between the two sensors, the greater the distance weight.
When one of the received detection data is larger than or equal to the early warning value and smaller than the alarm value, the wireless sensor with the acquired detection data larger than or equal to the early warning value and smaller than the alarm value is used as a main sensor, the wireless sensor directly connected with the main sensor in the association diagram is used as an association sensor, and the background server sends a supplementary acquisition instruction to the main sensor and a plurality of association sensors. And the main sensor and the associated sensor which receive the continuous acquisition instruction perform data acquisition uploading operation at a next data uploading time node.
As an alternative way, if the detection data uploaded by the main sensor is still greater than or equal to the early warning value and smaller than the alarm value, a determination value is calculated according to the number of associated sensors with the detection data greater than or equal to the early warning value and smaller than the alarm value and the corresponding distance weight, and whether to perform early warning operation and the grade of the early warning operation are determined according to the size of the determination value.
For example, assume that a master sensor has 10 corresponding associated sensors. The number of the associated sensors with the detection data being greater than or equal to the early warning value is 6, and the distance threshold values between the 6 associated sensors and the main sensor are 0.7,0.7,0.8,0.9,0.8 and 0.6 respectively. The final calculated determination value is 0.7+0.7+0.8+0.9+0.8+0.6=4.5, and whether the early warning operation is performed or not and the level of the early warning operation are confirmed according to the determination value 4.5.
As another alternative, if the detection data uploaded by the main sensor is still greater than or equal to the early warning value and less than the alarm value, the relevant sensor with the detection data greater than or equal to the early warning value and less than the alarm value is selected, a determination value is calculated according to the detection data and the corresponding distance weight, whether to perform early warning operation or not is determined according to the magnitude of the determination value, and the level of the early warning operation is determined.
For example, assume that the data detected by the sensor is a pressure value. Assume that the master sensor has 10 corresponding associated sensors. The number of the associated sensors with detection data larger than or equal to the early warning value (the early warning value is 95N, and the alarm value is 100N) is 5, namely 96N,98N, 97N and 97N, and the distance threshold values between the 4 associated sensors and the main sensor are 0.7,0.8,0.9,0.8 and 0.6 respectively. The final calculated determination value is 96×0.7+98×0.8+98×0.9+97×0.8+97×0.6= 369.6, and it is confirmed whether the warning operation is performed or not and the level of the warning operation according to the determination value 369.6.
As a preferred embodiment, the low power consumption data monitoring method further includes:
the background server also acquires temperature information of the area where the building project to be monitored is located, and corrects the received detection data according to the temperature information.
It will be appreciated that the presence of such data, as detected by the sensors, within a reasonable range of values means that the current state of the building project is relatively normal. However, even if the building itself does not change, it is at a different temperature, the detection data detected by these sensors are different, which is caused by the material of the building itself being affected by environmental factors.
In order to avoid inaccurate judgment caused by temperature difference, the data collected by the background also comprises temperature information of an area where a building project is located, and all detection data uploaded by the wireless sensors are corrected through temperature values.
In the application, the alarm value and the early warning value are set for the temperature of 20 ℃. If the current ambient temperature is higher than 20 ℃, for example, 30 ℃, the detection data is reduced according to the difference between 30 ℃ and 20 ℃. If the current ambient temperature is less than 20 ℃, for example, 10 ℃, amplifying the detection data according to the difference between 10 ℃ and 20 ℃.
The foregoing has shown and described the basic principles, principal features and advantages of the application. It will be appreciated by persons skilled in the art that the above embodiments are not intended to limit the application in any way, and that all technical solutions obtained by means of equivalent substitutions or equivalent transformations fall within the scope of the application.
Claims (6)
1. The low-power-consumption data monitoring method is characterized by comprising the following steps of:
dividing a building item to be monitored into a plurality of monitoring areas which are not overlapped with each other;
a plurality of wireless sensors are arranged in each monitoring area to collect detection data;
the background server generates a corresponding data acquisition strategy for each monitoring area and sends the generated data acquisition strategies to each wireless sensor in the corresponding monitoring area, wherein the data acquisition strategies define the sequence of acquiring uploading data by the wireless sensors in each monitoring area;
each wireless sensor executes the received corresponding data acquisition strategy, and one of the plurality of wireless sensors in each monitoring area performs data acquisition and sends the acquired detection data to the background server at each data uploading time node;
the background server executes alarm operation when one of the received detection data is greater than or equal to an alarm value;
the low-power consumption data monitoring method further comprises the following steps:
generating a correlation diagram for a plurality of wireless sensors in each monitoring area through the background server, wherein each wireless sensor is used as a connecting node in the correlation diagram, and each connecting node is connected with at least one other connecting node;
when one of the received detection data is larger than or equal to an early warning value and smaller than an alarm value, taking a wireless sensor with the acquired detection data larger than or equal to the early warning value and smaller than the alarm value as a main sensor, taking a wireless sensor directly connected with the main sensor in the association graph as an association sensor, and sending a supplementary acquisition instruction to the main sensor and a plurality of association sensors by a background server;
the main sensor and the associated sensor which receive the supplementary acquisition instruction perform data acquisition uploading operation at the next data uploading time node;
if the detection data uploaded by the main sensor is still greater than or equal to an early warning value and smaller than the alarm value, and meanwhile, the detection data uploaded by at least one of the plurality of associated sensors is greater than or equal to the early warning value and smaller than the alarm value, the background server executes early warning operation;
the specific method for the background server to execute the early warning operation is as follows:
determining a first weight value according to the number of the associated sensors corresponding to the main sensor;
determining a second weight value according to the number of the related sensors, which are greater than or equal to the early warning value and smaller than the warning value, of the uploaded detection data;
determining an early warning level according to the first weight value and the second weight value;
executing the corresponding early warning operation according to the early warning level;
the specific method for the background server to execute the alarm operation when one of the received detection data is greater than or equal to the alarm value is as follows:
sending alarm information to mobile equipment of a first risk manager;
the specific method for executing the corresponding early warning operation according to the early warning level comprises the following steps:
when the early warning level reaches a preset level, sending the alarm information to mobile equipment of a first risk manager;
and when the early warning level does not reach the preset level, sending early warning information to the mobile equipment of the second risk management personnel.
2. The method for low power consumption data monitoring as claimed in claim 1, wherein,
the specific method for generating the association graph for the wireless sensors in each monitoring area through the background server comprises the following steps:
acquiring the distance between each wireless sensor in the monitoring area;
setting a distance threshold;
and using each wireless sensor as one connecting node, and connecting the connecting nodes represented by the wireless sensors with the distance between each other being smaller than or equal to the distance threshold value through connecting wires to form the association graph.
3. The method for low power consumption data monitoring as claimed in claim 2, wherein,
the specific method for acquiring the distance between each wireless sensor in the monitoring area comprises the following steps:
establishing a 3D model according to the building project to be monitored;
corresponding marks are carried out in the 3D model according to the actual positions of the wireless sensors in the building project;
and obtaining the distance values of the two wireless sensors in the 3D model and the scaling of the 3D model to calculate the distance between the two wireless sensors.
4. A low power consumption data monitoring method according to any of the claims 2-3, characterized in that,
the range of the ratio of the early warning value to the alarm value is more than or equal to 0.9 and less than 1.
5. The method for low power consumption data monitoring as claimed in claim 1, wherein,
the low-power consumption data monitoring method further comprises the following steps:
and the background server also acquires temperature information of the area where the building project to be monitored is located, and corrects the received detection data according to the temperature information.
6. The method for low power consumption data monitoring as claimed in claim 1, wherein,
the wireless sensor enters a low power sleep mode during non-operation.
Priority Applications (1)
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