CN-122022445-A - Internet of things environment monitoring method, equipment, product and medium

CN122022445ACN 122022445 ACN122022445 ACN 122022445ACN-122022445-A

Abstract

An environment monitoring method, equipment, products and media for the Internet of things relate to the technical field of the Internet of things. The method comprises the steps of dividing a monitoring area into an upstream reservoir area, a middle reservoir area and a front reservoir area based on topographic distribution data and dam position information, acquiring multi-point pollutant concentration distribution data and flow rate monitoring data for the upstream reservoir area, determining a pollution source direction area based on the pollutant concentration distribution data, determining a water layering stability state based on temperature distribution data and the change trend of dissolved oxygen content of each water layer for the middle reservoir area, acquiring water level fluctuation data and gate opening information for the front reservoir area, calculating water level response time and response amplitude based on the water level fluctuation data and the gate opening information, determining response characteristics of the reservoir area to the scheduling operation based on the water level response time and the response amplitude, and determining a comprehensive environment assessment report based on the pollution source direction area, the water layering stability state and the response characteristics. The method has the effect of improving the accuracy of environmental monitoring.

Inventors

TANG JUN
XU LONG
ZHU XIAOMI
ZHU JINTAO
ZHAO ZIXUAN
ZHOU FENGQI
Xie Gewei

Assignees

三峡长电大数据科技(宜昌)有限公司

Dates

Publication Date: 20260512
Application Date: 20251211

Claims (10)

1. An internet of things environment monitoring method, comprising: acquiring topographic distribution data and dam position information of a reservoir area, and dividing a monitoring area into an upstream reservoir area, a midstream reservoir area and a pre-dam reservoir area based on the topographic distribution data and the dam position information; For an upstream reservoir area, acquiring multi-point pollutant concentration distribution data and flow rate monitoring data, calculating a pollutant concentration gradient based on the pollutant concentration distribution data, and determining a pollution source direction area based on the pollutant concentration gradient and the flow rate monitoring data; for a midstream pool area, acquiring vertically layered temperature distribution data and dissolved oxygen content of each water layer, calculating a temperature layering coefficient based on the temperature distribution data, and determining a water layering stability state based on the temperature layering coefficient and the change trend of the dissolved oxygen content of each water layer; Acquiring water level fluctuation data and gate opening information aiming at a pre-dam reservoir area, calculating water level response time and response amplitude based on the water level fluctuation data and the gate opening information, and determining response characteristics of the reservoir area to scheduling operation based on the water level response time and the response amplitude; Based on the pollution source direction area, the water body layering stability state and the response characteristic, a comprehensive environment assessment report is determined.
2. The internet of things environment monitoring method according to claim 1, wherein the calculating a contaminant concentration gradient based on the contaminant concentration distribution data, determining a contaminant source direction area based on the contaminant concentration gradient and the flow rate monitoring data, specifically comprises: Obtaining the real-time value of the pollutant concentration of each monitoring point in the upstream reservoir area, carrying out difference operation on the pollutant concentration values of adjacent monitoring points, dividing the difference operation result by the distance value between the adjacent monitoring points to obtain the pollutant concentration gradient between each adjacent monitoring point; performing spatial interpolation processing on each pollutant concentration gradient according to the geographic coordinates of the monitoring points to generate a pollutant concentration gradient distribution diagram of an upstream reservoir area, and identifying a region with the largest pollutant concentration gradient value from the pollutant concentration gradient distribution diagram as a region with the most intense pollutant concentration change; Acquiring flow velocity monitoring data of each monitoring point in the area with the most severe pollutant concentration change, extracting flow velocity direction angles and flow velocity magnitude values of each monitoring point, and performing vector superposition operation on the flow velocity direction angles and pollutant concentration gradient directions to obtain pollutant transmission direction angles of each monitoring point, wherein the pollutant concentration gradient directions are the directions with the fastest pollutant concentration increase; and carrying out reverse tracking calculation on the pollutant transmission direction angles of all the monitoring points, marking tracking paths in the terrain distribution data, and determining the intersection areas of a plurality of reverse tracking paths as pollution source direction areas.
3. The method for monitoring the environment of the internet of things according to claim 1, wherein the steps of obtaining the temperature distribution data of the vertical stratification and the dissolved oxygen content of each water layer, calculating the temperature stratification coefficient based on the temperature distribution data, and determining the water body stratification stability state based on the temperature stratification coefficient and the change trend of the dissolved oxygen content of each water layer comprise the following steps: Acquiring measurement values of temperature sensors at different depth positions in the vertical direction in the midstream storehouse region, and dividing measurement points into three water layers of a surface layer, a middle layer and a bottom layer according to the water depth direction; Calculating the temperature difference value and the depth difference value between adjacent water layers, dividing each temperature difference value by the depth difference value between the corresponding water layers to obtain temperature gradient values between each water layer, and carrying out accumulation operation on absolute values of the temperature gradient values between all water layers to obtain a temperature layering coefficient; obtaining the dissolved oxygen content of each water layer in a preset time period, and taking the difference value between the maximum value and the minimum value of the dissolved oxygen content in the preset time period as the change amplitude of the dissolved oxygen content; Calculating standard deviation of the variation amplitude of the dissolved oxygen content of the surface layer, the middle layer and the bottom layer, taking the standard deviation as the variation degree of the variation amplitude of the dissolved oxygen content, and carrying out weighted summation on the variation degree of the variation amplitude of the dissolved oxygen content and the temperature layering coefficient value to obtain a corresponding water layering degree evaluation value; Marking the water layering degree evaluation value higher than a preset state threshold as a stable layering state, marking the water layering degree evaluation value not higher than the preset state threshold as a mixed state, and taking the stable layering state and the mixed state as the water layering stability state.
4. The internet of things environment monitoring method according to claim 1, wherein the calculating of the water level response time and the response amplitude based on the water level fluctuation data and the gate opening information specifically comprises: Extracting gate opening change starting time and change degree value from the gate opening information; Identifying the change time when the change rate of the water level value exceeds a preset change rate threshold value for the first time from the water level fluctuation data, and calculating the time interval between the gate opening change starting time and the change time as the water level response time; and taking the variation of the water level value in the water level response time in the water level fluctuation data as the response amplitude.
5. The method for monitoring the environment of the internet of things according to claim 1, wherein the determining the response characteristic of the reservoir area to the scheduling operation based on the water level response time and the response amplitude specifically comprises: Carrying out ratio operation on the water level response time and the response amplitude to obtain a response rate index; Counting the numerical distribution condition of response rate indexes in the operation process of the gate for a plurality of times, and calculating the average numerical value of the response rate indexes of the operation for a plurality of times; The operation condition that the response rate index value is higher than the average value is marked as high-sensitivity response characteristic, the operation condition that the response rate index value is not higher than the average value is marked as low-sensitivity response characteristic, and the high-sensitivity response characteristic and the low-sensitivity response characteristic are used as response characteristics of a warehouse area to scheduling operation.
6. The method for monitoring the environment of the internet of things according to claim 1, wherein the determining the comprehensive environmental assessment report based on the pollution source direction area, the water body layered stability state and the response characteristic specifically comprises: Performing superposition analysis on the pollution source direction area identified by the upstream reservoir area and the topographic distribution data, determining geographic position coordinates and influence scope boundaries of the pollution source direction area, and evaluating diffusion paths and propagation speeds of pollutants propagated downstream from the pollution source direction area based on the geographic position coordinates and the influence scope boundaries; Performing correlation analysis on the water layering stability state and the temperature layering coefficient of the midstream storehouse region, identifying the water exchange capacity in the stable layering state and the vertical convection intensity in the mixed state, and evaluating the influence degree of different layering states on the vertical diffusion of pollutants; Matching and analyzing the response characteristics of the dam front reservoir area and the gate dispatching operation history record, identifying the optimal dispatching time corresponding to the high-sensitivity response characteristics and the dispatching delay risk corresponding to the low-sensitivity response characteristics, and evaluating the regulation and control effect of dispatching operation on the environmental conditions of the reservoir area; And determining a comprehensive environment assessment report based on the diffusion path, the propagation speed, the influence degree and the regulation effect.
7. The method for monitoring the environment of the internet of things according to claim 6, wherein the determining the comprehensive environmental assessment report based on the diffusion path, the propagation speed, the influence degree and the regulation effect specifically comprises: According to the diffusion path and the propagation speed, calculating the expected arrival time and the concentration attenuation value of the pollutants along the key nodes on the diffusion path, and generating a pollutant space-time propagation data table; According to the water body layering stability state, when the water body layering stability state is a stable layering state, the vertical retention time of the pollutants is calculated by combining the influence degree and applying a vertical retention conversion principle; the pollutant space-time propagation data table and the vertical retention time or vertical dilution multiple of the pollutant are synthesized, the final concentration value and the total retention time of the pollutant at each position in a reservoir area are calculated, and the area where the total retention time exceeds a preset safety time threshold and the final concentration value exceeds the preset safety concentration threshold is marked as a high risk area; Respectively making an emergency scheduling operation schedule for high sensitivity response characteristics and a preventive scheduling operation schedule for low sensitivity response characteristics according to evaluation conclusion about optimal scheduling opportunity and scheduling delay risk in the regulation effect; And forming a comprehensive environment assessment report by the reservoir pollution risk distribution map, the emergency dispatch operation scheduling and the preventive dispatch operation scheduling together.
8. An electronic device for internet of things environment monitoring, the electronic device comprising one or more processors and memory coupled with the one or more processors, the memory to store computer program code comprising computer instructions that the one or more processors invoke to cause the electronic device to perform the method of any of claims 1-7.
9. A computer program product comprising instructions which, when run on an electronic device for internet of things environment monitoring, cause the electronic device to perform the method of any of claims 1-7.
10. A computer readable storage medium comprising instructions which, when run on an electronic device for internet of things environment monitoring, cause the electronic device to perform the method of any of claims 1-7.

Description

Internet of things environment monitoring method, equipment, product and medium Technical Field The application relates to the technical field of the Internet of things, in particular to an Internet of things environment monitoring method, equipment, a product and a medium. Background In modern environment monitoring and water resource management, a reservoir is used as an important water conservancy infrastructure and bears multiple functions of flood control, water supply, power generation and the like, and the real-time monitoring and evaluation of the water environment quality of the reservoir has important significance for guaranteeing the safety of water resources and the stability of ecological environment. Along with the acceleration of industrialization progress and the continuous improvement of urban level, reservoirs face dual pressures from point source and non-point source pollution, and the precision and timeliness requirements of water environment monitoring technologies are increasingly improved. At present, in the field of reservoir environment monitoring, a three-dimensional environment online monitoring system and method based on LoRa are disclosed in China patent with publication number CN111800502A, and the method is characterized in that LoRa acquisition nodes are preset at grid positions which are segmented in advance in an environment to be monitored, environmental information and geographic position information are acquired, and the historical environmental information with the highest similarity with the environmental information is identified by using a k nearest neighbor algorithm, so that environmental change early warning information is predicted, and the moving speed and direction of out-of-standard pollutants are determined. However, in practical application, because the reservoir environment has the characteristics of large water area, complex hydrologic conditions, uneven distribution of pollution sources and the like, the traditional gridding monitoring method is difficult to fully consider the differences of the functional characteristics and hydrodynamic conditions of different areas of the reservoir, so that the environment is monitored only by means of uniform gridding distribution points and a single data analysis method, and the accuracy of an environment monitoring result is easily insufficient. Disclosure of Invention The application provides an environment monitoring method, equipment, a product and a medium for the Internet of things, which have the effect of improving the accuracy of environment monitoring. In a first aspect of the present application, there is provided a method for monitoring an environment of the internet of things, specifically including: acquiring topographic distribution data and dam position information of a reservoir area, and dividing a monitoring area into an upstream reservoir area, a midstream reservoir area and a pre-dam reservoir area based on the topographic distribution data and the dam position information; For an upstream reservoir area, acquiring multi-point pollutant concentration distribution data and flow rate monitoring data, calculating a pollutant concentration gradient based on the pollutant concentration distribution data, and determining a pollution source direction area based on the pollutant concentration gradient and the flow rate monitoring data; for a midstream pool area, acquiring vertically layered temperature distribution data and dissolved oxygen content of each water layer, calculating a temperature layering coefficient based on the temperature distribution data, and determining a water layering stability state based on the temperature layering coefficient and the change trend of the dissolved oxygen content of each water layer; Acquiring water level fluctuation data and gate opening information aiming at a pre-dam reservoir area, calculating water level response time and response amplitude based on the water level fluctuation data and the gate opening information, and determining response characteristics of the reservoir area to scheduling operation based on the water level response time and the response amplitude; Based on the pollution source direction area, the water body layering stability state and the response characteristic, a comprehensive environment assessment report is determined. By adopting the technical scheme, the topographic distribution data and the dam position information of the reservoir area are obtained, the monitoring area is divided into the upstream reservoir area, the middle reservoir area and the front reservoir area based on the topographic distribution data and the dam position information, the differential monitoring layout aiming at the characteristics of different reservoir areas is realized, the blindness of traditional uniform distribution monitoring is avoided, and the configuration efficiency of monitoring resources is improved. The method comprises the steps of acquiring