Geotechnical engineering monitoring system based on Internet of Things

Abstract

The invention discloses a geotechnical engineering monitoring system based on the Internet of Things, and relates to the technical field of geotechnical engineering monitoring, and the system comprises a sensor data collection module which collects geotechnical data in real time based on a geotechnical structure sensor; the data analysis and processing module is used for carrying out real-time analysis on the primarily processed data, judging the stability of the rock-soil structure and carrying out potential disaster prediction; the monitoring and early warning module is used for monitoring the health state of the rock-soil structure in real time; the energy management module is used for supplying power for a long time based on a solar power supply and energy collection technology; and the cloud platform and data visualization module provides remote access, analysis and management functions. The physical state of the rock-soil structure is monitored in real time, data of different sensors are aggregated, key signals are extracted through a time sequence analysis method and the like, the safety coefficient and stability of the rock-soil structure can be accurately evaluated, potential disaster risks are analyzed by establishing a disaster prediction model, early warning is made in advance, and the safety coefficient and stability of the rock-soil structure are improved. And disasters are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of geotechnical engineering monitoring, and in particular to a geotechnical engineering monitoring system based on the Internet of Things. Background Art

[0002] With the continuous advancement of urbanization, geotechnical engineering plays an important role in the construction of infrastructure such as buildings, roads, bridges, and dams. Geotechnical engineering structures such as foundations and rock formations are usually affected by complex geological conditions and the external environment, and there are safety hazards such as landslides, collapses, and subsidence. Therefore, real-time monitoring, analysis, and early warning of geotechnical engineering are particularly important. Traditional geotechnical engineering monitoring methods mainly rely on manual inspections and regular testing, which have problems such as untimely data collection, lag in manual judgment, and limited monitoring coverage.

[0003] In order to improve the accuracy and timeliness of monitoring, Internet of Things technology and big data analysis technology are gradually being applied to the field of geotechnical engineering. These technologies can realize remote real-time monitoring, data analysis and disaster prediction, thereby improving the safety of geotechnical engineering structures and providing early warning of potential risks. Internet of Things technology can automatically collect various monitoring data at geotechnical engineering sites through sensors, edge computing and wireless communications, and transmit them to remote platforms for real-time analysis and processing. Summary of the invention

[0004] In order to solve the above technical problems, a geotechnical engineering monitoring system based on the Internet of Things is provided. This technical solution solves the above problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] Geotechnical engineering monitoring system based on IoT, including:

[0007] Sensor data acquisition module: The sensor data acquisition module is used to collect geotechnical data in real time based on geotechnical structure sensors, and perform preliminary data processing at the data collection point based on edge computing technology;

[0008] Data analysis and processing module: The data analysis and processing module is electrically connected to the sensor data acquisition module, and is used to perform real-time analysis on the data after preliminary processing, determine the stability of the geotechnical structure, and predict potential disasters;

[0009] Monitoring and early warning module: The monitoring and early warning module is electrically connected to the data analysis and processing module. The monitoring and early warning module is used to monitor the health status of the geotechnical structure in real time, and trigger an early warning when the monitoring data reaches a threshold, establish a risk model, and generate a personalized early warning plan;

[0010] Energy management module: The energy management module is electrically connected to the monitoring and early warning module, and the energy management module is used for long-term power supply based on solar power supply and energy collection technology;

[0011] Cloud platform and data visualization module: The cloud platform and data visualization module are electrically connected to the energy management module. The cloud platform and data visualization module are used to upload monitoring data to the cloud platform and provide remote access, analysis and management functions.

[0012] Preferably, the sensor data acquisition module specifically includes:

[0013] Sensor data acquisition unit: Based on geotechnical structure monitoring sensors, including strain sensors, displacement sensors, pressure sensors, and temperature and humidity sensors, it monitors the physical changes of geotechnical bodies in real time, collects real-time data, including strain, displacement, pressure, and temperature, and converts these data into digital signals;

[0014] Data preprocessing and edge computing unit: amplifies and filters the signals collected from the sensor, removes noise, and converts the original output signal of the sensor into physical quantity;

[0015] Standardize the collected data to ensure that the units of the output data from different sensors are consistent, and combine the data from different sensors for multi-dimensional fusion processing to obtain a more accurate health status of the geotechnical structure;

[0016] At the data collection point, the edge computing device performs preliminary analysis and aggregation of the collected data, including calculating the average, maximum, and minimum statistics;

[0017] Use edge computing devices to perform real-time anomaly detection on data, determine whether there are equipment failures, signal interference, and abnormal changes in geotechnical structures, and compress the data;

[0018] Data transmission unit: Packs the data after preliminary processing and sends it to the cloud platform in a format suitable for network transmission.

[0019] Preferably, the data analysis and processing module specifically includes:

[0020] Data aggregation and feature extraction unit: Aggregate data from different sensors to build a multi-dimensional feature data set. Based on the time series analysis method, extract the trend and periodic change characteristics of key signals from the data.

[0021] Geotechnical structure safety factor calculation unit: calculate the safety factor of the geotechnical structure, determine whether the geotechnical structure is in the limit state, use the stress-strain model to simulate the mechanical behavior of the geotechnical material, and thus evaluate the stability of the geotechnical structure;

[0022] Disaster prediction model building unit: predict potential disaster risks based on data-driven models.

[0023] Preferably, the geotechnical structure safety factor calculation unit specifically includes:

[0024] Based on comprehensive geotechnical data, the safety factor of the limit equilibrium theory is used for analysis, where the safety factor calculation formula is:

[0025]

[0026] Where C is the cohesion of the soil, L is the length of the sliding surface, and σ is the normal stress of the soil. is the internal friction angle of the soil, is the area of ​​the sliding surface, and W is the gravity of the sliding body;

[0027] If the safety factor K is less than 1, it indicates that the geotechnical structure is in a limit state and landslide or collapse may occur;

[0028] The mechanical behavior of the soil is evaluated by calculating the stress and strain at each point in the structure using the stress-strain relationship. For elastic materials, the stress and strain of the material are assumed to be proportional and Hooke's law is used. When the geotechnical material undergoes a large deformation, it enters the plastic stage and a plastic model is used.

[0029] Preferably, the disaster prediction model building unit specifically includes:

[0030] Obtain historical data on geotechnical disasters, and establish a disaster prediction model based on the historical data of geotechnical disasters and in combination with a decision tree. The disaster characteristics are used as input and the disaster prediction results are used as output. The disaster prediction model expression is:

[0031] y=f(x 1 ,x 2 …x n )

[0032] In the formula, y is the prediction result, f is the decision tree function, and x 1 ,x 2 …x n The input features include weather data, geographic data, and historical data.

[0033] Preferably, the monitoring and early warning module specifically includes:

[0034] Threshold setting and warning trigger unit: Set the threshold of health monitoring indicators. Once the monitoring data exceeds the set threshold, the system will automatically trigger an early warning.

[0035] Personalized early warning plan generation unit: Based on the real-time risk assessment results, through the decision support system, it generates personalized risk warning reports and provides corresponding safety recommendations;

[0036] Warning notification and response unit: After the warning is triggered, relevant personnel are notified to take measures, and alarms are issued through multiple channels, including SMS, email and APP notifications, to start the emergency response process;

[0037] Follow-up and retrospective analysis unit: Track the subsequent processing after the warning occurs, collect emergency processing results, record the accident handling process, analyze the accuracy and response time of the warning, and provide feedback for system optimization.

[0038] Preferably, the energy management module specifically includes:

[0039] Solar panel configuration unit: deploy solar panels, collect solar energy and convert it into electrical energy, and configure the electrical connection between the panels and the energy management system;

[0040] Energy collection and conversion unit: converts the DC power generated by the solar panels into AC power, converts the DC power generated by the solar panels into the voltage level required by the monitoring system, optimizes the efficiency of the solar panels, and ensures maximum power output under different lighting conditions;

[0041] Energy storage unit: configure battery packs to store excess electricity generated by solar energy, determine battery charging and discharging strategies, ensure that the battery maintains effective capacity and extends its service life over a long period of time, monitor the health status of the battery, detect the battery power, temperature and life, and ensure the stability of the energy storage system;

[0042] Energy management and scheduling unit: monitors the power generation of solar panels, the status of battery packs and power load, and dynamically adjusts energy distribution according to the power demand of the monitoring and early warning module. When the battery power is sufficient, it will give priority to powering the monitoring and early warning module. When the battery power is low, it will give priority to low power consumption mode and start the backup power supply.

[0043] Grid auxiliary unit: configure the grid connection interface, set the priority strategy, give priority to solar power supply, switch to grid power supply in extreme weather, and intelligently switch power sources based on battery power, solar energy collection status and grid power price information;

[0044] Intelligent monitoring and fault diagnosis unit: monitors the solar panels, energy storage system, battery status and energy consumption. Once the system operation is abnormal, it notifies the administrator through the alarm system and provides a fault diagnosis report.

[0045] Preferably, the intelligent monitoring and fault diagnosis unit specifically includes:

[0046] Through the remote monitoring platform, it provides equipment operation status, historical data analysis and troubleshooting suggestions, regularly evaluates the power consumption of the monitoring system, and dynamically adjusts energy allocation according to demand;

[0047] Intelligently optimize energy collection, storage and use based on environmental conditions and power demand, and regularly evaluate the system's energy efficiency to find potential for improvement, thereby reducing waste and improving the system's ability to provide continuous power;

[0048] Optimize future energy dispatch strategies based on past weather data, battery charging and discharging records, and load demand.

[0049] Preferably, the cloud platform and data visualization module specifically include:

[0050] Monitoring data collection unit: collects real-time monitoring data from the energy management module, including battery power, power generation, load demand and meteorological data, and uploads the collected monitoring data to the cloud platform through wireless communication using the communication protocol;

[0051] Data storage and processing unit: stores the uploaded data in the database of the cloud platform, and the data storage structure is time series data;

[0052] Decision support unit: Implement a decision support system on the cloud platform to provide users with optimization suggestions based on data analysis results;

[0053] Data visualization and report generation unit: Provides visualization functions of real-time and historical data on the cloud platform, including charts, maps and dashboards;

[0054] Interactive dashboard unit: provides interactive dashboards, allowing users to customize views and instruments according to their needs. The dashboards support real-time data updates, historical data backtracking, and comparative analysis.

[0055] Remote management and control unit: Based on the remote access function of the mobile terminal, users can view the system operation status and monitoring data through the browser at any time.

[0056] Preferably, the remote management and control unit specifically includes:

[0057] Assign different access rights according to user roles and provide remote control and management functions;

[0058] Based on the data analysis results of the cloud platform, the system automatically adjusts the scheduling strategy, performs anomaly detection and alarm in real time, and encrypts and protects sensitive data stored in the cloud platform to ensure that only authorized users can access it.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] The present invention proposes real-time monitoring of the physical state of geotechnical structures. By aggregating data from different sensors and extracting key signals through methods such as time series analysis, the safety factor and stability of geotechnical structures can be accurately assessed. By establishing a disaster prediction model, potential disaster risks can be analyzed and early warnings can be issued. The monitoring and early warning module can generate personalized risk warning reports based on real-time monitoring data, optimize response time and processing efficiency, and avoid disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0062] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0063] Reference Figure 1 As shown, the geotechnical engineering monitoring system based on the Internet of Things includes: a sensor data acquisition module: the sensor data acquisition module is used to collect geotechnical data in real time based on geotechnical structure sensors, and performs preliminary data processing at the data acquisition point based on edge computing technology; a data analysis and processing module: the data analysis and processing module is electrically connected to the sensor data acquisition module, and the data analysis and processing module is used to perform real-time analysis on the data after preliminary processing, judge the stability of the geotechnical structure, and predict potential disasters; a monitoring and early warning module: the monitoring and early warning module is electrically connected to the data analysis and processing module, and the monitoring and early warning module is used to monitor the health status of the geotechnical structure in real time, and when the monitoring data reaches a threshold, trigger an early warning, establish a risk model, and generate a personalized early warning plan; an energy management module: the energy management module is electrically connected to the monitoring and early warning module, and the energy management module is used to provide long-term power supply based on solar power supply and energy collection technology; a cloud platform and data visualization module: the cloud platform and the data visualization module are electrically connected to the energy management module, and the cloud platform and the data visualization module are used to upload the monitoring data to the cloud platform to provide remote access, analysis and management functions.

[0064] The sensor data acquisition module specifically includes:

[0065] Sensor data acquisition unit: Based on geotechnical structure monitoring sensors, including strain sensors, displacement sensors, pressure sensors, and temperature and humidity sensors, it monitors the physical changes of geotechnical bodies in real time, collects real-time data, including strain, displacement, pressure, and temperature, and converts these data into digital signals;

[0066] Data preprocessing and edge computing unit: amplifies and filters the signals collected from the sensor, removes noise, and converts the original output signal of the sensor into physical quantity;

[0067] Standardize the collected data to ensure that the units of the output data from different sensors are consistent, and combine the data from different sensors for multi-dimensional fusion processing to obtain a more accurate health status of the geotechnical structure;

[0068] At the data collection point, the edge computing device performs preliminary analysis and aggregation of the collected data, including calculating the average, maximum, and minimum statistics;

[0069] Use edge computing devices to perform real-time anomaly detection on data, determine whether there are equipment failures, signal interference, and abnormal changes in geotechnical structures, and compress the data;

[0070] Data transmission unit: Packs the data after preliminary processing and sends it to the cloud platform in a format suitable for network transmission.

[0071] The data analysis and processing module specifically includes:

[0072] Data aggregation and feature extraction unit: Aggregate data from different sensors to build a multi-dimensional feature data set. Based on the time series analysis method, extract the trend and periodic change characteristics of key signals from the data.

[0073] Geotechnical structure safety factor calculation unit: calculate the safety factor of the geotechnical structure, determine whether the geotechnical structure is in the limit state, use the stress-strain model to simulate the mechanical behavior of the geotechnical material, and thus evaluate the stability of the geotechnical structure;

[0074] Disaster prediction model building unit: predict potential disaster risks based on data-driven models.

[0075] The geotechnical structure safety factor calculation unit specifically includes:

[0076] Based on comprehensive geotechnical data, the safety factor of the limit equilibrium theory is used for analysis, where the safety factor calculation formula is:

[0077]

[0078] Where C is the cohesion of the soil, L is the length of the sliding surface, and σ is the normal stress of the soil. is the internal friction angle of the soil, is the area of ​​the sliding surface, and W is the gravity of the sliding body;

[0079] If the safety factor K is less than 1, it indicates that the geotechnical structure is in a limit state and landslide or collapse may occur;

[0080] The mechanical behavior of the soil is evaluated by calculating the stress and strain at each point in the structure using the stress-strain relationship. For elastic materials, the stress and strain of the material are assumed to be proportional and Hooke's law is used. When the geotechnical material undergoes a large deformation, it enters the plastic stage and a plastic model is used.

[0081] The disaster prediction model establishment unit specifically includes:

[0082] Obtain historical data on geotechnical disasters, and establish a disaster prediction model based on the historical data of geotechnical disasters and in combination with a decision tree. The disaster characteristics are used as input and the disaster prediction results are used as output. The disaster prediction model expression is:

[0083] y=f(x 1 ,x 2 …x n )

[0084] In the formula, y is the prediction result, f is the decision tree function, and x 1 ,x 2 …x n The input features include weather data, geographic data, and historical data.

[0085] The monitoring and early warning module specifically includes:

[0086] Threshold setting and warning trigger unit: Set the threshold of health monitoring indicators. Once the monitoring data exceeds the set threshold, the system will automatically trigger an early warning.

[0087] Personalized early warning plan generation unit: Based on the real-time risk assessment results, through the decision support system, it generates personalized risk warning reports and provides corresponding safety recommendations;

[0088] Warning notification and response unit: After the warning is triggered, relevant personnel are notified to take measures, and alarms are issued through multiple channels, including SMS, email and APP notifications, to start the emergency response process;

[0089] Follow-up and retrospective analysis unit: Track the subsequent processing after the warning occurs, collect emergency processing results, record the accident handling process, analyze the accuracy and response time of the warning, and provide feedback for system optimization.

[0090] The energy management module specifically includes:

[0091] Solar panel configuration unit: deploy solar panels, collect solar energy and convert it into electrical energy, and configure the electrical connection between the panels and the energy management system;

[0092] Energy collection and conversion unit: converts the DC power generated by the solar panels into AC power, converts the DC power generated by the solar panels into the voltage level required by the monitoring system, optimizes the efficiency of the solar panels, and ensures maximum power output under different lighting conditions;

[0093] Energy storage unit: configure battery packs to store excess electricity generated by solar energy, determine battery charging and discharging strategies, ensure that the battery maintains effective capacity and extends its service life over a long period of time, monitor the health status of the battery, detect the battery power, temperature and life, and ensure the stability of the energy storage system;

[0094] Energy management and scheduling unit: monitors the power generation of solar panels, the status of battery packs and power load, and dynamically adjusts energy distribution according to the power demand of the monitoring and early warning module. When the battery power is sufficient, it will give priority to powering the monitoring and early warning module. When the battery power is low, it will give priority to low power consumption mode and start the backup power supply.

[0095] Grid auxiliary unit: configure the grid connection interface, set the priority strategy, give priority to solar power supply, switch to grid power supply in extreme weather, and intelligently switch power sources based on battery power, solar energy collection status and grid power price information;

[0096] Intelligent monitoring and fault diagnosis unit: monitors the solar panels, energy storage system, battery status and energy consumption. Once the system operation is abnormal, it notifies the administrator through the alarm system and provides a fault diagnosis report.

[0097] The intelligent monitoring and fault diagnosis unit specifically includes:

[0098] Through the remote monitoring platform, it provides equipment operation status, historical data analysis and troubleshooting suggestions, regularly evaluates the power consumption of the monitoring system, and dynamically adjusts energy allocation according to demand;

[0099] Intelligently optimize energy collection, storage and use based on environmental conditions and power demand, and regularly evaluate the system's energy efficiency to find potential for improvement, thereby reducing waste and improving the system's ability to provide continuous power;

[0100] Optimize future energy dispatch strategies based on past weather data, battery charging and discharging records, and load demand.

[0101] The cloud platform and data visualization module specifically include:

[0102] Monitoring data collection unit: collects real-time monitoring data from the energy management module, including battery power, power generation, load demand and meteorological data, and uploads the collected monitoring data to the cloud platform through wireless communication using the communication protocol;

[0103] Data storage and processing unit: stores the uploaded data in the database of the cloud platform, and the data storage structure is time series data;

[0104] Decision support unit: Implement a decision support system on the cloud platform to provide users with optimization suggestions based on data analysis results;

[0105] Data visualization and report generation unit: Provides visualization functions of real-time and historical data on the cloud platform, including charts, maps and dashboards;

[0106] Interactive dashboard unit: provides interactive dashboards, allowing users to customize views and instruments according to their needs. The dashboards support real-time data updates, historical data backtracking, and comparative analysis.

[0107] Remote management and control unit: Based on the remote access function of the mobile terminal, users can view the system operation status and monitoring data through the browser at any time.

[0108] The remote management and control unit specifically includes:

[0109] Assign different access rights according to user roles and provide remote control and management functions;

[0110] Based on the data analysis results of the cloud platform, the system automatically adjusts the scheduling strategy, performs anomaly detection and alarm in real time, and encrypts and protects sensitive data stored in the cloud platform to ensure that only authorized users can access it.

[0111] In summary, the advantages of the present invention are:

[0112] Through the sensor data acquisition module, the system can monitor the physical status of the geotechnical structure in real time, including strain, displacement, pressure, temperature and humidity, and perform preliminary processing on the collected data through edge computing technology. This efficient real-time monitoring capability can help engineers quickly understand the health status of the geotechnical structure.

[0113] The data analysis and processing module aggregates data from different sensors and extracts key signals through time series analysis and other methods, which can accurately assess the safety factor and stability of geotechnical structures. The system can also analyze potential disaster risks and issue early warnings by establishing disaster prediction models.

[0114] The monitoring and early warning module can generate personalized risk early warning reports based on real-time monitoring data. Once the monitoring data exceeds the preset threshold, the system will automatically trigger an early warning and notify relevant personnel. The personalized early warning plan generation unit provides safety recommendations for specific monitoring points, optimizes response time and processing efficiency, and avoids disasters.

[0115] The energy management module uses solar panels as the main power source, combined with energy storage systems and energy management technology to ensure that the system can operate stably for a long time without relying on external power grid power. Through intelligent scheduling strategies, the system can flexibly adjust power distribution according to battery power and light conditions to ensure the continuous power supply capacity of the monitoring system;

[0116] Through the cloud platform and data visualization module, the system can upload the collected data to the cloud in real time, provide remote access and management functions, and users can view real-time monitoring data, historical data, and perform data comparison and analysis through the interactive dashboard. In addition, the cloud platform also supports role permission management and data encryption to ensure data security and access control;

[0117] The intelligent monitoring and fault diagnosis unit can monitor the energy system in real time, provide fault diagnosis reports when abnormalities are found, and notify management personnel to handle them. This function can not only improve the stability of the system, but also optimize the energy efficiency, reduce the energy consumption of the system, and extend the life of the equipment;

[0118] Through intelligent monitoring and early warning systems, engineering accidents caused by human errors or neglect of geotechnical structural changes can be greatly reduced. Early warning can reduce unnecessary losses and provide protection for the long-term safety of engineering projects.

[0119] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. Geotechnical engineering monitoring system based on Internet of Things, characterized by: include: Sensor data acquisition module: The sensor data acquisition module is used to collect geotechnical data in real time based on geotechnical structure sensors and perform preliminary data processing at the data collection point based on edge computing technology; Data analysis and processing module: The data analysis and processing module is electrically connected to the sensor data acquisition module, and is used to perform real-time analysis on the data after preliminary processing, determine the stability of the geotechnical structure, and predict potential disasters; Monitoring and early warning module: The monitoring and early warning module is electrically connected to the data analysis and processing module. The monitoring and early warning module is used to monitor the health status of the geotechnical structure in real time, and trigger an early warning when the monitoring data reaches a threshold, establish a risk model, and generate a personalized early warning plan; Energy management module: The energy management module is electrically connected to the monitoring and early warning module, and the energy management module is used for long-term power supply based on solar power supply and energy collection technology; Cloud platform and data visualization module: The cloud platform and data visualization module are electrically connected to the energy management module. The cloud platform and data visualization module are used to upload monitoring data to the cloud platform and provide remote access, analysis and management functions.

2. The geotechnical engineering monitoring system based on the Internet of Things according to claim 1 is characterized in that: The sensor data acquisition module specifically includes: Sensor data acquisition unit: collects real-time data, including strain, displacement, pressure and temperature, and converts these data into digital signals; Data preprocessing and edge computing unit: amplifies and filters the signals collected from the sensor, removes noise, and converts the original output signal of the sensor into physical quantity; Use edge computing devices to perform real-time anomaly detection on data, determine whether there are equipment failures, signal interference, and abnormal changes in geotechnical structures, and compress the data; Data transmission unit: Packs the data after preliminary processing and sends it to the cloud platform in a format suitable for network transmission.

3. The geotechnical engineering monitoring system based on the Internet of Things according to claim 2 is characterized in that: The data analysis and processing module specifically includes: Data aggregation and feature extraction unit: Aggregate data from different sensors to build a multi-dimensional feature data set. Based on the time series analysis method, extract the trend and periodic change characteristics of key signals from the data. Geotechnical structure safety factor calculation unit: calculate the safety factor of the geotechnical structure, determine whether the geotechnical structure is in the limit state, use the stress-strain model to simulate the mechanical behavior of the geotechnical material, and thus evaluate the stability of the geotechnical structure; Disaster prediction model building unit: predict potential disaster risks based on data-driven models.

4. The geotechnical engineering monitoring system based on the Internet of Things according to claim 3 is characterized in that: The geotechnical structure safety factor calculation unit specifically includes: Based on comprehensive geotechnical data, the safety factor of the limit equilibrium theory is used for analysis, where the safety factor calculation formula is: Where C is the cohesion of the soil, L is the length of the sliding surface, and σ is the normal stress of the soil. is the internal friction angle of the soil, is the area of ​​the sliding surface, and W is the gravity of the sliding body; If the safety factor K is less than 1, it indicates that the geotechnical structure is in a limit state and landslide or collapse may occur; By calculating the stress and strain at each point in the structure, the stress-strain relationship is used to evaluate the mechanical behavior of the soil. For elastic materials, the stress and strain of the material are assumed to be proportional, and Hooke's law is used. When the geotechnical material undergoes a large deformation, it enters the plastic stage and the plastic model is used.

5. The geotechnical engineering monitoring system based on the Internet of Things according to claim 4 is characterized in that: The disaster prediction model establishment unit specifically includes: Obtain historical data on geotechnical disasters, and based on the historical data on geotechnical disasters, establish a disaster prediction model in combination with a decision tree, with disaster characteristics as input and disaster prediction results as output. The disaster prediction model expression is: y=f(x1,x2…x n ) In the formula, y is the prediction result, f is the decision tree function, x1,x2…x n The input features include weather data, geographic data, and historical data.

6. The geotechnical engineering monitoring system based on the Internet of Things according to claim 5 is characterized in that: The monitoring and early warning module specifically includes: Threshold setting and warning trigger unit: Set the threshold of health monitoring indicators. Once the monitoring data exceeds the set threshold, the system will automatically trigger an early warning. Personalized early warning plan generation unit: Based on the real-time risk assessment results, through the decision support system, it generates personalized risk warning reports and provides corresponding safety recommendations; Warning notification and response unit: After the warning is triggered, relevant personnel are notified to take measures, and alarms are issued through multiple channels, including SMS, email and APP notifications, to start the emergency response process; Follow-up and retrospective analysis unit: Track the subsequent processing after the warning occurs, collect emergency processing results, record the accident handling process, analyze the accuracy and response time of the warning, and provide feedback for system optimization.

7. The geotechnical engineering monitoring system based on the Internet of Things according to claim 6 is characterized in that: The energy management module specifically includes: Solar panel configuration unit: deploy solar panels, collect solar energy and convert it into electrical energy, and configure the electrical connection between the panels and the energy management system; Energy collection and conversion unit: converts the DC power generated by the solar panels into AC power, converts the DC power generated by the solar panels into the voltage level required by the monitoring system, optimizes the efficiency of the solar panels, and ensures maximum power output under different lighting conditions; Energy storage unit: configure battery packs to store excess electricity generated by solar energy, determine battery charge and discharge strategies, ensure that the battery maintains effective capacity and extends its service life over a long period of time, monitor the battery's health status, detect the battery's power, temperature, and life, and ensure the stability of the energy storage system; Intelligent monitoring and fault diagnosis unit: monitors the solar panels, energy storage system, battery status and energy consumption. Once the system operation is abnormal, it notifies the administrator through the alarm system and provides a fault diagnosis report.

8. The geotechnical engineering monitoring system based on the Internet of Things according to claim 7 is characterized in that: The intelligent monitoring and fault diagnosis unit specifically includes: Through the remote monitoring platform, it provides equipment operation status, historical data analysis and troubleshooting suggestions, regularly evaluates the power consumption of the monitoring system, and dynamically adjusts energy allocation according to demand; Intelligently optimize energy collection, storage and use based on environmental conditions and power demand, and regularly evaluate the system's energy efficiency to find potential for improvement, thereby reducing waste and improving the system's ability to provide continuous power; Optimize future energy dispatch strategies based on past weather data, battery charging and discharging records, and load demand.

9. The geotechnical engineering monitoring system based on the Internet of Things according to claim 8, characterized in that: The cloud platform and data visualization module specifically include: Monitoring data collection unit: collects real-time monitoring data from the energy management module, including battery power, power generation, load demand and meteorological data, and uploads the collected monitoring data to the cloud platform through wireless communication using the communication protocol; Data visualization and report generation unit: Provides visualization functions of real-time and historical data on the cloud platform, including charts, maps and dashboards; Interactive dashboard unit: provides interactive dashboards, allowing users to customize views and instruments according to their needs. The dashboards support real-time data updates, historical data backtracking, and comparative analysis. Remote management and control unit: Based on the remote access function of the mobile terminal, users can view the system operation status and monitoring data through the browser at any time.

10. The geotechnical engineering monitoring system based on the Internet of Things according to claim 9, characterized in that: The remote management and control unit specifically includes: Assign different access rights according to user roles and provide remote control and management functions; Based on the data analysis results of the cloud platform, the system automatically adjusts the scheduling strategy, performs anomaly detection and alarm in real time, and encrypts and protects sensitive data stored in the cloud platform to ensure that only authorized users can access it.

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