Dam termite intelligent monitoring and early warning method and system

Abstract

The invention belongs to the technical field of hydraulic engineering safety monitoring, and particularly relates to a dam termite intelligent monitoring and early warning method and system. The method comprises the following steps: burying monitoring sensors at different positions in a dam body of a dam, and deploying video monitoring modules at set positions of the dam body; when a vibration sensor monitors vibration caused by termite activity, if the vibration sensor is located in a video monitoring range of a video monitoring module, the video monitoring module in the video monitoring range where the vibration sensor is located is started for shooting, or an unmanned aerial vehicle monitoring module is used for shooting an area where the vibration sensor is located. If the vibration sensor is not located in the video monitoring range of any video monitoring module, the unmanned aerial vehicle monitoring module is used for shooting the area where the vibration sensor is located; the unmanned aerial vehicle monitoring module comprises an unmanned aerial vehicle carrying a camera and / or a thermal imager, and determines the nests, the number and the activities of the termites based on the monitored data, thereby achieving the real-time and accurate monitoring of the termites.

Description

Technical Field

[0001] The present invention belongs to the technical field of water conservancy project safety monitoring, and in particular relates to a dam termite intelligent monitoring and early warning method and system. Background Art

[0002] Termites are a major threat to the safety of reservoir dams. Their nests and activities can damage the dam structure and threaten the safety of the reservoir. Therefore, termite monitoring is necessary for reservoir dams and timely termite control. Traditional termite monitoring methods rely primarily on manual inspections and trapping. Manual inspections are inefficient and have limited coverage, making it difficult to detect hidden nests. Trapping cannot accurately reflect termite numbers and activity patterns, resulting in poor monitoring accuracy. Both methods rely on manual judgment of termite presence, resulting in delayed early warnings and difficulties in responding to emergencies.

[0003] To improve the efficiency of termite monitoring, Chinese patent application publication number CN116931110A discloses a method and device for detecting termite nests on earth-rock embankments. The device utilizes a high-definition camera and / or infrared thermal imager and / or infrared gas imager and / or plant spectrometer mounted on a drone. The HD camera captures images of the embankment surface and its surroundings, and an AI model trained using artificial intelligence (AI) training methods identifies natural phenomena in the HD images that reflect termite habits. The infrared thermal imager captures thermal images, which are then used to identify abnormal hotspots and identify suspected termite nest areas. The infrared gas imager captures CO2 concentration images of the embankment surface and its surroundings, and uses these images to identify areas with high CO2 concentrations, thereby identifying suspected termite nest openings. The plant spectrometer captures spectral images of vegetation on the embankment surface and its surroundings, and uses these spectral images to identify termite-related fungi and identify suspected termite nest areas. When any of these devices detects a suspected termite nest area, it designates that area as a suspected termite nest. This method monitors termite nests through drone aerial photography. Although it can improve monitoring efficiency, the size and distribution of the nests are still inaccurate. Moreover, since drones cannot fly in real time at all times, it is impossible to monitor the number and activity patterns of termites in real time and accurately. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for intelligent monitoring and early warning of termites in dams, so as to solve the problems of poor real-time performance and low accuracy of monitoring termite nests by drone aerial photography.

[0005] In order to solve the above-mentioned technical problems, the present invention provides an intelligent monitoring and early warning method for termites in dams, comprising: burying various monitoring sensors at different positions inside the dam body, and deploying various video monitoring modules at set positions on the dam body; the monitoring sensors include vibration sensors for real-time monitoring of vibrations caused by termite activities; when a vibration sensor detects vibrations caused by termite activities, if the vibration sensor is located within the video monitoring range of the video monitoring module, the video monitoring module within the video monitoring range of the vibration sensor is started to shoot, or an unmanned aerial vehicle monitoring module is used to shoot the area where the vibration sensor is located; if the vibration sensor is not within the video monitoring range of any video monitoring module, the unmanned aerial vehicle monitoring module is used to shoot the area where the vibration sensor is located; the unmanned aerial vehicle monitoring module includes a unmanned aerial vehicle equipped with a camera and / or a thermal imager; and the termite nests, number and activities are determined based on the data shot by the video monitoring module and the data shot by the unmanned aerial vehicle monitoring module.

[0006] Furthermore, the monitoring sensor also includes a temperature and humidity sensor for monitoring temperature and humidity changes caused by termite activities, and the temperature and humidity changes caused by termite activities are used to verify the confirmed termite nests, number and activities.

[0007] Furthermore, the method also includes using a drone monitoring module to regularly take aerial photos of the dam to obtain dam surface images and / or thermal infrared images, and using an AI model to process the obtained dam surface images and / or thermal infrared images to identify the location and size of termite nests.

[0008] Furthermore, the drone monitoring module is used to regularly take aerial photos of the dam to obtain dam surface images and thermal infrared images. The dam surface images and thermal infrared images are preprocessed and fused at the pixel level to generate multimodal feature data containing texture features and temperature data. The multimodal data is input into the trained AI model to obtain the location and scale of termite nests.

[0009] Furthermore, when the number of termites or the vibration frequency caused by termite activity or the temperature and humidity changes caused by termite activity exceed the corresponding warning threshold, a warning message is also issued; the warning information is issued in the form of sound and light alarms and / or SMS notifications and / or monitoring center platform notifications.

[0010] The beneficial effects of the above technical solution are as follows: This invention is a pioneering creation. Vibration sensors capable of monitoring termite activity throughout the dam are pre-buried within the dam, and video surveillance modules capable of capturing termite activity are deployed at key locations within the dam. If termites appear within the dam, the embedded vibration sensors can detect the vibration signals caused by the termite activity in real time. At this time, the video surveillance module in the corresponding area is activated, or a drone monitoring module is used to capture the area where the vibration sensor detected the anomaly. The captured data is used to determine the location, activity patterns, and number of termite nests, thereby achieving real-time and accurate monitoring of termites in the dam. Furthermore, the present invention activates the video surveillance module only when an anomaly caused by termites is detected in real time, avoiding blind drone monitoring. This significantly reduces monitoring energy consumption and enables timely and accurate monitoring of termite information, improving the accuracy and practicality of monitoring.

[0011] To solve the above technical problems, the present invention also provides an intelligent monitoring and early warning system for termites in dams, comprising a drone monitoring module, the drone monitoring module comprising a drone equipped with a camera and / or a thermal imager; further comprising a monitoring sensor, a video monitoring module and a data analysis module, wherein each monitoring sensor is buried at a different position inside the dam body, and each video monitoring module is deployed at a set position on the dam body; the monitoring sensor comprises a vibration sensor, the vibration sensor being used to monitor vibrations caused by termite activity in real time; when a vibration sensor detects vibrations caused by termite activity, if the vibration sensor is within the video monitoring range of the video monitoring module, the video monitoring module within the video monitoring range of the vibration sensor is started to shoot, or the drone monitoring module is used to shoot the area where the vibration sensor is located; if the vibration sensor is not within the video monitoring range of any video monitoring module, the drone monitoring module is used to shoot the area where the vibration sensor is located; the data analysis module is used to determine the nests, number and activity of termites based on the data shot by the video monitoring module or the data shot by the drone monitoring module.

[0012] Furthermore, the monitoring sensor also includes a temperature and humidity sensor for monitoring temperature and humidity changes caused by termite activities, and the temperature and humidity changes caused by termite activities are used to verify the confirmed termite nests, number and activities.

[0013] Furthermore, the drone monitoring module is also used to regularly take aerial photos of the dam to obtain dam surface images and / or thermal infrared images, and the dam surface images and / or thermal infrared images are used to identify the location and scale of termite nests after analysis.

[0014] Furthermore, an AI analysis module is also provided in the video monitoring module and the drone monitoring module. The AI ​​analysis module stores a trained AI model. The video monitoring module uses the stored AI model locally to analyze the captured data to obtain termite activity and quantity; the drone monitoring module uses the stored AI model locally to analyze the captured data to obtain termite activity and nests; the video monitoring module or the drone monitoring module sends the data processed by the AI ​​analysis module to the data analysis module. The data analysis module comprehensively determines the termite nests, quantity and activity based on the data processed by the AI ​​analysis module and the monitoring data of the vibration sensor.

[0015] Furthermore, the data analysis module is set up on the monitoring center platform, and the video monitoring module or the drone monitoring module uploads the data captured by itself to the monitoring center platform. The data analysis module stores a trained AI model, and the AI ​​model is used to analyze the data captured by the video monitoring module or the drone monitoring module itself, and comprehensively determine the termite nests, number and activities in combination with the monitoring data of the vibration sensor.

[0016] The beneficial effects of the above technical solution are as follows: the present invention is a pioneering invention. Vibration sensors that can monitor termite activity in various locations within the dam are pre-buried within the dam, and video surveillance modules that can capture termite activity are deployed at key locations within the dam. If termites appear within the dam, the vibration sensors embedded within the dam can detect the vibration signals caused by termite activity in real time. At this time, the video surveillance module within the corresponding area is activated, or a drone monitoring module is used to capture the area where the vibration sensor detected the abnormality. The range and scale of termite activity can be determined based on the abnormality detected by the vibration sensor. The pattern, number, and scale of termite activity can be preliminarily determined based on the captured data. The location, pattern, and number of termite nests can be determined by combining these data, thereby achieving real-time and accurate monitoring of termites in the dam. Furthermore, the present invention only activates the video surveillance module for capture when an abnormality caused by termites is detected in real time, avoiding blind drone monitoring, greatly reducing monitoring energy consumption, and enabling timely and accurate monitoring of termite information, thereby improving the accuracy and practicality of monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a framework diagram of the intelligent monitoring and early warning system for dam termites according to the system implementation method of the present invention; Figure 2 This is a flowchart of the intelligent monitoring and early warning of dam termites according to the embodiment of the method of the present invention; Figure 3 It is a schematic diagram of the composition of a vibration sensor in an embodiment of the method of the present invention. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clear, the specific embodiments of the present invention are further described below with reference to the accompanying drawings.

[0019] The present invention buries a vibration sensor inside the dam body to monitor termite activities in real time, and takes photos of the area where the vibration sensor is located when termite activities are monitored.

[0020] System Implementation The intelligent monitoring and early warning system for termites in dams of the present invention is suitable for real-time monitoring, intelligent analysis and early warning of termite nests, numbers and activities in small reservoirs, thereby improving the safety management level of small reservoirs.

[0021] like Figure 1 As shown in the figure, the intelligent monitoring and early warning system for termites in dams includes on-site monitoring equipment and a monitoring center platform. The on-site monitoring equipment includes a drone monitoring module ( Figure 1 UAV termite nest monitoring), monitoring sensors ( Figure 1 Sensors in termite activity monitoring) and video surveillance modules ( Figure 1 Video intelligent termite population monitoring).

[0022] The drone monitoring module includes a drone equipped with a camera and / or a thermal imager, which is used to take aerial photos of the reservoir dam. The drone's camera captures images of the dam surface, and the drone's thermal imager captures thermal infrared images of the dam. The range and number of termites are determined based on the captured dam surface images and / or thermal infrared images. As an embodiment, the range and location of termites are determined based on data fusion and texture feature analysis of the captured dam surface images and / or thermal infrared images. Furthermore, because termite nests may grow on the soil surface above the termite nests, the temperature inside the nests is different from that outside the nests. Therefore, termite nest information can be determined by identifying the termite nests on the dam surface based on the captured dam surface images, and by detecting the dam surface temperature using the captured thermal infrared images. Termite nest information includes the location and size of the termite nest.

[0023] Monitoring sensors are buried in different locations inside the dam body. The entire dam area is divided into grids. Monitoring sensors are used as grid nodes and deployed in the dam body in a grid manner to cover the entire reservoir dam to monitor termite activity in real time. Monitoring sensors include vibration sensors, which are used to monitor vibrations caused by termite activity in real time. Figure 3As shown, a bait stick (pine wood) is placed inside the vibration sensor. Inside the stick are magnets and fillers (such as glass beads). A magnetic induction sensor (such as a Hall effect sensor) is attached to the stick to monitor its status. Termites within the dam are attracted to the scent of the bait stick inside the vibration sensor. If termites bite through the stick, the glass beads will leak out. Leaking fillers will cause the magnet to drop, resulting in abnormal vibration and magnetic field changes. The Hall effect sensor detects this magnetic field change and generates an alarm signal, which is then transmitted to the monitoring center platform.

[0024] As a preferred embodiment, since the temperature and humidity in the place where termites appear also have significant characteristics, the monitoring sensor also includes a temperature and humidity sensor, which is used to monitor the temperature and humidity changes caused by termite activities in real time.

[0025] Video surveillance modules are distributed and deployed at designated locations within the dam to monitor termite activity and count termites in real time. These locations refer to key areas of the dam, including where the dam foundation meets the ground, where the dam meets the mountainside, and around structures that penetrate the dam, which are prone to leakage. The video surveillance modules can be cameras, using high-definition cameras to capture the area within their video surveillance range to monitor termite activity.

[0026] The on-site monitoring equipment also includes a data acquisition and transmission module, which is used to collect data from the drone monitoring module, monitoring sensors and video monitoring module, and transmit the data to the monitoring center platform through 4G / 5G network and / or Beidou satellite communication, ensuring the reliability of data transmission through multi-mode communication.

[0027] The monitoring center platform includes a data analysis module, which is used to determine the nests, number and activities of termites based on the data sent by the on-site monitoring equipment.

[0028] The monitoring center platform also includes a data receiving and storage module, a data early warning module, a visualization display module and a remote control module.

[0029] The data receiving and storage module is used to receive and store data from on-site monitoring equipment.

[0030] The data warning module is used to issue warnings when termite damage risks are identified. Specifically, if the termite population, the vibration frequency caused by termite activity, or the temperature and humidity changes caused by termite activity exceed corresponding warning thresholds, a warning message will be issued. Warning information can be issued through audible and visual alarms, / or SMS notifications, and / or notifications from the monitoring center platform. Based on the warning information, the monitoring platform center activates the emergency plan and notifies relevant personnel. Each warning threshold is set based on corresponding historical data and dam structural parameters.

[0031] The visualization display module is used to display monitoring data and analysis results in the form of three-dimensional models and / or charts, which are convenient for users to use and maintain.

[0032] The remote control module is used to remotely control and set parameters of drones, cameras, and monitoring sensors.

[0033] As a preferred embodiment, an AI analysis module is further provided in the video monitoring module and the drone monitoring module. The AI ​​analysis module stores a trained AI model. The video monitoring module uses the stored AI model locally to analyze the captured data to obtain termite activity and quantity; the drone monitoring module uses the stored AI model locally to analyze the captured data to obtain termite activity and nests; the video monitoring module or the drone monitoring module sends the data processed by the AI ​​analysis module to the data analysis module. The data analysis module determines the preliminary termite quantity and activity range based on the abnormal area and scale detected by the monitoring sensor, and finally determines the termite nest, quantity and activity based on the data processed by the AI ​​analysis module and the monitoring data of the vibration sensor, thereby reducing the amount of data transmission, improving the data processing rate, and improving the accuracy and timeliness of the early warning.

[0034] As another embodiment, an AI module that analyzes data captured by the video surveillance module and the drone monitoring module is set in the data analysis module of the monitoring center platform, that is, the data analysis module stores a trained AI model, and the video surveillance module or the drone monitoring module uploads the data captured by itself or the visible light / spectral images collected to the monitoring center platform. The data analysis module stores a trained AI model, and the AI ​​model is used to analyze the data captured by the video surveillance module or the drone monitoring module or the visible light / spectral images collected by itself, and combine the monitoring data of the vibration sensor to comprehensively determine the termite nests, number and activities, thereby improving the accuracy and timeliness of the early warning.

[0035] Based on the intelligent monitoring and early warning system for dam termites of the present invention, a method for intelligent monitoring and early warning for dam termites is realized, such as Figure 2 As shown, the following steps are included: 1. Deployment of on-site monitoring equipment.

[0036] Monitoring sensors are buried at different locations inside the dam body, video surveillance modules are deployed at set positions on the dam body, and drone hangars are deployed around the reservoir dam.

[0037] 2. When a vibration sensor detects vibration caused by termite activity, if the vibration sensor is located within the video monitoring range of the video monitoring module, the video monitoring module within the video monitoring range where the vibration sensor is located is activated to take pictures, or the drone monitoring module is used to take pictures of the area where the vibration sensor is located.

[0038] Specifically, when the vibration sensor detects vibrations caused by termite activity, the Hall sensor attached to the bait stick will send an alarm signal and upload it to the monitoring center platform. When the monitoring center platform receives the alarm signal sent by the Hall sensor, if the vibration sensor is within the video monitoring range of the video monitoring module, the video monitoring module within the video monitoring range of the vibration sensor can be activated to focus on taking pictures, thereby obtaining the activity patterns and number of termites, and using the AI ​​model to identify and analyze the nest location of the captured pictures. The drone monitoring module can also be used to take pictures of the area where the vibration sensor is located, and the key areas around the vibration sensor can be reviewed, so as to use the AI ​​model to analyze the captured pictures and / or thermal infrared images to obtain the activity patterns and number of termites and identify the location and size of the termite nest. Preferably, when the vibration sensor is within the video monitoring range of the video monitoring module, the video monitoring module within the video monitoring range where the vibration sensor is located is preferentially activated to take pictures.

[0039] If the vibration sensor is not located within the video monitoring range of any video monitoring module, the drone monitoring module is used to shoot the area where the vibration sensor is located.

[0040] 3. Use the drone monitoring module to regularly take aerial photos of the dam to obtain dam surface images and / or thermal infrared images. Use the AI ​​model to process the obtained dam surface images and / or thermal infrared images to identify the location and size of termite nests.

[0041] For example, if weather conditions permit, dam cruise photography can be carried out at the same time every week, with a flight altitude of 10m and a flight speed of 8m / s, so that intensive monitoring can be carried out during the peak period of termite activity. Preferably, the drone is equipped with both a camera and a thermal imager to obtain dam surface images and thermal infrared images. The collected dam surface images and thermal infrared images are preprocessed and pixel-level fused to generate multimodal feature data containing texture features and temperature data. The multimodal data is input into the trained AI model to obtain the location and size of the termite nest. The AI ​​model is constructed by combining target monitoring and semantic segmentation models with morphological feature knowledge, and is trained based on a manually annotated nest training set. The aerial images and thermal infrared images transmitted back by the drone monitoring module in real time are preprocessed and input into the trained AI model for detection. After the nest is detected, the detection results are mapped to the GIS system, and the longitude and latitude coordinates are marked on the map to identify the location and size of the termite nest.

[0042] 4. Determine termite nests, numbers, and activities.

[0043] The location, number and activity of termites are determined based on the data captured by the video surveillance module or the data captured by the drone monitoring module.

[0044] Method implementation The specific implementation process of the intelligent monitoring and early warning method for dam termites of the present invention has been described in detail in the system implementation method and will not be repeated here.

Claims

1. A dam termite intelligent monitoring and early warning method, characterized in that: include: Monitoring sensors are embedded at different locations within the dam, and video surveillance modules are deployed at designated locations within the dam. The monitoring sensors include vibration sensors for real-time monitoring of vibrations caused by termite activity. When a vibration sensor detects vibration caused by termite activity, if the vibration sensor is within the video surveillance range of a video surveillance module, the video surveillance module within which the vibration sensor is located is activated to take a picture, or a drone monitoring module is used to take a picture of the area where the vibration sensor is located; if the vibration sensor is not within the video surveillance range of any video surveillance module, a drone monitoring module is used to take a picture of the area where the vibration sensor is located; the drone monitoring module includes a drone equipped with a camera and / or a thermal imager; The location, number and activity of termites are determined based on the data captured by the video monitoring module or the data captured by the drone monitoring module.

2. The intelligent monitoring and early warning method for dam termites according to claim 1 is characterized in that: The monitoring sensor also includes a temperature and humidity sensor for monitoring temperature and humidity changes caused by termite activities. The temperature and humidity changes caused by termite activities are used to verify the confirmed termite nests, number and activities.

3. The intelligent monitoring and early warning method for dam termites according to claim 1 or 2, characterized in that: The method also includes using a drone monitoring module to regularly take aerial photos of the dam to obtain dam surface images and / or thermal infrared images, and using an AI model to process the obtained dam surface images and / or thermal infrared images to identify the location and size of termite nests.

4. The intelligent monitoring and early warning method for dam termites according to claim 3 is characterized in that: The drone monitoring module is used to regularly take aerial photos of the dam to obtain dam surface images and thermal infrared images. The dam surface images and thermal infrared images are preprocessed and fused at the pixel level to generate multimodal feature data containing texture features and temperature data. The multimodal data is input into the trained AI model to obtain the location and scale of termite nests.

5. The intelligent monitoring and early warning method for dam termites according to claim 2 is characterized in that: When the number of termites or the vibration frequency caused by termite activity or the temperature and humidity changes caused by termite activity exceed the corresponding warning threshold, a warning message is also issued; the warning information is issued in the form of sound and light alarms and / or SMS notifications and / or monitoring center platform notifications.

6. An intelligent monitoring and early warning system for termites in dams, comprising an unmanned aerial vehicle (UAV) monitoring module, wherein the UAV monitoring module comprises an UAV equipped with a camera and / or a thermal imager; characterized in that: The system also includes monitoring sensors, video monitoring modules and data analysis modules. Each monitoring sensor is buried at a different position inside the dam body, and each video monitoring module is deployed at a set position on the dam body. The monitoring sensor includes a vibration sensor, which is used to monitor vibrations caused by termite activity in real time. When a vibration sensor detects vibrations caused by termite activity, if the vibration sensor is within the video monitoring range of the video monitoring module, the video monitoring module within the video monitoring range of the vibration sensor is activated to take a picture, or a drone monitoring module is used to take a picture of the area where the vibration sensor is located. If the vibration sensor is not within the video monitoring range of any video monitoring module, the drone monitoring module is used to take a picture of the area where the vibration sensor is located. The data analysis module is used to determine the nests, number and activities of termites based on the data captured by the video monitoring module or the data captured by the drone monitoring module.

7. The intelligent monitoring and early warning system for termites in dams according to claim 6 is characterized in that: The monitoring sensor also includes a temperature and humidity sensor for monitoring temperature and humidity changes caused by termite activities. The temperature and humidity changes caused by termite activities are used to verify the confirmed termite nests, number and activities.

8. The intelligent monitoring and early warning system for termites in dams according to claim 6 or 7, characterized in that: The drone monitoring module is also used to regularly take aerial photos of the dam to obtain dam surface images and / or thermal infrared images, which are used to identify the location and size of termite nests after analysis.

9. The intelligent monitoring and early warning system for termites in dams according to claim 6 or 7, characterized in that: An AI analysis module is also provided in the video monitoring module and the drone monitoring module. The AI ​​analysis module stores a trained AI model. The video monitoring module uses the stored AI model locally to analyze the captured data to obtain termite activity and quantity; the drone monitoring module uses the stored AI model locally to analyze the captured data to obtain termite activity and nests; the video monitoring module or the drone monitoring module sends the data processed by the AI ​​analysis module to the data analysis module. The data analysis module comprehensively determines the termite nests, quantity and activity based on the data processed by the AI ​​analysis module and the monitoring data of the vibration sensor.

10. The intelligent monitoring and early warning system for termites in dams according to claim 6 or 7, characterized in that: The data analysis module is set on the monitoring center platform. The video monitoring module or the drone monitoring module uploads the data it shoots to the monitoring center platform. The data analysis module stores a trained AI model. The AI ​​model is used to analyze the data shot by the video monitoring module or the drone monitoring module, and comprehensively determine the termite nests, number and activities in combination with the monitoring data of the vibration sensor.

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