Satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction

Abstract

The invention belongs to the technical field of engineering construction, and particularly relates to a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction, and the system comprises a region remote sensing module which carries out remote sensing modeling on an engineering construction region through satellite remote sensing to form a remote sensing picture; pictures and time when a vehicle passes through a certain road are recorded, pictures of the road are shot periodically, obstacle recognition is carried out on the pictures of the road through the recognition module to detect whether an obstacle exists on the road or not, and when the recognition module recognizes the obstacle in the pictures, the vehicle falling off the obstacle needs to be traced, so that the vehicle can be traced. A driver of the vehicle is reminded through the traveling data recorder, or personnel responsible for loading objects on the transport vehicle are reminded, related personnel are timely notified to remind and clean obstacles, and transport vehicles which need to pass through the road subsequently are reminded through the traveling data recorder. Therefore, obstacles appearing on the road in the construction area can be handled in time, and follow-up passing vehicles can be reminded.

Description

Technical Field

[0001] The invention relates to the technical field of engineering construction, and in particular to a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction. Background Art

[0002] The satellite remote sensing automated dynamic monitoring system for engineering construction uses high-resolution satellite images and advanced image processing and machine learning technologies to monitor the construction progress of engineering projects, as well as changes in building areas, vegetation areas, and water areas of environmental protection projects, to protect the construction environment.

[0003] At present, during the construction process, a lot of dust will be raised when vehicles are driving in the construction area. When vehicles transport objects, the unreasonable speed or object stacking height will cause objects to fall and form obstacles, especially stones, which will affect driving safety. At the same time, if there is no planned road in the construction area, safety accidents are prone to occur. Therefore, most projects will plan vehicle routes during construction, which can reduce the dust caused by vehicles passing through dusty areas and reduce the occurrence of safety accidents. However, some drivers' vehicles will not drive according to the prescribed trajectory and exceed the speed limit in the construction area, and it is difficult to supervise. Obstacles falling from vehicles on the road will affect vehicle safety from time to time. At the same time, a large amount of waste will be generated during the construction process. The classified stacking of waste can improve resource utilization. However, some transport vehicle drivers do not stack waste according to the type of waste they transport. The mixing of waste will greatly increase the difficulty of waste recycling.

[0004] Therefore, it is necessary to provide a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction to solve the above technical problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction, which solves the safety problem of irregular vehicle driving in the construction area and strengthens resource recovery management.

[0006] The present invention provides a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction, which is characterized by:

[0007] Regional remote sensing module: The remote sensing modeling of the construction area is carried out through satellite remote sensing to form a remote sensing picture. After the construction area, vegetation area and water area in the remote sensing picture are divided into regions, each transportation road, unloading location, waste location and construction location is divided into regions, and the waste location is further divided according to the waste type;

[0008] Road monitoring module: cameras are installed on each transport road, unloading location, waste location and construction location in the construction area, and the unloading location, waste location and construction location are photographed by the cameras to form corresponding pictures;

[0009] Driving track module: Install driving recorders on transport vehicles and construction vehicles entering the construction area. The driving recorders are activated when the transport vehicles and construction vehicles enter the construction area to record their driving tracks and speeds in the construction area.

[0010] Identification module: collects image data, processes the images, and then performs identification analysis; identifies and analyzes remote sensing images, images of unloading locations, images of waste locations, images of construction locations, and images of vehicle driving trajectories;

[0011] Identify and mark the range of building areas, vegetation areas and water areas in pictures;

[0012] Mark the scope of the pictures of the unloading location, waste location and construction location;

[0013] Perform obstacle recognition on road images;

[0014] Identify the transport track in the transport vehicle's driving track image, and identify the construction track in the construction vehicle's driving track image;

[0015] Supervision module: Monitor the road pictures taken by transport vehicles and construction vehicles after they pass through the road and the vehicles passing through. Monitor the time point when obstacles appear in the road pictures and the vehicles passing through the road at that time. Periodically monitor the range of materials in the pictures of unloading locations, waste locations, and construction locations. Periodically monitor the range of building areas, vegetation areas, and water areas in remote sensing pictures. Monitor the driving speed of transport vehicles and construction vehicles.

[0016] Analogy module: The analogy module draws analogies with the pictures of periodic supervision in the supervision module;

[0017] Compare road photos of transport vehicles or construction vehicles passing through the same road before and after to see if there are any additional obstacles;

[0018] Compare the size of the materials in the pictures of the unloading location, the waste location, and the construction location before and after the time to see whether the size of the waste has increased;

[0019] Compare the sizes of building areas, vegetation areas and water areas in remote sensing images before and after the time period to see whether the size of waste has increased;

[0020] Compare the driving trajectory images of construction vehicles and transport vehicles to see if there are any abnormalities in the driving trajectory;

[0021] Control platform: The regional remote sensing module periodically takes remote sensing images of the construction area and uploads them to the control platform. The road supervision module uploads images of various transportation roads, unloading locations, waste locations and construction locations to the control platform. The driving trajectory module uploads records of the driving trajectories and driving speeds of transportation vehicles and construction vehicles in the construction area to the control platform. The supervision module of the control platform completes the supervision of various types of images, and the analogy module of the control platform compares the images to determine image changes.

[0022] Preferably, the camera installation points should ensure full coverage of all key roads and locations, so that the camera can capture the situation of transport vehicles and construction vehicles passing through the roads, and the camera should have an automatic start function, which can automatically start and start shooting when a vehicle is detected passing by.

[0023] Preferably, the images of the unloading location, the waste location and the construction location are range-marked by the recognition module;

[0024] Identify the images taken at the unloading location, waste location, and construction location. The recognition module identifies objects at the unloading location based on the shape of the building materials.

[0025] The recognition module combines the images captured by the road monitoring module’s camera with the remote sensing images from the regional remote sensing module, and uses image segmentation and feature extraction algorithms to identify the scope and height changes of the construction location;

[0026] The recognition module identifies the type of waste at the waste location by combining the images captured by the camera of the road monitoring module and the remote sensing images of the regional remote sensing module with colors.

[0027] Preferably, the recognition module recognizes obstacles in the road image, associates the time point of the obstacle in the road image with the vehicle passing through the road at that time point, and notifies subsequent vehicles that need to pass through the road;

[0028] When the size of objects in the pictures of the unloading location, the waste location, and the construction location changes or exceeds the preset range, an early warning message is sent to the management personnel through the control platform, prompting them to conduct inspection and processing.

[0029] Preferably, firstly, regional image analogy is performed in the analogy module, and the ranges of building areas, vegetation areas and water areas are extracted from the remote sensing images. Then, range analogy is performed, and two groups of remote sensing images are compared in chronological order to analyze the range changes of these areas. Through analogy analysis, the unnecessary occupation of vegetation areas or water areas is discovered, and corresponding regulatory measures are taken. Through the changes in the building area, the progress of the project in the construction area can be understood.

[0030] Preferably, the driving trajectory is first compared in the analogy module, and the actual driving trajectory of the construction vehicle and the transport vehicle is compared with the predetermined route to form anomaly detection. The trajectory similarity calculation and trajectory clustering analysis methods are used to detect whether the driving trajectory is abnormal. When an abnormal trajectory is detected, the system of the control platform automatically issues a warning message and reminds the driver to correct the driving direction through the driving recorder.

[0031] Preferably, the analogy module first compares road pictures by comparing road pictures of transport vehicles or construction vehicles that pass the same road before and after to check whether there are any additional obstacles. When an obstacle is detected, the system of the control platform automatically issues a warning message, and reminds subsequent drivers who pass the road through the driving recorder, and reminds the driver of the vehicle that spilled the obstacle to pay attention to the amount of cargo.

[0032] Preferably, image segmentation is performed on pictures of the unloading position, waste position and construction position to extract the range of the material. The size of the material range is calculated by range calculation, and compared with historical data, and the change result is given by an analogy module.

[0033] Compared with the related art, the satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction provided by the present invention has the following beneficial effects:

[0034] 1. The present invention marks the roads in the construction area where transport vehicles can travel, and sets the numerical range of the driving speed of transport vehicles entering the construction area. The driving trajectory and driving speed of the transport vehicles are supervised by the supervision module of the control platform. The driving trajectory is compared by the analogy module of the control platform, and the actual driving trajectory of the construction vehicle and the transport vehicle is compared with the predetermined route to form an abnormality detection. When an abnormal trajectory is detected, the system of the control platform automatically sends out an early warning message, and reminds the driver to correct the driving direction through the driving recorder. When the transport vehicle exceeds the speed limit, the driving recorder can complete the detection of the vehicle's driving speed, and the driving recorder reminds the driver and reports the speeding behavior of the vehicle at the same time, which is conducive to behavioral constraints on vehicles in the construction area, avoiding vehicles from causing a large amount of dust when driving on non-roads, and avoiding safety risks.

[0035] 2. The present invention records the images and time of vehicles passing a certain road, and takes pictures of the road periodically. The recognition module performs obstacle recognition on the road images to detect whether there are obstacles on the road. When the recognition module recognizes an obstacle in the image, it is necessary to trace the vehicle that dropped the obstacle, and remind the driver of the vehicle through the driving recorder, or remind the person responsible for loading the transport vehicle, and promptly notify the relevant personnel to remind and clear the obstacles. The driving recorder is used to remind the transport vehicles that need to pass through the road in the future, which is conducive to timely handling of obstacles on the road in the construction area and reminding subsequent passing vehicles.

[0036] 3. The present invention divides each construction area into regions through the remote sensing images of the regional remote sensing module of the control platform, especially the waste location needs further division, and is divided again according to the type of waste, and wood, soil and rock are placed in different regions. The waste transported by the transport vehicle is identified through the identification module. When the type of waste transported by the transport vehicle is different from the type of the area where it is about to unload, the control platform promptly notifies the transport vehicle to change the unloading area through the driving recorder, or the driver confirms the waste type for the second time, that is, the identification module identifies the error, which is conducive to stacking the waste according to type and is conducive to resource recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of the control flow of a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction provided by the present invention;

[0038] Figure 2 A schematic diagram of a specific embodiment 2 of a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction provided by the present invention;

[0039] Figure 3 A schematic diagram of a specific embodiment 3 of a satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction provided by the present invention;

[0040] Figure 4 A schematic diagram of a specific embodiment 4 of a satellite remote sensing automated dynamic monitoring system for electric power environmental protection engineering construction provided by the present invention. DETAILED DESCRIPTION

[0041] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the examples described are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1

[0043] A satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction:

[0044] Regional remote sensing module: remote sensing modeling of the construction area is carried out through satellite remote sensing to form a remote sensing picture. After dividing the construction area, vegetation area and water area in the remote sensing picture, the transportation roads, unloading locations, waste locations and construction locations are divided into regions. The waste locations are further divided according to the waste type.

[0045] The image data of the construction area is obtained through high-resolution satellite remote sensing technology, and the collected remote sensing images are preprocessed, including radiation correction, geometric correction, atmospheric correction, etc., to eliminate or reduce noise and errors in the image and improve image quality.

[0046] The preprocessed images are modeled to form remote sensing pictures of the construction area, which includes steps such as feature extraction, image segmentation, and target recognition in order to extract useful information from the images.

[0047] It requires the use of GIS technology, visualization tools and other means to present the monitoring results in an intuitive and vivid way.

[0048] The waste location needs to be further divided according to the type of waste, and wood, soil and rocks should be placed in different areas.

[0049] Road supervision module: cameras are set up on various transport roads as well as unloading locations, waste locations and construction locations in the construction area. When transport vehicles and construction vehicles pass through the roads, the cameras are activated to form road pictures of the roads, and the unloading locations, waste locations and construction locations are photographed through the cameras to form corresponding pictures.

[0050] The camera installation points should ensure that all key roads and locations are fully covered so as to capture the situations when transport vehicles and construction vehicles pass through the roads. The cameras should also have an automatic start function so that they can automatically start and start filming when a vehicle is detected passing by.

[0051] The images captured by the camera are transmitted to the control platform in real time through the network, and the control platform needs to cooperate in establishing a database to save the image data.

[0052] The transmitted images are preprocessed, including denoising, enhancing analogy and other operations to improve image quality, and image recognition technology is used to extract useful information from the images, such as vehicle type, license plate number, driving speed, etc.

[0053] Driving track module: Install driving recorders on transport vehicles and construction vehicles entering the construction area. The driving recorders are activated when the transport vehicles and construction vehicles enter the construction area to record their driving tracks and speeds in the construction area.

[0054] Install a driving recorder with GPS positioning function on the transport vehicles and construction vehicles entering the construction area. When the vehicle enters the construction area, it can automatically start and start recording.

[0055] The images and GPS data captured by the driving recorder are transmitted to the control platform in real time through the network to form a driving trajectory map. The GPS data is used to reconstruct the driving trajectory of the vehicle in the construction area, which is achieved through the trajectory reconstruction algorithm of professional GIS software.

[0056] According to the timestamp and location information in the GPS data, the instantaneous speed and average speed of the vehicle at each moment are calculated to understand the driving status of the vehicle and whether there is speeding behavior.

[0057] Identification module: collects image data, processes the images, and then performs identification analysis. It performs identification analysis on remote sensing images, images of unloading locations, images of waste locations, images of construction locations, and images of vehicle driving trajectories.

[0058] Identify and mark the ranges of built-up areas, vegetation areas, and water areas in images.

[0059] Mark the scope of the pictures of the unloading location, waste location and construction location.

[0060] Perform obstacle recognition on road images.

[0061] The transport track is identified in the transport vehicle's driving track picture, and the construction track is identified in the construction vehicle's driving track picture.

[0062] The recognition module needs to pre-process the collected image data, including denoising, enhancing analogy, geometric correction and other operations, in order to improve image quality and reduce errors in subsequent processing.

[0063] The building area, vegetation area and water area in the remote sensing image are divided into regions by using remote sensing image processing software or developed algorithms.

[0064] The original remote sensing images need to be calibrated by radiation and corrected by atmosphere to eliminate the influence caused by sensors and atmospheric conditions. The Normalized Difference Vegetation Index (NDVI) is used to identify vegetation areas, and water indices such as the Modified Normalized Difference Water Index (MNDWI) are used to identify water areas. The above two indices are calculated by comparing the reflectivity of different bands and can effectively distinguish different types of land objects.

[0065] Dividing the image into multiple homogeneous patches and then classifying them based on spatial information such as the size, shape, and texture of the patches can overcome the "salt and pepper phenomenon" in pixel-based classification methods and improve classification accuracy.

[0066] The pictures of the unloading location, waste location and construction location are range marked, which helps to understand the incoming materials and the progress of the construction location.

[0067] The pictures taken at the unloading location, waste location and construction location are identified. Bags of cement, strips of steel bars and blocks of bricks are piled at the unloading location. Object recognition is performed through shape. The findContours function is used to find and extract the contours in the image, and then the shapes they represent are judged according to various conditions and rules to complete the identification of construction materials at the unloading location.

[0068] The construction location is identified by combining the images captured by the camera of the road supervision module and the remote sensing images of the regional remote sensing module, so that changes in the range and height of the construction location can be identified.

[0069] Extract building patches from remote sensing images. The features of remote sensing images are learned through encoding and decoding parts, and the probability values ​​of building targets are output. For construction images, image segmentation and feature extraction algorithms can be used to identify feature information such as edges and corners of buildings.

[0070] The preprocessed remote sensing images are divided into different construction stages, such as foundation stage, construction stage, and completed stage. Then, the change detection algorithm is used to compare the differences between the images of each stage to identify changes in the construction scope.

[0071] The detection of height changes can be achieved by analyzing the changes in the length and direction of the building's shadow during construction, and combining the sun's position and terrain information to calculate the building's height.

[0072] The waste locations need to be divided by color through remote sensing images. During the construction process, the waste needs to be classified and placed. For example, gray and white colors are mostly stones or building wall waste, while soil is mostly black, dark brown and red, and wood is mostly light yellow, orange to dark brown, and most of them are green. By classifying and placing, different types of waste can be recycled and reused more effectively. For example, waste concrete can be crushed and used as recycled aggregate for new concrete production. Waste formwork, waste bricks and tiles can also be reused after processing. This not only reduces the consumption of new resources, but also reduces the environmental pressure caused by waste landfills.

[0073] Obstacle recognition is performed on road images to detect whether there are obstacles on the road. It is mainly used to identify whether transport vehicles have dropped objects, such as stones or waste concrete.

[0074] The trajectories in the transport vehicle's driving trajectory picture are identified to determine the transport trajectory, and the trajectories in the construction vehicle's driving trajectory picture are identified to determine the construction trajectory.

[0075] Supervision module: supervise the correspondence between road pictures taken after transport vehicles and construction vehicles pass through the road, correspond the time point when obstacles appear in the road pictures and the vehicles passing through the road at that time point, periodically supervise the range of materials in the pictures of unloading locations, pictures of waste locations, and pictures of construction locations, periodically supervise the range of building areas, vegetation areas, and water areas in remote sensing pictures, and supervise the driving speed of transport vehicles and construction vehicles.

[0076] The time point of the obstacle in the road image is associated with the vehicles passing through the road at that time point to determine the vehicles that may be affected.

[0077] That is, identify the vehicle that has dropped the obstacle, remind the driver of the vehicle through the driving recorder, or remind the person responsible for loading the transport vehicle, and promptly notify the relevant personnel to remind and clear the obstacle, and use the driving recorder to remind subsequent transport vehicles that need to pass through the road.

[0078] The size of the objects at the unloading, waste and construction locations is compared with the periodically taken pictures to analyze the changing trend of the object range.

[0079] Compare the building area, vegetation area and water area in the remote sensing images with historical data to analyze regional changes;

[0080] If the building area is being constructed, the building area should be gradually expanded; if it is being demolished, the building area should be gradually reduced;

[0081] Vegetation areas and water areas are adjusted according to the planning scheme. If the vegetation area is expanded or reduced in the planning scheme, the picture of the vegetation area will also change accordingly, and the same applies to the water area.

[0082] Based on the GPS data of transport vehicles and construction vehicles, the vehicle's driving speed is calculated and compared with the preset speed threshold to determine whether there is speeding behavior.

[0083] The speed of transport vehicles in the construction area should be between 10-30 kilometers per hour. Exceeding 30 kilometers per hour is considered speeding. The speed limit for construction vehicles in the construction area usually does not exceed 10-20 kilometers per hour.

[0084] When the size of objects in the pictures of the unloading location, the waste location, and the construction location changes or exceeds the preset range, an early warning message is sent to the management personnel through the control platform, prompting them to conduct inspection and processing.

[0085] Analogy module: The analogy module draws analogies with the pictures of periodic supervision in the supervision module;

[0086] Compare road photos of transport vehicles or construction vehicles passing through the same road before and after to see if there are any additional obstacles;

[0087] Compare the size of the materials in the pictures of the unloading location, the waste location, and the construction location before and after the time to see whether the size of the waste has increased;

[0088] Compare the sizes of building areas, vegetation areas and water areas in remote sensing images before and after the time period to see whether the size of waste has increased;

[0089] Compare the driving trajectory images of construction vehicles and transport vehicles to see if there are any abnormalities in the driving trajectory.

[0090] Road obstacle detection analogy:

[0091] Image registration is used to register the images that pass through the same road one after the other to ensure that the two images are aligned in space.

[0092] By using methods such as image difference and change vector analysis, changes in obstacles on the road can be detected.

[0093] Based on the detection results, determine whether to add new obstacles.

[0094] Material range change detection analogy:

[0095] Image segmentation is performed on the pictures of the unloading location, waste location and construction location to extract the range of the materials.

[0096] By calculating the range, we can calculate the size of the material range and compare it with the historical data, and then conduct change analysis to analyze the changing trend of the material range and determine its changing situation.

[0097] For example, the objects at the unloading position mainly refer to construction materials, such as concrete materials, steel materials, etc. If the range of objects at the unloading position is reduced and exceeds the preset range, it means that the construction progress is fast, or if the materials are not supplied in time, the range of objects at the material position is expanded and exceeds the preset range, which means that the construction progress is slow;

[0098] The objects at the waste location mainly refer to waste concrete, stones and soil, etc. If the range of objects at the waste location shrinks and exceeds the preset range, it means that the waste cleaning has entered the final stage and can be checked by referring to the construction progress. If the range of objects at the waste location expands and exceeds the preset range, it means that the waste is not transported out in time and coordination is needed;

[0099] Objects at the construction location mainly refer to buildings under construction or buildings under demolition. First of all, it is necessary to determine the construction nature of the construction location. If the range of objects at the construction location shrinks and exceeds the preset range, only in the case of demolition will the construction location shrink, which means that the demolition work is fast. If the range of objects at the construction location expands and exceeds the preset range, it means that the construction progress is fast. The expansion speed of the construction object range can reflect the construction progress to a certain extent.

[0100] Analogy between zoning and change monitoring:

[0101] First, regional image analogy is performed in the analogy module. The scope of the building area, vegetation area and water area is extracted from the remote sensing image. Then, scope analogy is performed. Two sets of remote sensing images are compared in chronological order. The scope changes of these areas are analyzed. Through analogy analysis, the unnecessary occupation of vegetation areas or water areas is discovered, and corresponding regulatory measures are taken. Through the changes in the building area, the progress of the project in the construction area can be understood.

[0102] Anomaly detection based on driving trajectory analogy:

[0103] First, the analogy module compares the driving trajectories of construction vehicles and transport vehicles with the planned routes to form anomaly detection. It uses methods such as trajectory similarity calculation and trajectory clustering analysis to detect whether the driving trajectory is abnormal. When an abnormal trajectory is detected, the system of the control platform automatically issues a warning message and reminds the driver to correct the driving direction through the driving recorder.

[0104] The driving recorder can be used to detect the vehicle's speed. When the vehicle's speed exceeds the threshold set by the system in the control platform, the driving recorder reminds the driver and reports the vehicle's speeding behavior.

[0105] Obstacle detection using road images:

[0106] First, the analogy module compares road images, comparing road photos of transport vehicles or construction vehicles passing through the same road to see if there are any additional obstacles. When an obstacle is detected, the system of the control platform automatically issues a warning message, and reminds subsequent drivers passing through the road through the driving recorder, and reminds the driver of the vehicle that spilled the obstacle to pay attention to the amount of cargo.

[0107] Control platform: The regional remote sensing module periodically takes remote sensing images of the construction area and uploads them to the control platform. The road supervision module uploads images of various transportation roads, unloading locations, waste locations and construction locations to the control platform. The driving trajectory module uploads the driving trajectory and driving speed records of transportation vehicles and construction vehicles in the construction area to the control platform. The supervision module of the control platform completes the supervision of various types of images. The control platform extracts key features from the image, such as road edges, material boundaries, building outlines, etc., to prepare for subsequent analogy analysis. The analogy module of the control platform compares the images to determine image changes.

[0108] The system can realize real-time monitoring of the construction area and display the monitoring results to managers in a visual manner. Managers can view information such as road obstacles, object range changes, area division results, and vehicle speed through the system interface of the control platform. Specific embodiment 2

[0110] When a transport vehicle enters the construction area for the first time, a driving recorder should be installed on the transport vehicle, and the driving recorder number should be associated with the license plate number of the transport vehicle in the system of the control platform;

[0111] The driving track and speed of the transport vehicle after entering the construction area are recorded by a driving recorder;

[0112] First, it is necessary to mark the roads in the construction area where transport vehicles can travel on the control platform, and set the driving speed range for transport vehicles entering the construction area. Through the supervision module of the control platform, the driving trajectory and speed of the transport vehicles can be supervised.

[0113] Through the analog module of the control platform, the driving trajectory is compared, and the actual driving trajectory of construction vehicles and transport vehicles is compared with the predetermined route to form anomaly detection. When an abnormal trajectory is detected, the control platform system will automatically issue a warning message and remind the driver to correct the driving direction through the driving recorder.

[0114] When a transport vehicle exceeds the speed limit, the driving recorder will detect the vehicle's speed, remind the driver, and report the vehicle's speeding behavior.

[0115] The control platform can directly view the speeding location, speed, time and vehicle license plate. Specific embodiment 3

[0117] Cameras should be installed on various transport roads in the construction area. The installation points of the cameras should ensure that all key roads and locations are fully covered to record road conditions when transport vehicles and construction vehicles pass through the roads. The cameras should have an automatic start function, which means they can automatically start and start filming when a vehicle passes by.

[0118] The images and time of vehicles passing through a certain road are recorded, and pictures of the road are taken periodically. The road pictures are then identified by the recognition module to detect obstacles on the road. This is mainly used to identify whether transport vehicles have dropped objects, such as stones or waste concrete.

[0119] When the recognition module identifies an obstacle in the image, it is necessary to trace the vehicle that dropped the obstacle, remind the driver of the vehicle through the driving recorder, or remind the person responsible for loading the transport vehicle, and promptly notify the relevant personnel to remind and clear the obstacle, and use the driving recorder to remind subsequent transport vehicles that need to pass through the road. Specific embodiment 4

[0121] Regardless of whether the construction area requires the demolition of buildings, area cleanup is required before construction begins, which brings in waste materials such as trees, soil, and rocks.

[0122] If building demolition is required, there will also be concrete waste, bricks, wooden boards, etc.

[0123] Through the regional remote sensing module of the control platform, remote sensing images are used to divide each construction area into regions, especially the waste locations need further division.

[0124] The waste is divided again according to its type, and wood, soil and rocks are placed in different areas. The waste transported by the transport vehicle is identified through the identification module.

[0125] When the category of waste transported by the transport vehicle is different from the category of the area where it is about to unload, the control platform will promptly notify the transport vehicle to change the unloading area through the driving recorder.

[0126] Alternatively, the driver can reconfirm the waste type, report the recognition error of the identification module through the driving recorder, and continue to complete the unloading to prevent the recognition error of the identification module.

[0127] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction, characterized in that: Regional remote sensing module: The remote sensing modeling of the construction area is carried out through satellite remote sensing to form a remote sensing picture. After the construction area, vegetation area and water area in the remote sensing picture are divided into regions, each transportation road, unloading location, waste location and construction location is divided into regions, and the waste location is further divided according to the waste type; Road monitoring module: cameras are installed on each transport road, unloading location, waste location and construction location in the construction area, and the unloading location, waste location and construction location are photographed by the cameras to form corresponding pictures; Driving track module: Install driving recorders on transport vehicles and construction vehicles entering the construction area. The driving recorders are activated when the transport vehicles and construction vehicles enter the construction area to record their driving tracks and speeds in the construction area. Identification module: collects image data, processes the images, and then performs identification analysis; identifies and analyzes remote sensing images, images of unloading locations, images of waste locations, images of construction locations, and images of vehicle driving trajectories; Identify and mark the range of building areas, vegetation areas and water areas in pictures; Mark the scope of the pictures of the unloading location, waste location and construction location; Perform obstacle recognition on road images; Identify the transport track in the transport vehicle's driving track image, and identify the construction track in the construction vehicle's driving track image; Supervision module: Monitor the road pictures taken by transport vehicles and construction vehicles after they pass through the road and the vehicles passing through. Monitor the time point when obstacles appear in the road pictures and the vehicles passing through the road at that time. Periodically monitor the range of materials in the pictures of unloading locations, waste locations, and construction locations. Periodically monitor the range of building areas, vegetation areas, and water areas in remote sensing pictures. Monitor the driving speed of transport vehicles and construction vehicles. Analogy module: The analogy module draws analogies with the pictures of periodic supervision in the supervision module; Compare road photos of transport vehicles or construction vehicles passing through the same road before and after to see if there are any additional obstacles; Compare the size of the materials in the pictures of the unloading location, the waste location, and the construction location before and after the time to see whether the size of the waste has increased; Compare the sizes of building areas, vegetation areas and water areas in remote sensing images before and after the time period to see whether the size of waste has increased; Compare the driving trajectory images of construction vehicles and transport vehicles to see if there are any abnormalities in the driving trajectory; Control platform: The regional remote sensing module periodically takes remote sensing images of the construction area and uploads them to the control platform. The road supervision module uploads images of various transportation roads, unloading locations, waste locations and construction locations to the control platform. The driving trajectory module uploads records of the driving trajectories and driving speeds of transportation vehicles and construction vehicles in the construction area to the control platform. The supervision module of the control platform completes the supervision of various types of images, and the analogy module of the control platform compares the images to determine image changes.

2. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 1 is characterized in that: The camera installation points should ensure full coverage of all key roads and locations so that the camera can capture the situations of transport vehicles and construction vehicles passing through the roads. The camera should also have an automatic start function, which allows it to automatically start and start filming when a vehicle is detected passing by.

3. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 1 is characterized in that: Use the recognition module to mark the range of the images of the unloading location, waste location, and construction location; Identify the images taken at the unloading location, waste location, and construction location. The recognition module identifies objects at the unloading location based on the shape of the building materials. The recognition module combines the images captured by the road monitoring module’s camera with the remote sensing images from the regional remote sensing module, and uses image segmentation and feature extraction algorithms to identify the scope and height changes of the construction location; The recognition module identifies the type of waste at the waste location by combining the images captured by the camera of the road monitoring module and the remote sensing images of the regional remote sensing module with colors.

4. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 1 is characterized in that: The recognition module identifies obstacles in the road image, associates the time point of the obstacle in the road image with the vehicle passing through the road at that time point, and notifies subsequent vehicles that need to pass through the road; When the size of objects in the pictures of the unloading location, the waste location, and the construction location changes or exceeds the preset range, an early warning message is sent to the management personnel through the control platform, prompting them to conduct inspection and processing.

5. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 1 is characterized in that: First, regional image analogy is performed in the analogy module. The scope of the building area, vegetation area and water area is extracted from the remote sensing image. Then, scope analogy is performed. Two sets of remote sensing images are compared in chronological order. The scope changes of these areas are analyzed. Through analogy analysis, the unnecessary occupation of vegetation areas or water areas is discovered, and corresponding regulatory measures are taken. Through the changes in the building area, the progress of the project in the construction area can be understood.

6. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 5 is characterized in that: First, the driving trajectory is compared in the analogy module. The actual driving trajectory of construction vehicles and transport vehicles is compared with the predetermined route to form anomaly detection. The trajectory similarity calculation and trajectory clustering analysis methods are used to detect whether the driving trajectory is abnormal. When an abnormal trajectory is detected, the system of the control platform automatically issues a warning message and reminds the driver to correct the driving direction through the driving recorder.

7. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 6 is characterized in that: First, the analogy module compares road images by comparing road photos of transport vehicles or construction vehicles passing through the same road to see if there are any additional obstacles. When an obstacle is detected, the system of the control platform automatically issues a warning message, and reminds subsequent drivers passing through the road through the driving recorder, and reminds the driver of the vehicle that spilled the obstacle to pay attention to the amount of cargo.

8. The satellite remote sensing automatic dynamic monitoring system for electric power environmental protection engineering construction according to claim 7 is characterized in that: Through image segmentation, the images of the unloading position, waste position and construction position are segmented to extract the range of the material. The size of the material range is calculated through range calculation, and compared with historical data. The change results are given through the analogy module.

Images