Solid waste collection and transportation vehicle dynamic route optimization management method and system

Abstract

The invention relates to the technical field of vehicle route management systems, in particular to a solid waste collection and transportation vehicle dynamic route optimization management method and system which comprises a position acquisition unit, an analysis and judgment unit, a coordinate recognition unit and a solid waste collection and transportation unit. Sensor nodes are deployed at garbage can placement points of all parks to construct a wireless sensor network, the positions of garbage cans are obtained, the loading degree of the garbage cans is judged through infrared emission devices and CCD calibration devices of the sensor nodes, and finally solid waste images are collected through cameras right above the garbage cans. And the command center formulates a solid waste transportation route according to the solid waste position coordinates, the garbage can loading degree and the residual load capacity of the solid waste collection and transportation vehicle, so that the solid waste collection and transportation efficiency is improved, the cost is reduced, and the environmental pollution is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle route management systems, and in particular to a method and system for optimizing the dynamic routes of solid waste collection and transportation vehicles. Background Art

[0002] The route optimization management technology for solid waste collection and transportation vehicles is an important technology. With the acceleration of urbanization and the rapid development of the economy, the amount of solid waste generated continues to increase, and the collection and treatment of solid waste has become an important issue. In the process of solid waste collection and transportation, how to reasonably plan the routes of collection and transportation vehicles, improve collection and transportation efficiency and reduce costs is a technical problem that needs to be solved urgently.

[0003] Since traditional solid waste collection and transportation methods lack the necessary sensors and real-time monitoring methods, the location and loading status of garbage bins cannot be accurately obtained. Because the location and loading information of garbage bins are inaccurate, vehicles in some areas may run empty, while vehicles in other areas may be overloaded, which can easily lead to high empty and overload rates of collection and transportation vehicles. Traditional route planning methods lead to additional energy consumption due to vehicle idling, overloading or unoptimized routes, which in turn increases carbon emissions and environmental pollution, wastes resources and increases transportation costs. In addition, there are difficulties in identifying and locating solid waste. Traditional collection and transportation methods lack technologies such as RFID, barcodes or image recognition, making it difficult to achieve accurate solid waste positioning and classification, which affects the accuracy and timeliness of solid waste collection and transportation. In order to solve this technical problem, we provide a dynamic route optimization management method and system for solid waste collection and transportation vehicles. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for dynamic route optimization management of solid waste collection and transportation vehicles. By deploying sensor nodes at the garbage bin placement points in each park to build a wireless sensor network, the location of the garbage bin can be accurately obtained, avoiding the tediousness and error of manual inspection one by one.

[0005] To solve the background technical problems, one of the purposes of the present invention is to provide a method for optimizing the dynamic route management of solid waste collection and transportation vehicles, comprising the following steps:

[0006] S1. Deploy sensor nodes at the garbage bin placement points in each park, build a wireless sensor network, and obtain the location of the garbage bin based on the signal transmission between the beacon nodes and sensor nodes in the wireless sensor network;

[0007] S2. After obtaining the location of the garbage bin, the infrared emitting device of the sensor node emits infrared rays to the solid waste. The CCD detector device of the sensor node receives the reflected rays between the infrared rays and the solid waste, analyzes the reflected rays, obtains the angle offset value, and then substitutes the angle offset value into the trigonometric principle to obtain the distance between the solid waste and the sensor node, and judges the loading degree of the garbage bin according to the distance.

[0008] S3. Install a camera directly above the trash bin and collect solid waste images. Use visual recognition and identification technology to identify and grayscale the solid waste images, match them with the solid waste characteristic database to obtain the solid waste identification code of the solid waste in the trash bin, and then introduce Gaussian filtering and Canny algorithm to extract the edges of the solid waste identification code to obtain the quadrilateral of the solid waste identification code, and calculate the location coordinates of the solid waste based on the quadrilateral of the solid waste identification code;

[0009] S4. The location coordinates of the solid waste are transmitted to the command center. The command center obtains the load capacity of the solid waste collection and transportation vehicle through sensors, and formulates a solid waste transportation route based on the location coordinates of the solid waste, the loading level of the garbage bin, and the remaining load capacity of the solid waste collection and transportation vehicle.

[0010] As a further improvement of the technical solution, the method of obtaining the location of the garbage bin according to the signal transmission between the beacon node and the sensor node in the wireless sensor network in S1 specifically includes:

[0011] The beacon node in the wireless sensor sends a signal containing its own location information to the area around the trash can. The sensor node at the trash can placement point receives the signal sent by the beacon node and measures the received signal strength and the time when the signal arrives. Based on information such as signal strength and time, the distance between the sensor node and the beacon node is calculated. By transmitting and measuring signals with multiple beacon nodes, the location coordinates of the sensor node, i.e., the location coordinates of the trash can, are determined using a triangulation positioning algorithm.

[0012] As a further improvement of the technical solution, the method in S2 of transmitting infrared rays to the solid waste by the infrared emitting device of the sensor node and receiving the reflected rays between the infrared rays and the solid waste by the CCD detector device of the sensor node specifically includes:

[0013] An infrared emitting device and a CCD calibrator are installed on the sensor node of the trash bin. The infrared emitting device is used to emit infrared rays to the solid waste in the trash bin, and the CCD calibrator is used to receive reflected rays between the infrared rays and the solid waste. The incident angle of the reflected rays is determined through the measurement mechanism inside the sensor, and the incident angle of the reflected rays is compared with the emission angle of the infrared rays. According to the difference between the incident angle and the emission angle, the angle offset value of the reflected rays is calculated.

[0014] As a further improvement of the technical solution, the distance between the solid waste and the sensor node is obtained by triangulation principle in S2, and the method of judging the loading degree of the garbage bin according to the distance specifically includes:

[0015] The angle at which the infrared ray emitted by the infrared emitting device of the sensor node is recorded as θ f The angle offset of the reflected line obtained by the CCD detector of the sensor node can be combined with the emission angle to obtain the reflection angle, which is recorded as θ r , the vertical distance from the sensor node to the bottom of the trash can is recorded as h. With the sensor node as the vertex, the infrared rays emitted to the solid waste and the vertical line from the sensor node to the bottom of the trash can form a triangle. According to the sine theorem, the distance d from the sensor node to the solid waste is calculated. The calculation formula of the distance d from the sensor node to the solid waste is d = h × tan (θ f +θ r );

[0016] According to historical experience, d 1 ,d 2 ,d 3 The three distance thresholds divide the bin loading level into high, medium, and low levels, and d 1 <d 2 <d 3 , when d<d 1 When d 1 <d<d 2 When d 2 <d<d 3 When d 3 When <d, it is judged that the garbage bin has just been put into use or there is no solid waste.

[0017] As a further improvement of the technical solution, the method of graying the solid waste image by visual recognition technology in S3 and matching it with the solid waste characteristic database to obtain the solid waste identification code of the solid waste in the trash bin specifically includes:

[0018] Through the camera directly above the garbage bin, video is collected for garbage bins with high loading degree, medium loading degree and low loading degree, and the video stream of solid waste in the garbage bin is obtained. Single-frame images of solid waste are extracted from the solid waste video stream at the same time interval, and the single-frame images of solid waste are grayed by using the maximum value method. The grayed single-frame images of solid waste are subjected to feature extraction to obtain the texture features, color features and shape features of the solid waste.

[0019] Collect different types of solid waste images, adjust the weights of the texture features, color features and shape features of the solid waste according to historical experience, obtain the comprehensive features of the solid waste, convert the comprehensive features of the solid waste into a vector representation, denoted as F = (T1, T2, T3), where F represents the comprehensive feature vector of the solid waste, T1 represents the texture feature of the solid waste, T2 represents the color feature, and T3 represents the shape feature. Calculate the similarity between the comprehensive feature vector of the solid waste to be identified and the comprehensive feature vector of each solid waste type in the solid waste characteristic database, select the solid waste type with the highest similarity as the matching result, and determine its corresponding identification code as the identification code of the solid waste.

[0020] As a further improvement of the technical solution, the method of introducing Gaussian filtering to extract the edge of the solid waste identification code in S3 to obtain the quadrilateral of the solid waste identification code, and obtaining the location coordinates of the solid waste according to the quadrilateral of the solid waste identification code specifically includes:

[0021] The solid waste identification code image is smoothed using Gaussian filtering, and non-maximum suppression and double threshold detection are performed on the solid waste identification code image according to the Canny algorithm to obtain the edge image of the solid waste identification code. The contour detection algorithm is then used to detect all contours in the edge image of the solid waste identification code, and the number of convex hulls of the contours is obtained. It is checked whether the number of convex hulls of the contour is 4. If so, it is a quadrilateral contour, and the image of the contour area is extracted to obtain the quadrilateral of the solid waste identification code;

[0022] Assume the optical center coordinates of the camera are (C x , C y , C z ), the focal length of the camera is j, and the coordinates of a vertex in the identification code quadrilateral in the image are (u1, v1). Then the coordinates of a vertex in the identification code quadrilateral in the actual space (X1, Y1, Z) are calculated by the following formula:

[0023]

[0024]

[0025] Among them, Z is calculated by the ratio of the actual size of the solid waste and the size in the solid waste image. Similarly, the coordinates of the other three vertices of the identification code quadrilateral in the actual space can be obtained, and the average value of the coordinates of the four vertices of the identification code quadrilateral is calculated as the coordinates of the center of the identification code (X0, Y0, Z0). Assuming that the offset of the coordinates of the center of the identification code on the solid waste relative to the center of the solid waste is (eX, eY, eZ), the center coordinates of the solid waste are (X0+eX, Y0+eY, Z0+eZ), and the position on the plane is (X0+eX, Y0+eY).

[0026] As a further improvement of the technical solution, the command center in S4 obtains the load capacity of the solid waste collection and transportation vehicle through the sensor, and formulates the solid waste transportation route according to the solid waste location coordinates and the load capacity of the solid waste collection and transportation vehicle, specifically including:

[0027] A load sensor is installed at the bottom of the solid waste collection and transportation vehicle. The load sensor is used to obtain the load of the solid waste collection and transportation vehicle in real time and feed it back to the command center. The coordinates of the solid waste location of each park are imported into the GIS software, and the garbage bins at the solid waste location of each park are marked with colors according to the loading degree of the garbage bins. Red is defined as a high loading degree, blue is a medium loading degree, and green is a low loading degree. The solid waste transportation route is formulated according to the load of the solid waste collection and transportation vehicle and the loading degree of the garbage bins at the solid waste location of each park;

[0028] The command center obtains the remaining load capacity of all solid waste collection and transportation vehicles through load sensors. The remaining load capacity is obtained by subtracting the loaded load capacity from the maximum load capacity of the solid waste collection and transportation vehicle, and calculates the distance between the location coordinates of the solid waste marked in red on the GIS map and the location coordinates of the solid waste collection and transportation vehicle, finds the solid waste collection and transportation vehicle closest to the red marked solid waste, and gives priority to arranging the solid waste collection and transportation vehicle with the largest remaining load capacity and the closest distance to collect solid waste. After completing the solid waste collection, the command center re-obtains the remaining load capacity of the solid waste collection and transportation vehicle through the load sensor, and obtains the color marks of the remaining parks through the GIS map, and gives priority to arranging the solid waste collection and transportation vehicle with the closest distance and the largest remaining load capacity to collect the solid waste at the red mark.

[0029] The second object of the present invention is to provide a system for implementing a method for optimizing the dynamic route management of solid waste collection and transportation vehicles as described in any one of the above, comprising:

[0030] The location acquisition unit deploys sensor nodes at the garbage bin placement points in each park to build a wireless sensor network, and obtains the location coordinates of the garbage bin based on the signal transmission between the beacon nodes and sensor nodes in the wireless sensor network;

[0031] The analysis and judgment unit obtains the angle offset value by analyzing the infrared rays emitted by the sensor node and the reflected rays formed by the solid waste, and then substitutes the angle offset value into the triangulation principle for analysis to judge the loading degree of the garbage bin;

[0032] The coordinate recognition unit includes a visual recognition module and a coordinate acquisition module;

[0033] The visual recognition module recognizes and grayscales the solid waste image through visual recognition and identification technology, and matches it with the solid waste characteristic database to obtain the solid waste identification code;

[0034] The coordinate acquisition module introduces Gaussian filtering and Canny algorithm to extract the edge of the solid waste identification code, obtains the quadrilateral of the solid waste identification code, and calculates the location coordinates of the solid waste according to the quadrilateral of the solid waste identification code;

[0035] The solid waste collection and transportation unit receives the solid waste location coordinates and the loading level of the garbage bin, and formulates a solid waste transportation route based on the solid waste location coordinates, the loading level of the garbage bin and the remaining load capacity of the solid waste collection and transportation vehicle.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention deploys sensor nodes at the garbage bin placement points in each park to build a wireless sensor network, which can accurately obtain the location of the garbage bin, avoiding the tediousness and errors of manual inspection one by one. At the same time, the infrared emission device and CCD calibration device of the sensor node can accurately determine the loading degree of the garbage bin, which is more accurate and reliable than the traditional method of relying on manual observation or simple sensors. The visual recognition and identification technology is used to process the solid waste image, and the solid waste identification code is obtained by matching with the solid waste characteristic database, and then the edge extraction is performed by Gaussian filtering and Canny algorithm, which can accurately obtain the location coordinates of the solid waste. This method improves the efficiency and accuracy of solid waste identification and helps to optimize the formulation of solid waste collection and transportation routes. The command center formulates the solid waste transportation route according to the solid waste location coordinates, the loading degree of the garbage bin and the remaining load of the solid waste collection and transportation vehicle, and can give priority to the solid waste collection and transportation vehicle with the largest remaining load and the closest distance for solid waste collection, avoiding the empty and overloaded vehicles, improving the transportation efficiency and reducing the transportation cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is the overall workflow diagram of the present invention;

[0039] Figure 2 It is a schematic diagram of the overall structure of the present invention;

[0040] The meaning of each number in the figure is:

[0041] 1. Position acquisition unit; 2. Analysis and judgment unit; 3. Coordinate identification unit; 31. Visual recognition module; 32. Coordinate acquisition module; 4. Solid waste collection and transportation unit. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. 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.

[0043] Example 1

[0044] See also Figure 1 As shown, one of the purposes of this embodiment is to provide a method for optimizing the dynamic route management of solid waste collection and transportation vehicles, including the following steps:

[0045] S1. Deploy sensor nodes at the garbage bin placement points in each park, build a wireless sensor network, and obtain the location of the garbage bin based on the signal transmission between the beacon nodes and sensor nodes in the wireless sensor network.

[0046] In S1, the method of obtaining the location of the garbage bin according to the signal transmission between the beacon node and the sensor node in the wireless sensor network specifically includes:

[0047] The reason for wireless sensor network node positioning technology is to accurately obtain the location information of garbage bins in a large area without manual inspection one by one, which improves efficiency and real-time performance. Wireless sensor network node positioning technology has the advantages of wide coverage, strong real-time performance and low cost.

[0048] The beacon node in the wireless sensor sends a signal containing its own location information to the area around the trash can. The sensor node at the trash can placement point receives the signal sent by the beacon node and measures the received signal strength and the time when the signal arrives. Based on information such as signal strength and time, the distance between the sensor node and the beacon node is calculated. By transmitting and measuring signals with multiple beacon nodes, the location coordinates of the sensor node, i.e., the location coordinates of the trash can, are determined using a triangulation positioning algorithm.

[0049] The specific calculation formula for calculating the distance between the sensor node and the beacon node is: Where d represents the distance between the sensor node and the beacon node, p tx It is represented as the transmission power of the beacon node, p rx It is represented as the power received by the sensor node, and n is the environmental attenuation factor.

[0050] The method of using triangulation positioning algorithm to determine the location of sensor nodes includes:

[0051] Assume that the coordinates of the three beacon nodes are (x1, y1), (x2, y2), (x3, y3) and the distances from the sensor node to the three beacon nodes are d1, d2, d3, and the coordinates (x, y) of the sensor node are calculated by the following formula, namely:

[0052]

[0053]

[0054] S2. After obtaining the location of the trash bin, the infrared emitting device of the sensor node emits infrared rays to the solid waste. The CCD calibrator device of the sensor node receives the reflected rays between the infrared rays and the solid waste, and analyzes the reflected rays to obtain the angle offset value. The angle offset value is then substituted into the triangulation principle to obtain the distance between the solid waste and the sensor node, and the loading degree of the trash bin is judged based on the distance.

[0055] In S2, the infrared ray transmitting device of the sensor node transmits infrared rays to the solid waste, and the CCD detector device of the sensor node receives the reflected rays between the infrared rays and the solid waste, specifically including:

[0056] Traditional methods that rely on manual observation or simple sensors make it difficult to accurately judge the loading level of a trash bin. However, more accurate data can be obtained through infrared rays and reflected lines, thereby more accurately determining the accumulation of solid waste in the trash bin. The use of infrared sensor ranging technology is to monitor the loading status of the trash bin in real time, so as to arrange collection and transportation in a timely manner and avoid secondary pollution caused by overfilling of the trash bin.

[0057] An infrared transmitting device and a CCD calibrator are installed on the sensor node of the garbage bin. The infrared transmitting device is used to transmit infrared rays to the solid waste in the garbage bin, and the CCD calibrator is used to receive the reflected rays between the infrared rays and the solid waste. The incident angle of the reflected rays is determined by the measurement mechanism inside the sensor, and the incident angle of the reflected rays is compared with the emission angle of the infrared rays. According to the difference between the incident angle and the emission angle, the angle offset value of the reflected rays is calculated. The infrared rays and the CCD calibrator can achieve high-precision angle measurement and distance calculation, which can more accurately reflect the loading status of the garbage bin than the traditional method. This measurement method does not require direct contact with the solid waste, and will not interfere with or contaminate the solid waste. At the same time, it also reduces the risk of wear and damage to the sensor. By accurately judging the loading degree of the garbage bin, the route and time of the collection and transportation vehicles can be reasonably arranged to avoid unnecessary driving and waiting, thereby improving the collection and transportation efficiency.

[0058] The method for calculating the angle offset value of the reflected line includes:

[0059] Assume the emission angle of infrared ray is θ f , the incident angle of the reflected light is θ r , then the calculation formula of the angle offset value Δθ is: Δθ=θ r -θ f .

[0060] In S2, the distance between the solid waste and the sensor node is obtained by the triangulation principle, and the method of judging the loading degree of the garbage bin according to the distance includes:

[0061] The angle at which the infrared ray emitted by the infrared emitting device of the sensor node is recorded as θ f The angle offset of the reflected line obtained by the CCD detector of the sensor node can be combined with the emission angle to obtain the reflection angle, which is recorded as θ r , the vertical distance from the sensor node to the bottom of the trash can is recorded as h. With the sensor node as the vertex, the infrared rays emitted to the solid waste and the vertical line from the sensor node to the bottom of the trash can form a triangle. According to the sine theorem, the distance d from the sensor node to the solid waste is calculated. The calculation formula of the distance d from the sensor node to the solid waste is d = h × tan (θ f +θ r );

[0062] According to historical experience, d 1 ,d 2 ,d 3 The three distance thresholds divide the bin loading level into high, medium, and low levels, and d 1 <d 2 <d 3 , when d<d 1 When d 1 <d<d 2 When d 2 <d<d 3 When d 3 When the load is less than d, it is judged that the garbage bin has just been put into use or there is no solid waste. By accurately judging the loading degree of the garbage bin, the route and time of the collection and transportation vehicles can be reasonably arranged to avoid unnecessary driving and waiting, thereby improving the collection and transportation efficiency.

[0063] S3. Install a camera directly above the trash bin and collect solid waste images. Use visual recognition and identification technology to identify and grayscale the solid waste images, and match them with the solid waste characteristic database to obtain the solid waste identification code of the solid waste in the trash bin. Then introduce Gaussian filtering and Canny algorithm to extract the edges of the solid waste identification code, obtain the quadrilateral of the solid waste identification code, and calculate the location coordinates of the solid waste based on the quadrilateral of the solid waste identification code.

[0064] In order to more accurately obtain information on solid waste in trash bins for subsequent effective solid waste collection and management, traditional solid waste identification methods may not be accurate and efficient enough to meet the needs of refined solid waste management.

[0065] In S3, the solid waste image is grayed out by visual recognition technology, and matched with the solid waste characteristic database to obtain the solid waste identification code of the solid waste in the trash bin, specifically including:

[0066] Through the camera directly above the garbage bin, video capture is performed on garbage bins with high, medium and low loading degrees, and a video stream of solid waste in the garbage bin is obtained. Single-frame images of solid waste are extracted from the solid waste video stream at the same time interval, and the single-frame images of solid waste are grayed using the maximum value method. Feature extraction is performed on the grayed single-frame images of solid waste to obtain the texture features, color features and shape features of the solid waste. By graying and extracting features from the solid waste images, the texture features, color features and shape features of the solid waste can be more accurately obtained and matched with the solid waste characteristic database. The solid waste type with the highest similarity can be selected as the matching result, thereby improving the accuracy of the solid waste identification code.

[0067] Collect different types of solid waste images, adjust the weights of the texture features, color features and shape features of the solid waste according to historical experience, obtain the comprehensive features of the solid waste, convert the comprehensive features of the solid waste into a vector representation, denoted as F = (T1, T2, T3), where F represents the comprehensive feature vector of the solid waste, T1 represents the texture features of the solid waste, T2 represents the color features, and T3 represents the shape features. Calculate the similarity between the comprehensive feature vector of the solid waste to be identified and the comprehensive feature vector of each solid waste type in the solid waste characteristic database, select the solid waste type with the highest similarity as the matching result, and determine its corresponding identification code as the identification code of the solid waste. Convert the comprehensive features of the solid waste into a vector representation and match it with the database, so as to accurately obtain the solid waste identification code of the solid waste in the trash can, providing an important basis for the subsequent collection, transportation and management of solid waste.

[0068] The edge extraction of solid waste identification code is crucial to accurately obtain the location coordinates of solid waste. By introducing Gaussian filtering and Canny algorithm, the edge extraction of solid waste identification code can be effectively performed to obtain a clear quadrilateral outline, and then the location coordinates of solid waste can be calculated based on the quadrilateral.

[0069] In S3, Gaussian filtering is introduced to extract the edge of the solid waste identification code to obtain the quadrilateral of the solid waste identification code, and the location coordinates of the solid waste are obtained according to the quadrilateral of the solid waste identification code, which specifically includes:

[0070] The solid waste identification code image is smoothed using Gaussian filtering, and non-maximum suppression and double threshold detection are performed on the solid waste identification code image according to the Canny algorithm to obtain the edge image of the solid waste identification code. The contour detection algorithm is then used to detect all contours in the edge image of the solid waste identification code, and the number of convex hulls of the contour is obtained. It is checked whether the number of convex hulls of the contour is 4. If so, it is a quadrilateral contour, and the image of the contour area is extracted to obtain the quadrilateral of the solid waste identification code.

[0071] Assume the optical center coordinates of the camera are (C x , C y, C z ), the focal length of the camera is j, and the coordinates of a vertex in the identification code quadrilateral in the image are (u1, v1). Then the coordinates of a vertex in the identification code quadrilateral in the actual space (X1, Y1, Z) are calculated by the following formula:

[0072]

[0073]

[0074] Among them, Z is calculated by the ratio of the actual size of the solid waste and the size in the solid waste image. Similarly, the coordinates of the other three vertices of the identification code quadrilateral in the actual space can be obtained, and the average value of the coordinates of the four vertices of the identification code quadrilateral is calculated as the coordinates of the center of the identification code (X0, Y0, Z0). Assuming that the offset of the coordinates of the center of the identification code on the solid waste relative to the center of the solid waste is (eX, eY, eZ), the center coordinates of the solid waste are (X0+eX, Y0+eY, Z0+eZ), and the position on the plane is (X0+eX, Y0+eY), which helps the command center to grasp the location information of the solid waste more accurately, thereby formulating a more optimized solid waste transportation route, improving the efficiency and accuracy of solid waste collection and transportation, and reducing transportation costs and resource waste.

[0075] Traditional solid waste collection and transportation route planning often lacks scientificity and real-timeness, resulting in low collection and transportation efficiency and increased costs. It is also difficult to meet the collection and transportation needs of different garbage bin loading levels. By installing load sensors on the bottom of solid waste collection and transportation vehicles and combining GIS software to mark the solid waste location and garbage bin loading level, real-time monitoring and precise management of solid waste collection and transportation vehicles and solid waste information can be achieved, thereby formulating a more reasonable solid waste transportation route.

[0076] S4. The location coordinates of the solid waste are transmitted to the command center. The command center obtains the load capacity of the solid waste collection and transportation vehicle through sensors, and formulates a solid waste transportation route based on the location coordinates of the solid waste, the loading level of the garbage bin, and the remaining load capacity of the solid waste collection and transportation vehicle.

[0077] In S4, the command center obtains the load capacity of the solid waste collection and transportation vehicles through sensors, and formulates the solid waste transportation route according to the solid waste location coordinates and the load capacity of the solid waste collection and transportation vehicles, including:

[0078] A load sensor is installed at the bottom of the solid waste collection and transportation vehicle. The load sensor is used to obtain the load capacity of the solid waste collection and transportation vehicle in real time and feed it back to the command center. The solid waste location coordinates of each park are imported into the GIS software, and color marking is performed according to the loading degree of the garbage bins at the solid waste locations of each park. Red is defined as a high loading degree, blue as a medium loading degree, and green as a low loading degree. Solid waste transportation routes are formulated according to the load capacity of the solid waste collection and transportation vehicles and the loading degree of the garbage bins at the solid waste locations of each park, so as to achieve accurate scheduling, give priority to the solid waste collection and transportation vehicles with the largest remaining load capacity and the closest distance to collect solid waste, and improve collection and transportation efficiency.

[0079] The command center obtains the remaining load of all solid waste collection and transportation vehicles through load sensors. The remaining load is obtained by subtracting the loaded load from the maximum load of the solid waste collection and transportation vehicle, and calculates the distance between the solid waste location coordinates marked in red on the GIS map and the location coordinates of the solid waste collection and transportation vehicle, finds the solid waste collection and transportation vehicle closest to the red marked solid waste, reduces the transportation distance and time, and gives priority to arranging the solid waste collection and transportation vehicle with the largest remaining load and the closest distance to collect solid waste. After completing the solid waste collection, the command center re-obtains the remaining load of the solid waste collection and transportation vehicle through the load sensor, and obtains the color marks of the remaining parks through the GIS map, and gives priority to arranging the solid waste collection and transportation vehicle with the closest distance and the largest remaining load to collect the solid waste at the red mark, avoids vehicle overloading or emptying, improves transportation efficiency, collects and transports solid waste in a timely manner, and avoids secondary pollution caused by excessive filling of garbage bins.

[0080] Embodiment 2:

[0081] The second object of the present invention is to provide a system for implementing a method for optimizing the dynamic route management of solid waste collection and transportation vehicles including any one of the above items, comprising:

[0082] The location acquisition unit 1 builds a wireless sensor network by deploying sensor nodes at the garbage bin placement points in each park, and acquires the location coordinates of the garbage bin based on the signal transmission between the beacon nodes and the sensor nodes in the wireless sensor network.

[0083] The analysis and judgment unit 2 obtains the angle offset value by analyzing the infrared rays emitted by the sensor node and the reflected rays formed between the solid waste, and then substitutes the angle offset value into the triangulation principle for analysis to judge the loading degree of the garbage bin.

[0084] The coordinate recognition unit 3 includes a visual recognition module 31 and a coordinate acquisition module 32;

[0085] The visual recognition module 31 recognizes and grayscales the solid waste image through visual recognition and identification technology, and matches it with the solid waste characteristic database to obtain the solid waste identification code.

[0086] The coordinate acquisition module 32 introduces Gaussian filtering and Canny algorithm to extract the edge of the solid waste identification code, obtain the quadrilateral of the solid waste identification code, and calculate the location coordinates of the solid waste based on the quadrilateral of the solid waste identification code.

[0087] The solid waste collection and transportation unit 4 receives the solid waste location coordinates and the loading level of the garbage bin, and formulates a solid waste transportation route according to the solid waste location coordinates, the loading level of the garbage bin and the remaining load capacity of the solid waste collection and transportation vehicle.

[0088] The present invention builds a wireless sensor network by deploying sensor nodes at the garbage bin placement points in the park, obtains the location of the garbage bin, uses an infrared transmitter and a CCD calibrator to determine the loading degree of the garbage bin, collects solid waste images through a camera, identifies and processes them to obtain solid waste identification codes and location coordinates. The command center formulates transportation routes based on this information and the remaining load capacity of the vehicle, reduces environmental pollution, improves the efficiency of solid waste collection and transportation, and reduces costs, which has important practical application value.

[0089] 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 by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for optimizing the dynamic routes of solid waste collection and transportation vehicles. Features: The following steps are involved: S1. Deploy sensor nodes at the garbage bin placement points in each park, build a wireless sensor network, and obtain the location of the garbage bin based on the signal transmission between the beacon nodes and sensor nodes in the wireless sensor network; S2. After obtaining the location of the garbage bin, the infrared emitting device of the sensor node emits infrared rays to the solid waste. The CCD detector device of the sensor node receives the reflected rays between the infrared rays and the solid waste, analyzes the reflected rays, obtains the angle offset value, and then substitutes the angle offset value into the trigonometric principle to obtain the distance between the solid waste and the sensor node, and judges the loading degree of the garbage bin according to the distance. S3. Install a camera directly above the trash bin and collect solid waste images. Use visual recognition and identification technology to identify and grayscale the solid waste images, match them with the solid waste characteristic database to obtain the solid waste identification code of the solid waste in the trash bin, and then introduce Gaussian filtering and Canny algorithm to extract the edges of the solid waste identification code to obtain the quadrilateral of the solid waste identification code, and calculate the location coordinates of the solid waste based on the quadrilateral of the solid waste identification code; S4. The location coordinates of the solid waste are transmitted to the command center. The command center obtains the load capacity of the solid waste collection and transportation vehicle through sensors, and formulates a solid waste transportation route based on the location coordinates of the solid waste, the loading level of the garbage bin, and the remaining load capacity of the solid waste collection and transportation vehicle.

2. The method for optimizing the dynamic route management of solid waste collection and transportation vehicles according to claim 1, Features: The method of obtaining the location of the garbage bin according to the signal transmission between the beacon node and the sensor node in the wireless sensor network in S1 specifically includes: The beacon node in the wireless sensor sends a signal containing its own location information to the area around the trash can. The sensor node at the trash can placement point receives the signal sent by the beacon node and measures the received signal strength and the time when the signal arrives. Based on information such as signal strength and time, the distance between the sensor node and the beacon node is calculated. By transmitting and measuring signals with multiple beacon nodes, the location coordinates of the sensor node, i.e., the location coordinates of the trash can, are determined using a triangulation positioning algorithm.

3. The method for optimizing the dynamic route management of solid waste collection and transportation vehicles according to claim 2, Features: In S2, the infrared emitting device of the sensor node emits infrared rays to the solid waste, and the CCD detector device of the sensor node receives the reflected rays between the infrared rays and the solid waste, specifically including: An infrared emitting device and a CCD calibrator are installed on the sensor node of the trash bin. The infrared emitting device is used to emit infrared rays to the solid waste in the trash bin, and the CCD calibrator is used to receive reflected rays between the infrared rays and the solid waste. The incident angle of the reflected rays is determined through the measurement mechanism inside the sensor, and the incident angle of the reflected rays is compared with the emission angle of the infrared rays. According to the difference between the incident angle and the emission angle, the angle offset value of the reflected rays is calculated.

4. The method for optimizing the dynamic route management of solid waste collection and transportation vehicles according to claim 2, Features: In S2, the distance between the solid waste and the sensor node is obtained by using the triangulation principle, and the method of judging the loading degree of the garbage bin according to the distance specifically includes: The angle at which the infrared ray emitted by the infrared emitting device of the sensor node is recorded as θ f The angle offset of the reflected line obtained by the CCD detector of the sensor node can be combined with the emission angle to obtain the reflection angle, which is recorded as θ r , the vertical distance from the sensor node to the bottom of the trash can is recorded as h. With the sensor node as the vertex, the infrared rays emitted to the solid waste and the vertical line from the sensor node to the bottom of the trash can form a triangle. According to the sine theorem, the distance d from the sensor node to the solid waste is calculated. The calculation formula of the distance d from the sensor node to the solid waste is d = h × tan (θ f +θ r ); Set d according to historical experience 1 , d 2 , d 3 Three distance thresholds divide the loading degree of the trash bin into three levels: high, medium, and low, and d 1 < d 2 < d 3 , when d < d 1 , it is judged that the trash bin has a high loading degree. When d 1 < d < d 2 , it is judged that the trash bin has a medium loading degree. When d 2 < d < d 3 , it is judged that the trash bin has a low loading degree. When d 3 < d, it is judged that the trash bin has just been put into use or there is no solid waste.

5. The method for optimizing the dynamic route management of solid waste collection and transportation vehicles according to claim 1, Features: In S3, the solid waste image is grayed out by visual recognition technology, and matched with the solid waste characteristic database to obtain the solid waste identification code of the solid waste in the trash bin, specifically including: Through the camera directly above the garbage bin, video is collected for garbage bins with high loading degree, medium loading degree and low loading degree, and the video stream of solid waste in the garbage bin is obtained. Single-frame images of solid waste are extracted from the solid waste video stream at the same time interval, and the single-frame images of solid waste are grayed by using the maximum value method. The grayed single-frame images of solid waste are subjected to feature extraction to obtain the texture features, color features and shape features of the solid waste. Different types of solid waste images are collected, and the texture features, color features, and shape features of the solid waste are weighted according to historical experience to obtain the comprehensive features of the solid waste. The comprehensive features of the solid waste are converted into vector representation, which is recorded as F = (T 1 , T 2 , T 3 ), where F represents the comprehensive feature vector of solid waste, T 1 Represented as the texture feature of solid waste, T 2 Represented as color feature, T 3 It is represented as shape features, and the similarity between the comprehensive feature vector of the solid waste to be identified and the comprehensive feature vector of each solid waste type in the solid waste characteristic database is calculated. The solid waste type with the highest similarity is selected as the matching result, and its corresponding identification code is determined as the identification code of the solid waste.

6. The method for optimizing the dynamic route management of solid waste collection and transportation vehicles according to claim 1, Features: In S3, Gaussian filtering is introduced to extract the edge of the solid waste identification code to obtain the quadrilateral of the solid waste identification code, and the location coordinates of the solid waste are obtained according to the quadrilateral of the solid waste identification code, which specifically includes: The solid waste identification code image is smoothed using Gaussian filtering, and non-maximum suppression and double threshold detection are performed on the solid waste identification code image according to the Canny algorithm to obtain the edge image of the solid waste identification code. The contour detection algorithm is then used to detect all contours in the edge image of the solid waste identification code, and the number of convex hulls of the contours is obtained. It is checked whether the number of convex hulls of the contour is 4. If so, it is a quadrilateral contour, and the image of the contour area is extracted to obtain the quadrilateral of the solid waste identification code; Assume the optical center coordinates of the camera are (C x , C y , C z ), the focal length of the camera is j, and the coordinates of a vertex in the identification code quadrilateral in the image are (u 1 , v 1 ), then the coordinates of a vertex in the identification code quadrilateral in real space (X 1 , Y 1 , Z) is calculated by the following formula: Among them, Z is calculated by the ratio of the actual size of the solid waste and the size in the solid waste image. Similarly, the coordinates of the other three vertices of the identification code quadrilateral in the actual space can be obtained, and the coordinates of the center of the identification code (X) are calculated by calculating the average value of the coordinates of the four vertices of the identification code quadrilateral. 0 , Y 0 , Z 0 ), let the offset of the coordinates of the center of the identification code on the solid waste relative to the center of the solid waste be (eX, eY, eZ), then the center coordinates of the solid waste are (X 0 +eX,Y 0 +eY,Z 0 +eZ), the position on the plane is (X 0 +eX,Y 0 +eY).

7. The method for optimizing the dynamic route management of solid waste collection and transportation vehicles according to claim 1, Features: In S4, the command center obtains the load capacity of the solid waste collection and transportation vehicle through sensors, and formulates a solid waste transportation route according to the solid waste location coordinates and the load capacity of the solid waste collection and transportation vehicle, specifically including: A load sensor is installed at the bottom of the solid waste collection and transportation vehicle. The load sensor is used to obtain the load of the solid waste collection and transportation vehicle in real time and feed it back to the command center. The coordinates of the solid waste location of each park are imported into the GIS software, and the garbage bins at the solid waste location of each park are marked with colors according to the loading degree of the garbage bins. Red is defined as a high loading degree, blue is a medium loading degree, and green is a low loading degree. The solid waste transportation route is formulated according to the load of the solid waste collection and transportation vehicle and the loading degree of the garbage bins at the solid waste location of each park; The command center obtains the remaining load capacity of all solid waste collection and transportation vehicles through load sensors. The remaining load capacity is obtained by subtracting the loaded load capacity from the maximum load capacity of the solid waste collection and transportation vehicle, and calculates the distance between the location coordinates of the solid waste marked in red on the GIS map and the location coordinates of the solid waste collection and transportation vehicle, finds the solid waste collection and transportation vehicle closest to the red marked solid waste, and gives priority to arranging the solid waste collection and transportation vehicle with the largest remaining load capacity and the closest distance to collect solid waste. After completing the solid waste collection, the command center re-obtains the remaining load capacity of the solid waste collection and transportation vehicle through the load sensor, and obtains the color marks of the remaining parks through the GIS map, and gives priority to arranging the solid waste collection and transportation vehicle with the closest distance and the largest remaining load capacity to collect the solid waste at the red mark.

8. A system for implementing the method for dynamic route optimization management of solid waste collection and transportation vehicles according to any one of claims 1 to 7, It is characterized in that include: The location acquisition unit (1) constructs a wireless sensor network by deploying sensor nodes at the garbage bin placement points in each park, and acquires the location coordinates of the garbage bin according to the signal transmission between the beacon nodes and the sensor nodes in the wireless sensor network; The analysis and judgment unit (2) obtains an angle offset value by analyzing the infrared rays emitted by the sensor node and the reflected rays formed between the solid waste, and then substitutes the angle offset value into the triangulation principle for analysis to judge the loading degree of the garbage bin; The coordinate recognition unit (3) comprises a visual recognition module (31) and a coordinate acquisition module (32); The visual recognition module (31) recognizes and grayscales the solid waste image using visual recognition and identification technology, and matches it with the solid waste characteristic database to obtain a solid waste identification code; The coordinate acquisition module (32) introduces Gaussian filtering and Canny algorithm to extract the edge of the solid waste identification code, obtains the quadrilateral of the solid waste identification code, and calculates the position coordinates of the solid waste based on the quadrilateral of the solid waste identification code; The solid waste collection and transportation unit (4) receives the solid waste location coordinates and the loading level of the garbage bin, and formulates a solid waste transportation route according to the solid waste location coordinates, the loading level of the garbage bin and the remaining load of the solid waste collection and transportation vehicle.

Images