Data interaction method of garbage classification collection vehicle based on Internet of Things

Abstract

The present invention relates to the field of data processing technology, and in particular to a data interaction method for a garbage classification collection vehicle based on the Internet of Things. The method comprises: obtaining the distribution positions and garbage volumes of garbage bins, clustering the garbage bins to obtain multiple first clustering clusters, updating the first clustering clusters to obtain the best clustering cluster; and transporting the garbage in the garbage bins in the best clustering cluster to a transfer station. The present invention simplifies the garbage collection path planning problem and improves the efficiency and quality of garbage collection.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a data interaction method for a garbage sorting and collection vehicle based on the Internet of Things. Background Art

[0002] IoT technology is gradually becoming an important part of smart city management in terms of data interaction of garbage sorting and collection vehicles. For example, by installing GPS positioning systems and sensors on garbage collection vehicles, the location of the vehicle, garbage loading volume and other information can be monitored in real time, and the visual scheduling of the garbage collection and transportation process can be realized. In addition, IoT technology can also help optimize garbage collection routes, reduce transportation costs, improve transportation efficiency, and ensure that the garbage collection and transportation process does not affect the urban traffic order. At present, some cities have begun to implement smart garbage sorting and management projects based on the Internet of Things. These projects have improved the efficiency and management level of garbage sorting by deploying IoT devices and applying cloud computing technology, and promoted resource recycling and environmental protection. With the continuous advancement of technology and the reduction of costs, it is expected that the application of IoT in data interaction of garbage sorting and collection vehicles will be further expanded and become an indispensable part of smart city construction.

[0003] The Chinese patent document with the announcement number CN206906583U discloses a garbage collection vehicle location monitoring system, including a GPS positioning module, a processor, a display, a speaker, a wireless transceiver module, a remote control center and a mobile terminal arranged on the garbage collection vehicle, the processor collects location information and sends it to the remote control center, the mobile terminal connects to the remote control center to obtain the location information of the garbage collection vehicle and sends the processed garbage information, the remote control center sends the processed garbage information and the location information of the corresponding mobile device to the processor, the display is used to display the received processed garbage information and the location information of the mobile device, and the speaker is used for message reminder. The mobile terminal is a smart phone.

[0004] The above technical solution cannot plan the garbage collection route during the garbage collection process, while a reasonable garbage collection route and reasonable vehicle arrangement can reduce transportation costs, improve transportation efficiency, and shorten garbage collection time. When multiple garbage trucks need to be arranged to collect garbage from multiple garbage bins, due to the large number of garbage bins to be collected and their wide distribution range, the path planning complexity is high and the processing difficulty is relatively large. Summary of the invention

[0005] In order to solve the problem of how to plan the garbage collection route, the present invention provides a data interaction method for garbage classification collection vehicles based on the Internet of Things.

[0006] The present invention provides a data interaction method for a garbage classification collection vehicle based on the Internet of Things, which adopts the following technical solutions:

[0007] The data interaction method of garbage classification collection vehicle based on the Internet of Things includes the following steps:

[0008] Obtain the distribution location and garbage volume of the garbage bins, cluster the garbage bins to obtain multiple first clusters, and update the first clusters to obtain the best cluster;

[0009] Transport the garbage in the garbage bins in the best cluster to the transfer station;

[0010] The method for updating the first cluster to obtain the best cluster is:

[0011] The trash cans are clustered again using the location of any trash can in the first cluster as the cluster center to obtain multiple second clusters;

[0012] Calculate the sum of the garbage volumes of the garbage bins in each second cluster, and determine whether the maximum value of the sum of the garbage volumes is greater than the right end point of the preset allocation interval. If so, allocate one or more garbage bins in the corresponding second cluster to the remaining second clusters, so that the sum of the garbage volumes in the garbage bins in the second cluster corresponding to the maximum value is within the preset allocation interval;

[0013] Repeat the calculation and determination of the garbage volumes in the remaining second clusters until the garbage volumes in all second clusters are within the preset allocation interval, and take the second cluster whose sum of garbage volumes is finally within the preset allocation interval as the best cluster.

[0014] The clustering algorithm is used to initially cluster the garbage bins according to their location distribution, and the initial clustering results are updated and adjusted to obtain the best cluster. Finally, the garbage in each garbage bin in the best cluster is collected by a collection vehicle, which shortens the walking route of the collection vehicle during the garbage transportation process and improves the efficiency of garbage collection.

[0015] Preferably, the method of clustering the trash cans again by taking the location of any trash can in the first cluster as the cluster center is:

[0016] Calculate the distance between the trash can in the first cluster and the transfer station to obtain a first distance value of the corresponding trash can;

[0017] Calculate the distance between each first cluster center point and the transfer station to obtain multiple second distance values, and calculate the median and the average of the multiple second distance values;

[0018] The absolute value of the difference between the first distance value and the mean of each trash can is calculated, and the position of the trash can corresponding to the absolute value of the difference with the smallest value is used as the cluster center to cluster the trash cans again according to the preset adjustment distance.

[0019] Redefining the cluster centers and adjusting the distances to perform secondary clustering of the trash cans improves the accuracy and practicality of clustering, makes the collection routes more rational, and further improves the efficiency of garbage collection.

[0020] Preferably, the method further includes constructing an ideal extension line and an actual extension line by:

[0021] Connect the center point of the first cluster and the trash can farthest from the transfer station to obtain the first line segment;

[0022] Connect the center point of the first cluster and the trash can closest to the transfer station to obtain a second line segment;

[0023] The actual extension line is obtained by connecting the midpoint of the first line segment and the midpoint of the second line segment, and the ideal extension line is obtained by connecting the transfer station and the center point.

[0024] Preferably, the expression for adjusting the distance is:

[0025]

[0026] in, Indicates Trash bin and its The adjusted distance of the second cluster center, It is The center point of the second cluster, It is A trash can and The straight-line distance between the center points of the second cluster, is the sine value of the angle between the ideal extension line and the actual extension line in the first cluster, It represents the angle between the ideal extension line and the actual extension line, and its value range is 0-π / 2. It means the The set of all trash cans in the first cluster, Indicates The vertical distance from the trash can to the ideal extension line of the first cluster to which it belongs.

[0027] By determining the expression of adjusting the distance, the first clustering is corrected and the effect of the secondary clustering is improved.

[0028] Preferably, the method of allocating one or more trash bins in the corresponding second cluster to the remaining second cluster is:

[0029] Obtain the distance between the trash cans and the transfer station in the second cluster, and sort the trash cans from small to large according to the distance values ​​to obtain a distance sequence;

[0030] The volume of garbage in the garbage bins corresponding to the data points in the distance sequence is accumulated from front to back until the accumulated sum reaches the preset allocation interval;

[0031] Assign the corresponding trash bins of the remaining data points in the distance sequence to other second clustering clusters.

[0032] The category of the corresponding garbage bin is adjusted according to the garbage volume in the second cluster, so that the collection vehicle can fully collect the garbage in the corresponding optimal cluster during one garbage collection process, avoiding the phenomenon of incomplete garbage collection and improving the work efficiency of garbage collection.

[0033] Preferably, the method further comprises:

[0034] Calculate the priority value of each trash can. The priority value is positively correlated with the ratio of the volume of trash in the trash can to the capacity of the trash can.

[0035] Sort the bins according to priority values;

[0036] The volumes of the garbage in the sorted garbage bins are sequentially added up from front to back to calculate the cumulative sum of the volumes of the garbage in the garbage bins until the cumulative sum is greater than a preset processing volume threshold;

[0037] The stacked trash cans are treated as the first priority level, and the remaining trash cans are treated as the second priority level;

[0038] Clustering is performed on the garbage bins of the first priority level to obtain a plurality of first clustering clusters.

[0039] By calculating the priority value of the trash can and dividing the priority level of the trash can according to the priority value, it is convenient to plan the path of the collection vehicle, improve the work efficiency of the collection vehicle, and enable the trash can to fully collect garbage, thereby improving the work efficiency of the trash can.

[0040] Preferably, the expression of the priority value is:

[0041]

[0042] In the formula, Indicates the priority value of the current trash bin. Indicates the distance between the current trash bin and the transfer station. Indicates the volume of garbage currently in the trash can. is the current capacity of the trash can.

[0043] Preferably, the number of the first clusters is:

[0044]

[0045] In the formula, represents the number of the first cluster, Indicates the total volume of garbage that needs to be collected. represents the rounding function, is the correlation coefficient, Indicates the volume of garbage that the collection truck can collect.

[0046] The formula can be used to determine the number of clusters, so that the number of collection vehicles matches the number of clusters, fully mobilizing the collection vehicles and improving the practical efficiency of the collection vehicles.

[0047] The present invention has the following technical effects:

[0048] 1. By determining the priority level of the trash cans, clustering the trash cans of the first priority level, and cleaning the trash in the trash cans of the first priority level first, that is, cleaning the trash in the trash cans with high trash volume first to prevent the trash in the trash cans from overflowing, and temporarily ignoring the trash cans with low trash volume, thereby improving the work efficiency when cleaning the trash and ensuring that all trash cans can be used normally.

[0049] 2. Use clustering algorithms to initially cluster the trash cans according to their location distribution, and make multiple adjustments to the initial clustering results based on distance, trash volume and other characteristics to obtain the best clustering cluster. By reasonably classifying the trash, the classification results are optimized, and the trash is cleaned according to the optimal classification results to maximize work efficiency.

[0050] 3. Plan the shortest path for each garbage bin in the best cluster, and arrange the collection truck to collect garbage along the shortest path, which can make full use of the garbage collection capacity of the collection truck. At the same time, the garbage truck's walking path is the shortest when collecting garbage, which simplifies the garbage collection path planning problem and improves the efficiency and quality of garbage collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0052] Figure 1 It is a flow chart of the data interaction method of the garbage classification collection vehicle based on the Internet of Things of the present invention.

[0053] Figure 2 It is a flow chart of a method for updating a first cluster to obtain an optimal cluster according to the present invention. DETAILED DESCRIPTION

[0054] 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 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0055] It should be understood that when the terms "first", "second", etc. are used in the claims, descriptions, and drawings of the present invention, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their collections.

[0056] The embodiment of the present invention discloses a data interaction method for garbage classification collection vehicles based on the Internet of Things, referring to Figure 1 , including steps S1 to S5, which are specifically as follows:

[0057] S1: Get the distribution location of trash cans and the volume of trash.

[0058] The location information of each trash can is obtained by the positioning device installed on each trash can in the city, and the height data of the garbage in the trash can is obtained by using a sensor. The sensor is one of a laser ranging sensor, an ultrasonic sensor, a radar sensor, and a photoelectric sensor. The height data of the garbage is obtained by measurement, and then the volume of the garbage in the trash can is calculated.

[0059] During the garbage collection process, the number of garbage collection trucks available at the garbage transfer station may be insufficient. This may be caused by a variety of factors, such as: a sudden and substantial increase in the amount of garbage generated, vehicle failures, traffic congestion, and a surge in garbage volume caused by holidays. At this time, it is necessary to reasonably plan the number of collection trucks and the collection routes of the collection trucks, and give priority to collecting garbage bins with a large volume of garbage in the garbage bins to ensure that the garbage collection task is completed on time and that various resources are consumed at the lowest cost. Therefore, it is necessary to preliminarily classify the garbage bins according to the priority level. The classification process is shown below.

[0060] S2: Calculate the priority value of each trash can. The priority value is positively correlated with the ratio of the volume of trash in the trash can to the capacity of the trash can.

[0061] The expression for the priority value is:

[0062]

[0063] In the formula, Indicates the priority value of the current trash bin. Indicates the distance between the current trash bin and the transfer station. Indicates the volume of garbage currently in the trash can. is the capacity of the current trash can. The trash cans that are far away from the transfer station and have a large volume of trash have a more complicated processing process and a higher processing cost. It is necessary to collect the trash in the corresponding trash cans first to ensure that the corresponding trash cans can be used normally.

[0064] The trash cans are sorted according to the priority values; the volumes of the trash in the sorted trash cans are stacked from front to back to calculate the cumulative sum of the trash volumes in the trash cans until the cumulative sum is greater than a preset processing volume threshold; the stacked trash cans are taken as the first priority level, and the remaining trash cans are taken as the second priority level; the trash cans of the first priority level are clustered to obtain multiple first clustering clusters.

[0065] For example, the trash cans are sorted from large to small according to the priority values, and the sorted trash cans are ( , , …, ),in, , , …, ( ) corresponds to the volume of garbage in the garbage bin being less than the preset processing volume threshold, and , , …, ( ) If the volume of garbage in the corresponding garbage bin is greater than the preset processing volume threshold, , , …, Corresponding to the trash can as the first priority level, , …, Corresponding to the trash can as the second priority level, it can be understood that the garbage in the trash can of the first priority level is the trash can that needs to be collected and processed as soon as possible.

[0066] S3: Cluster the trash cans to obtain multiple first clusters.

[0067] The first priority level trash cans are clustered using the k-means clustering algorithm to obtain the first cluster. The number of the first cluster is: , where represents the number of the first cluster, Indicates the total volume of garbage that needs to be collected. It indicates the volume of garbage that can be collected by the collection truck, which can also be understood as the capacity of the collection truck. represents the rounding function, is the correlation coefficient, and its value range is 0.6-1. The purpose of selecting the coefficient is to ensure that during the process of garbage collection and cleaning by the collection vehicle, there is still a certain amount of capacity in each garbage bin to be collected and processed, so that the garbage bin can continue to hold garbage and avoid garbage overflow.

[0068] S4: Update the first cluster to obtain the best cluster.

[0069] like Figure 2 As shown, the update method is:

[0070] S41: Determine the cluster center.

[0071] Calculate the distance between the trash can and the transfer station in the first cluster to obtain the first distance value of the corresponding trash can; calculate the distance between the center point of each first cluster and the transfer station to obtain multiple second distance values, and calculate the median and the average of the multiple second distance values; calculate the absolute value of the difference between the first distance value and the mean of each trash can, and take the position of the trash can corresponding to the smallest absolute value of the difference as the cluster center.

[0072] S42: Determine the clustering adjustment distance, and cluster the trash cans again according to the preset adjustment distance to obtain a second cluster.

[0073] Construct the ideal extension line and the actual extension line, connect the center point of the first cluster and the trash can farthest from the transfer station to obtain the first line segment; connect the center point of the first cluster and the trash can closest to the transfer station to obtain the second line segment; connect the midpoint of the first line segment and the midpoint of the second line segment to obtain the actual extension line, and connect the transfer station and the center point of the first cluster to obtain the ideal extension line. The expression for adjusting the distance is:

[0074]

[0075] in, Indicates Trash bin and its The adjusted distance of the second cluster center, It is The center point of the second cluster, It is A trash can and The straight-line distance between the center points of the second cluster, is the sine value of the angle between the ideal extension line and the actual extension line in the first cluster, It represents the angle between the ideal extension line and the actual extension line, and its value range is 0-π / 2. It means the The set of all trash cans in the first cluster, Indicates The vertical distance from the trash can to the ideal extension line of the first cluster to which it belongs. According to the determined cluster center and the adjustment distance formula, the trash cans are clustered again to obtain the second cluster.

[0076] Indicates The coordinates of the trash can. represents the coordinates of the cluster center of the second cluster. The direction of the actual extension line reflects the distribution of the farthest and nearest garbage bins in the first cluster relative to the garbage transfer station. When , the distance between the trash can and the cluster to which it belongs is calculated. and . Reflects the degree of deviation of the trash can from the ideal reference line in the first cluster to which it belongs. It reflects the deviation between the actual extension line and the ideal extension line in the current first cluster. The larger the value is, the more the actual extension line of the first cluster needs to be adjusted. The larger the The farther the distance between the first trash can and the ideal reference line is, the The trash cans are at the edge of the cluster, so The larger the The trash cans are assigned to other second clusters, which plays a corrective role on the current first cluster.

[0077] S43: Adjust the second cluster to obtain the best cluster.

[0078] Calculate the sum of the garbage volumes of the garbage bins in each second cluster, and determine whether the maximum value of the sum of the garbage volumes is greater than the right end point of the preset allocation interval. If so, allocate one or more garbage bins in the corresponding second cluster to the remaining second clusters so that the sum of the garbage volumes in the garbage bins in the second cluster corresponding to the maximum value is within the preset allocation interval. If not, it indicates that the sum of the garbage volumes of the garbage bins in all the second clusters does not exceed the right end point of the allocation interval. At this time, all the second clusters are regarded as the best clusters.

[0079] Specifically, the distance between the trash cans and the transfer station in the second cluster is obtained, and the trash cans are sorted from small to large according to the distance value to obtain a distance sequence; the garbage volumes in the trash cans corresponding to the data points in the distance sequence are accumulated from front to back until the accumulated sum reaches a preset allocation interval; the trash cans corresponding to the remaining data points in the distance sequence are allocated to other second clusters.

[0080] For example, the trash cans in the second cluster with the largest trash volume and a trash volume greater than the right end point of the allocation interval are sorted, and the sorted trash cans are respectively ( , , …, ),in, , , …, If the accumulated sum is within the preset allocation interval, , …, The corresponding trash cans are allocated to other second clusters. It should be noted here that when allocating trash cans to other second clusters, the distance between the trash cans and the centers of the other second clusters is first calculated, and the trash cans are allocated to the nearest second cluster. The allocation interval is set according to the volume of trash that the collection vehicle can carry. The allocation interval represents the amount of trash that a vehicle can carry at one time. For example, if the volume of trash that the collection vehicle can carry is a~b cubic meters, the allocation interval can be set to (a, b), where a≥0.

[0081] Repeat the calculation and determination of the garbage volumes in the remaining second clusters until the garbage volumes in all second clusters are within the preset allocation interval, and take the second clusters whose garbage volumes are finally within the preset allocation interval as the best cluster.

[0082] Exemplarily, the second cluster is ( , , , ),in, The garbage volume in is the largest and the garbage volume value is greater than the right endpoint of the allocation interval. The trash cans in the , , Then recalculate , , If the volume of garbage in The garbage volume in the distribution interval is the largest and the garbage volume value is greater than the right endpoint of the distribution interval. Sort the trash bins in the Some of the trash cans in the , Then continue to calculate , until the garbage volume in all clusters is within the preset allocation interval, and the final , , , As the best cluster, if The garbage volume in the distribution interval is the largest, but the garbage volume is inside the distribution interval or is smaller than the left endpoint of the distribution interval, then no more Sort the trash cans in the , , , as the best cluster.

[0083] S5: Use the collection vehicle to transport the garbage in the garbage bins in the best cluster to the transfer station.

[0084] Calculate the distance of all paths that the collection vehicle takes from the garbage transfer station to all garbage bins in the best cluster, passing each garbage bin only once, and finally returns to the garbage transfer station. The shortest path is taken as the actual route of the collection vehicle. Finally, arrange the collection vehicle to start from the garbage transfer station, collect and transport the garbage from all garbage bins contained in the best cluster, and return to the garbage transfer station.

[0085] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

[0086] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A data interaction method for garbage classification collection vehicles based on the Internet of Things, characterized in that: include: Obtain the distribution location and garbage volume of the garbage bins, cluster the garbage bins to obtain multiple first clusters, and update the first clusters to obtain the best cluster; Transport the garbage in the garbage bins in the best cluster to the transfer station; The method for updating the first cluster to obtain the best cluster is: The trash cans are clustered again with the location of any trash can in the first cluster as the cluster center to obtain multiple second clusters; Calculate the sum of the garbage volumes of the garbage bins in each second cluster, and determine whether the maximum value of the sum of the garbage volumes is greater than the right end point of the preset allocation interval. If so, allocate one or more garbage bins in the corresponding second cluster to the remaining second clusters so that the sum of the garbage volumes in the garbage bins in the second cluster corresponding to the maximum value is within the preset allocation interval. Repeat the calculation and determination of the garbage volumes in the remaining second clusters until the garbage volumes in all the second clusters are within the preset allocation interval, and take the second cluster whose sum of garbage volumes is finally within the preset allocation interval as the best cluster; The method of clustering the trash cans again with the location of any trash can in the first cluster as the cluster center is: Calculate the distance between the trash can in the first cluster and the transfer station to obtain a first distance value of the corresponding trash can; Calculate the distance between each first cluster center point and the transfer station to obtain multiple second distance values, and calculate the median and the average of the multiple second distance values; Calculate the absolute value of the difference between the first distance value and the mean of each trash can, take the location of the trash can corresponding to the absolute value of the difference with the smallest value as the cluster center, and cluster the trash cans again according to the preset adjustment distance; The expression for adjusting the distance is: in, Indicates Trash bin and its The adjusted distance of the second cluster center, It is The center point of the second cluster, It is A trash can and The straight-line distance between the center points of the second cluster, is the sine value of the angle between the ideal extension line and the actual extension line in the first cluster, It represents the angle between the ideal extension line and the actual extension line, and its value range is 0-π / 2. It means the The set of all trash cans in the first cluster, Indicates The vertical distance from the trash can to the ideal extension line of the first cluster to which it belongs; The method for constructing the ideal extension line and the actual extension line is as follows: Connect the center point of the first cluster and the trash can farthest from the transfer station to obtain the first line segment; Connect the center point of the first cluster and the trash can closest to the transfer station to obtain a second line segment; Connect the midpoint of the first line segment and the midpoint of the second line segment to obtain the actual extension line, and connect the transfer station and the center point to obtain the ideal extension line; The step of clustering the trash cans to obtain a plurality of first clusters includes: Calculate the priority value of each trash can. The priority value is positively correlated with the ratio of the volume of trash in the trash can to the capacity of the trash can. Sort the bins according to priority values; The volumes of the garbage in the sorted garbage bins are sequentially added up from front to back to calculate the cumulative sum of the volumes of the garbage in the garbage bins until the cumulative sum is greater than a preset processing volume threshold; The stacked trash cans are treated as the first priority level, and the remaining trash cans are treated as the second priority level; Clustering the trash bins of the first priority level to obtain a plurality of first clustering clusters; The expression for the priority value is: In the formula, Indicates the priority value of the current trash bin. Indicates the distance between the current trash bin and the transfer station. Indicates the volume of garbage currently in the trash can. is the current capacity of the trash can.

2. The data interaction method for garbage classification and collection vehicles based on the Internet of Things according to claim 1 is characterized in that: The method of allocating one or more trash bins in the corresponding second cluster to the remaining second clusters is: Obtain the distance between the trash cans and the transfer station in the second cluster, and sort the trash cans from small to large according to the distance values ​​to obtain a distance sequence; The volume of garbage in the garbage bins corresponding to the data points in the distance sequence is accumulated from front to back until the accumulated sum reaches the preset allocation interval; Assign the corresponding trash bins of the remaining data points in the distance sequence to other second clustering clusters.

3. The data interaction method for garbage classification and collection vehicles based on the Internet of Things according to claim 1 is characterized in that: The number of the first cluster is: In the formula, represents the number of the first cluster, Indicates the total volume of garbage that needs to be collected. represents the rounding function, is the correlation coefficient, ranging from 0.6 to 1. Indicates the volume of garbage that the collection truck can collect.

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