Identification method, device, system and storage medium for illegal waste disposal sites

Abstract

The present invention discloses a method, device, system and storage medium for identifying illegal disposal sites. The method comprises: step S11: obtaining multiple unloading locations of multiple transport vehicles on an electronic map, and taking each unloading location as a tracking location point; step S12: identifying whether the density of multiple tracking location points in a certain area on the electronic map reaches a first preset condition. If so and the area has not applied for disposal filing, the area is identified as an illegal disposal site. The present invention obtains multiple unloading locations of multiple transport vehicles. If the density of a certain area of ​​the multiple unloading locations reaches a predetermined condition, the area is used as a suspected location of an illegal disposal site, thereby overcoming the technical problem of manually searching for illegal disposal sites in the prior art and realizing automatic reporting of the location of illegal disposal sites. The present invention can be widely used in urban construction waste treatment.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a method, device, system and storage medium for identifying illegal disposal sites. Background Art

[0002] Illegal disposal sites refer to disposal sites that have not been reported to the regulatory authorities. Normally, waste generated by construction sites must be approved by the regulatory authorities before being transported from the construction site to the disposal site designated at the time of declaration. However, in reality, there may be illegal discharges, that is, construction sites transport waste to an unregistered location (i.e., illegal disposal sites) without reporting, causing chaos in urban management and prone to landslide accidents.

[0003] At present, the detection methods of illegal construction waste disposal sites are basically through reports from citizens, construction units and regulatory agencies, and after suspected illegal disposal sites are found, the regulatory authorities will investigate and collect evidence. However, this method has a small detection area, is random and has a low accuracy rate, and requires a large human cost for investigation and detection.

[0004] Therefore, in the field of intelligent supervision of construction waste, how to design a method to detect illegal disposal sites has become a technical problem that needs to be solved urgently. With the continuous development of Internet of Things technology, more and more intelligent hardware is used in computer application systems. The system can make full use of the navigation and positioning function of construction waste transport vehicles, extract and analyze the number, real-time positioning, driving trajectory and other data of waste transport vehicles, and analyze whether the geographical area where the transport vehicle enters and exits is a registered disposal site, thereby constructing a detection method for illegal construction waste disposal sites. Summary of the invention

[0005] The present invention aims to solve one of the technical problems in the related art at least to a certain extent. To this end, one object of the present invention is to provide a method, device, system and storage medium for identifying illegal waste disposal sites, which can automatically identify the location of illegal waste disposal sites using software methods.

[0006] The technical solution adopted by the present invention is:

[0007] In a first aspect, the present invention provides a method for identifying an illegal disposal site, the method comprising: step S11: obtaining multiple unloading locations of multiple transport vehicles on an electronic map, and taking each unloading location as a tracking location point; step S12: identifying whether the density of multiple tracking location points in a certain area on the electronic map reaches a first preset condition, and if so, identifying the area as an illegal disposal site.

[0008] Among them, step S12 includes: traversing the multiple tracking position points to find all the core areas, and the core area is defined as: obtaining an area with the current tracking position point as the center and the first value as the radius, if the total number of tracking position points in the area is greater than a preset first threshold, then the area is determined to be a core area; traversing each core area of ​​all the core areas to find the cluster corresponding to the current core area, if the cluster is not empty and the cluster queue does not contain the cluster, then the cluster is sent to the cluster queue, and the cluster is defined as: a set of core areas that have a specific relationship with the current core area; traversing each cluster in the cluster queue, counting the total number of tracking position points contained in each cluster, if the total number of tracking position points is greater than or equal to a preset second threshold, then the area corresponding to the cluster is determined to be an illegal consumption field.

[0009] Among them, the specific relationship includes the following types: the first type is a density direct relationship, and the definition of the density direct relationship is: if the center position of the second core area B is within the range of the first core area A, then the second core area B is determined to have a density direct relationship with the first core area A; the second type is a density connection relationship, and the definition of the density connection relationship is: if the first core area A and the second core area B have the density direct relationship, and the third core area C and the second core area B have the density direct relationship, then the third core area C and the first core area A are determined to be the density connection relationship; the third type is a density reachable relationship, and the definition of the density reachable relationship is: if the first core area A and the second core area B have the density direct relationship, the third core area C and the second core area B have the density direct relationship, the fourth core area D and the third core area C have the density direct relationship, ... and so on, the Nth core area N and the N-1th core area M have the density direct relationship, then the Nth core area N and the N-1th core area M are determined to be the density reachable relationship.

[0010] Among them, step S11 includes: monitoring the running track of each transport vehicle on the electronic map, and simultaneously monitoring the real-time running big data of each transport vehicle; if the real-time running big data meets the preset second condition, then determining that the current position of the transport vehicle on the electronic map is the unloading position of the transport vehicle.

[0011] Among them, the operation big data includes: load data and the tilt angle of the carriage; if the real-time operation big data meets the preset second condition, then the current position of the transport vehicle is determined to be the unloading position of the transport vehicle, including: if at a certain position of the operation trajectory, it is monitored that the load data becomes smaller and the tilt angle of the carriage has changed, then the position is determined to be the unloading position.

[0012] In a second aspect, the present invention provides an illegal disposal site identification device, which includes: a tracking location point acquisition module, used to obtain multiple unloading locations of multiple transport vehicles on an electronic map, and take each unloading location as a tracking location point; an illegal disposal site identification module, used to identify whether the density of multiple tracking location points in a certain area on the electronic map reaches a first preset condition, and if so, identify the area as an illegal disposal site.

[0013] Among them, the tracking location point acquisition module includes: a data monitoring unit, which is used to monitor the running track of each transport vehicle on the electronic map, and simultaneously monitor the real-time running big data of each transport vehicle; an unloading position determination unit, which is used to determine that the current position of the transport vehicle on the electronic map is the unloading position of the transport vehicle if the real-time running big data meets a preset second condition.

[0014] Among them, the illegal consumption field identification module includes: a core area search unit, which is used to traverse the multiple tracking position points and find all the core areas. The core area is defined as: obtaining an area with the current tracking position point as the center and the first value as the radius. If the total number of tracking position points in the area is greater than a preset first threshold, the area is determined to be a core area; a cluster search unit, which is used to traverse all the core areas and find the cluster corresponding to each core area. If the cluster is not empty and the cluster queue does not contain the cluster, the cluster is sent to the cluster queue. The cluster is defined as: a set of core areas that have a specific relationship with the current core area; an illegal consumption field determination unit, which is used to traverse the cluster queue and count the total number of tracking position points contained in each cluster of the cluster queue. If the total number of tracking position points is greater than or equal to a preset second threshold, the area corresponding to the cluster is determined to be an illegal consumption field.

[0015] In the third aspect, the present invention provides an identification system for illegal disposal sites, the identification system comprising: a plurality of identification terminals, the identification terminal being installed on a transport vehicle, the identification terminal being equipped with a GPS positioning device, a weight sensor and a car tilt angle sensor, the identification terminal transmitting data collected in real time by the GPS positioning device, the weight sensor and the car tilt angle sensor to the server; a server having a computer executable program, the computer executable program being used to execute the method as described above.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method as described above.

[0017] The beneficial effects of the present invention are:

[0018] The present invention obtains multiple unloading locations of multiple transport vehicles on an electronic map. If the density of multiple unloading locations in a certain area reaches a predetermined condition, the area is identified as an illegal disposal site. This overcomes the technical problem in the prior art of requiring manual search for illegal disposal sites and realizes automatic reporting of the location of illegal disposal sites. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of an embodiment of a method for identifying an illegal waste disposal site of the present invention;

[0020] Figure 2 yes Figure 1 A flowchart of an embodiment of step S11;

[0021] Figure 3 yes Figure 1 A schematic diagram of the structure of multiple tracking location points on the electronic map in step S11;

[0022] Figure 4 yes Figure 1 A schematic flow chart of an embodiment of step S12;

[0023] Figure 5 It is a structural schematic diagram of an embodiment of a device for identifying illegal disposal sites of the present invention.

[0024] Figure 6 yes Figure 5 A schematic structural diagram of an embodiment of a tracking position point module 51;

[0025] Figure 7 yes Figure 5 A schematic structural diagram of an embodiment of an illegal consumption field identification module 52;

[0026] Figure 8 It is a structural schematic diagram of an embodiment of the illegal consumption site identification system of the present invention. DETAILED DESCRIPTION

[0027] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other.

[0028] Embodiment 1

[0029] See also Figure 1 , Figure 1 FIG. 1 is a flow chart of an embodiment of a method for identifying illegal waste disposal sites of the present invention. Figure 1 As shown, the identification method is executed on the server and includes the steps of:

[0030] S11 obtains multiple unloading locations of multiple transport vehicles on an electronic map, and uses each unloading location as a tracking location point;

[0031] The electronic map is an electronic map of the suspected illegal waste disposal area. If the superior regulatory department receives a certain area, such as an area near the Xili Sub-district Office in Nanshan District, Shenzhen, as a suspected illegal waste disposal area, the electronic map of the area will be obtained.

[0032] See also Figure 2 , Figure 2 yes Figure 1 A flow chart of an embodiment of step S11. Figure 2 As shown, step S11 includes the steps of:

[0033] S111 monitors the running track of each transport vehicle on the electronic map, and simultaneously monitors the real-time big data of the operation of each transport vehicle;

[0034] Among them, the real-time operation big data includes: load data and car body angle tilt data. GPS positioning devices, weight sensors and car body tilt angle sensors can be installed on transport vehicles such as mud trucks to obtain the location information, load data and car body tilt angle of the transport vehicle at regular intervals. Specifically, the time interval can be 1S, 2S or 3S, which is not limited here. The transport vehicle is also provided with a collection terminal, which is used to regularly collect the location information, load data, car body tilt angle and other data of the transport vehicle, and transmit the data to the server. Optionally, the server marks the operation track of the transport vehicle on the electronic map according to the correspondence between the electronic map and the actual position of the transport vehicle.

[0035] S112. If the real-time operation big data meets the preset second condition, it is determined that the current position of the transport vehicle on the electronic map is the unloading position of the transport vehicle.

[0036] If the real-time operation big data meets the preset second condition, determining that the current position of the transport vehicle on the electronic map is the unloading position of the transport vehicle includes: if at the current position, the load data is monitored to be smaller and the tilt angle of the carriage has changed, then determining that the current position is the unloading position of the transport vehicle. Figure 3 On the electronic map, at point A, the load data of a transport vehicle is monitored to decrease from 1000KG to less than 10KG, and the inclination angle of the carriage has changed at point A, such as from horizontal 0 degrees to 90 degrees and then to 0 degrees, so point A is determined to be the unloading position of the transport vehicle. Using the same method, you can also find out the unloading positions B, C, D and other positions of other transport vehicles on the electronic map.

[0037] It should be noted here that for the same transport vehicle, there may be multiple unloading locations on the electronic map, that is, unloading locations A, B, C, and D may be the unloading locations left by the same transport vehicle, or they may be the unloading locations left by 2, 3 or even 4 transport vehicles.

[0038] Optionally, the unloading location is marked on an electronic map. Figure 3 As shown, a cart is used to identify an unloading location.

[0039] S12: Identify whether the density of the plurality of tracking location points in a certain area on the electronic map reaches a first preset condition, and if so, identify the area as an illegal disposal site.

[0040] See also Figure 4 , Figure 4 yes Figure 1 A flow chart of an embodiment of step S12. Figure 4 As shown, step S12 includes the steps of:

[0041] S121: traverse the multiple tracking position points to find all core areas;

[0042] The core area is defined as: obtaining an area with the current tracking position point as the center and the first value as the radius, and if the total number of tracking position points in the area is greater than a preset first threshold, determining the area as the core area.

[0043] like Figure 3 As shown, Figure 3 Four core areas are shown, each of which is formed by tracking position points A, B, C, and D. Each core area is centered on each tracking position point and has a radius of Eps. In each core area, the total number of tracking position points is greater than the first threshold value 5. Each core area is named after the tracking position point at its center. These four core areas are called core areas A, B, C, and D.

[0044] S122: traverse all the core areas to find the cluster corresponding to each core area, and if the cluster is not empty and the cluster queue does not contain the cluster, send the cluster to the cluster queue;

[0045] The cluster is defined as a set of core regions that have a specific relationship with the current core region.

[0046] The specific relationships include the following types:

[0047] The first type is a density direct relationship, which is defined as follows: if the center position of the second core region B is within the range of the first core region A, then it is determined that the second core region B has a density direct relationship with the first core region A. Figure 3As shown, core area A and core area B are in a density direct relationship, core area B and core area C are in a density direct relationship, and core area C and core area D are in a density direct relationship.

[0048] The second type is a density connection relationship, which is defined as: if the first core area A and the second core area B have the density direct relationship, and the third core area C and the second core area B have the density direct relationship, then it is determined that the third core area C and the first core area A are in the density connection relationship. Figure 3 As shown, core area A and core area C are density-connected.

[0049] The third type is the density reachable relationship, which is defined as: if the first core area A and the second core area B have the density direct relationship, the third core area C and the second core area B have the density direct relationship, the fourth core area D and the third core area C have the density direct relationship, and so on, the Nth core area N and the N-1th core area M have the density direct relationship, then it is determined that the Nth core area N and the N-1th core area M are in the density reachable relationship. Figure 3 As shown, core area A and core area D are in a density-reachable relationship.

[0050] Taking core area A as an example, the clusters corresponding to core area A are: core area B that is directly accessible to core area A by density, core area C that is densely connected to core area A by density, and core area D that is densely accessible to core area A by density.

[0051] Taking core area B as an example, the cluster corresponding to core area B is: including core areas A and C that are directly connected to core area B by density, and core area D that is densely connected to core area B.

[0052] Taking core area C as an example, the cluster corresponding to core area C is: including core areas B and D that are directly connected to core area C by density, and core area A that is densely connected to core area C.

[0053] Taking core area D as an example, the clusters corresponding to core area D are: core area C that is directly accessible to core area D, core area B that is densely connected to core area D, and core area A that is densely accessible to core area D.

[0054] It can be seen from the above that the clusters corresponding to the core areas A, B, C, and D are the same cluster, which is a set of areas including core area A, core area B, core area C, and core area D. The cluster is sent to the cluster queue. The cluster queue is denoted as C k Represents each cluster in the cluster array.

[0055] S123: traverse the cluster queue, count the total number of tracking position points contained in each cluster of the cluster queue, and if the total number of tracking position points is greater than or equal to a preset second threshold, determine that the area corresponding to the cluster is an illegal consumption field.

[0056] In step S123, for example, cluster C i If the total number of tracking position points contained in is greater than the preset second threshold N, the area corresponding to the cluster is determined to be an illegal consumption field. For example, if the total number of tracking position points contained in cluster C1 including core areas A, B, C, and D formed in step S122 is 162 times, and the second threshold is 20 times, the area corresponding to cluster C1 is determined to be an illegal consumption field.

[0057] Embodiment 2

[0058] See also Figure 5 , Figure 5 FIG. 1 is a schematic diagram of the structure of an embodiment of the device for identifying illegal waste disposal sites of the present invention. Figure 5 As shown, the device includes a tracking location point acquisition module 51 and an illegal consumption site identification module 52.

[0059] like Figure 6 As shown, the tracking location point acquisition module 51 includes a data monitoring unit 511 and an unloading location determination unit 512. The data monitoring unit 511 is used to monitor the running track of each transport vehicle on the electronic map, and simultaneously monitor the real-time running big data of each transport vehicle. The unloading location determination unit 512 is used to determine that the current position of the transport vehicle on the electronic map is the unloading location of the transport vehicle if the real-time running big data meets the preset second condition.

[0060] like Figure 7 As shown, the illegal consumption field identification module 52 includes a core area search unit 521, a cluster search unit 522 and an illegal consumption field determination unit 523. The core area search unit 521 is used to traverse the multiple tracking position points to find all the core areas. The definition of the core area is: obtain an area with the current tracking position point as the center and the first value as the radius. If the total number of tracking position points in the area is greater than the preset first threshold, the area is determined to be a core area. The cluster search unit 522 is used to traverse all the core areas to find the cluster corresponding to each core area. If the cluster is not empty and the cluster queue does not contain the cluster, the cluster is sent to the cluster queue. The cluster is defined as: a set of core areas with a specific relationship with the current core area. The illegal consumption field determination unit 523 is used to traverse the cluster queue, count the total number of tracking position points contained in each cluster of the cluster queue, and if the total number of tracking position points is greater than or equal to the preset second threshold, the area corresponding to the cluster is determined to be an illegal consumption field.

[0061] The working methods of each module have been described in detail in the first embodiment and will not be repeated here.

[0062] Embodiment 3

[0063] The present invention also provides an identification system for illegal consumption sites, the identification system comprising: a plurality of identification terminals and a server that can communicate with the plurality of identification terminals.

[0064] Each identification terminal is installed on each transport vehicle, and is equipped with a GPS positioning device, a weight sensor and a car body tilt angle sensor. The identification terminal transmits the data collected by the GPS positioning device, the weight sensor and the car body tilt angle sensor in real time to the server.

[0065] The server has a computer executable program, and the computer executable program is used to execute the method as described in the above embodiment 1.

[0066] Embodiment 4

[0067] The present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method described in the first embodiment.

[0068] In summary, the present invention provides a method, device, system and storage medium for identifying illegal disposal sites, which can intelligently identify the locations of illegal disposal sites without the need for manual on-site identification at each suspected location, thereby facilitating management by municipal management personnel.

[0069] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for identifying illegal consumption sites, characterized in that: include: Step S11: obtaining multiple unloading locations of multiple transport vehicles on the electronic map, and taking each unloading location as a tracking location point; Step S12: Identify whether the density of multiple tracking location points in a certain area on the electronic map reaches a first preset condition, and if so, identify the area as an illegal consumption site. The step S12 comprises: Traversing the multiple tracking position points to find all core areas, where the core area is defined as: obtaining an area with the current tracking position point as the center and a first value as the radius, and if the total number of tracking position points in the area is greater than a preset first threshold, determining that the area is a core area; Traversing all the core areas, finding the cluster corresponding to each core area, and if the cluster is not empty and the cluster queue does not contain the cluster, sending the cluster to the cluster queue, wherein the cluster is defined as: a set of core areas having a specific relationship with the current core area; Traversing the cluster queue, counting the total number of tracking location points contained in each cluster of the cluster queue, and if the total number of tracking location points is greater than or equal to a preset second threshold, determining that the area corresponding to the cluster is an illegal consumption field; The specific relationships include the following types: The first type is a density direct relationship, which is defined as follows: if the center position of the second core area B is within the range of the first core area A, it is determined that the second core area B has a density direct relationship with the first core area A; The second type is a density connection relationship, and the density connection relationship is defined as: if the first core area A and the second core area B have the density direct relationship, and the third core area C and the second core area B have the density direct relationship, then it is determined that the third core area C and the first core area A are in the density connection relationship; The third type is a density-reachable relationship, which is defined as: if the first core area A and the second core area B have the density-reachable relationship, the third core area C and the second core area B have the density-reachable relationship, the fourth core area D and the third core area C have the density-reachable relationship, and so on, the Nth core area N and the N-1th core area M have the density-reachable relationship, then it is determined that the Nth core area N and the N-1th core area M are in the density-reachable relationship.

2. The method according to claim 1, characterized in that The step S11 comprises: Monitor the running track of each transport vehicle on the electronic map, and simultaneously monitor the real-time big data of the running of each transport vehicle; If the real-time operation big data meets a preset second condition, the current position of the transport vehicle on the electronic map is determined to be the unloading position of the transport vehicle.

3. The method according to claim 2, characterized in that The real-time operation big data includes: load data and carriage tilt angle; If the real-time operation big data meets the preset second condition, then determining that the current position of the transport vehicle is the unloading position of the transport vehicle includes: if at a certain position on the operation trajectory, it is monitored that the load data becomes smaller and the inclination angle of the carriage changes, then determining that the position is the unloading position.

4. A device for identifying illegal waste disposal sites, characterized in that: include: A tracking location point acquisition module is used to acquire multiple unloading locations of multiple transport vehicles on an electronic map, and each unloading location is used as a tracking location point; An illegal consumption site identification module, used to identify whether the density of multiple tracking location points in a certain area on the electronic map reaches a first preset condition, and if so, identify the area as an illegal consumption site; The illegal consumption site identification module includes: a core area search unit, configured to traverse the plurality of tracking position points and find all core areas, wherein the core area is defined as: obtaining an area with the current tracking position point as the center and a first value as the radius, and determining that the area is a core area if the total number of tracking position points in the area is greater than a preset first threshold; a cluster search unit, configured to traverse all the core regions, find a cluster corresponding to each core region, and if the cluster is not empty and the cluster queue does not contain the cluster, send the cluster to the cluster queue, wherein the cluster is defined as: a set of core regions having a specific relationship with the current core region; An illegal consumption field determination unit is used to traverse the cluster queue, count the total number of tracking position points contained in each cluster of the cluster queue, and if the total number of tracking position points is greater than or equal to a preset second threshold, determine that the area corresponding to the cluster is an illegal consumption field; The specific relationships include the following types: The first type is a density direct relationship, which is defined as follows: if the center position of the second core area B is within the range of the first core area A, it is determined that the second core area B has a density direct relationship with the first core area A; The second type is a density connection relationship, and the density connection relationship is defined as: if the first core area A and the second core area B have the density direct relationship, and the third core area C and the second core area B have the density direct relationship, then it is determined that the third core area C and the first core area A are in the density connection relationship; The third type is a density-reachable relationship, which is defined as: if the first core area A and the second core area B have the density-reachable relationship, the third core area C and the second core area B have the density-reachable relationship, the fourth core area D and the third core area C have the density-reachable relationship, and so on, the Nth core area N and the N-1th core area M have the density-reachable relationship, then it is determined that the Nth core area N and the N-1th core area M are in the density-reachable relationship.

5. The identification device according to claim 4, characterized in that: The tracking position point acquisition module includes: A data monitoring unit, used to monitor the running track of each transport vehicle on the electronic map, and simultaneously monitor the real-time big data of the running of each transport vehicle; The unloading position determination unit is used to determine that the current position of the transport vehicle on the electronic map is the unloading position of the transport vehicle if the real-time operation big data meets a preset second condition.

6. A system for identifying illegal waste disposal sites, characterized in that: include: A plurality of identification terminals and servers, wherein the identification terminal is installed on a transport vehicle, and is equipped with a GPS positioning device, a weight sensor, and a car body tilt angle sensor, and the identification terminal transmits data collected in real time by the GPS positioning device, the weight sensor, and the car body tilt angle sensor to the server, and the server has a computer executable program, and the computer executable program is used to execute the method as claimed in any one of claims 1 to 3.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method according to any one of claims 1 to 3.

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