CN113821735A - Method, device, equipment and storage medium for identifying illegal refueling station - Google Patents
Method, device, equipment and storage medium for identifying illegal refueling station Download PDFInfo
- Publication number
- CN113821735A CN113821735A CN202110951374.1A CN202110951374A CN113821735A CN 113821735 A CN113821735 A CN 113821735A CN 202110951374 A CN202110951374 A CN 202110951374A CN 113821735 A CN113821735 A CN 113821735A
- Authority
- CN
- China
- Prior art keywords
- refueling
- stop
- vehicle
- preset
- station
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 53
- 230000002159 abnormal effect Effects 0.000 claims abstract description 65
- 238000012216 screening Methods 0.000 claims abstract description 12
- 238000003064 k means clustering Methods 0.000 claims description 4
- 230000006872 improvement Effects 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 7
- 238000004590 computer program Methods 0.000 description 5
- 230000006399 behavior Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000007405 data analysis Methods 0.000 description 3
- 230000008030 elimination Effects 0.000 description 2
- 238000003379 elimination reaction Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 239000004566 building material Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/906—Clustering; Classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Navigation (AREA)
Abstract
The invention discloses a method, a device, equipment and a storage medium for identifying illegal refueling sites, wherein the method comprises the following steps: matching the stop data of the vehicle with the interest point data to obtain a stop data set of a gas station; screening abnormal refueling vehicles which are not in the gas station stop data set according to the track data in a preset time period of the vehicles; clustering the stop points of the abnormal refueling vehicles, and taking a clustering area which does not contain a preset interest point as an abnormal area; and judging whether the vehicles in the abnormal area meet a preset refueling condition or not, and if so, determining that the abnormal area is an illegal refueling station. According to the method for identifying the illegal refueling station, the illegal refueling station can be automatically identified, so that a powerful basis is provided for hitting the illegal refueling station, and a technical means is provided for centralized improvement and treatment of the finished oil market.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a method, a device, equipment and a storage medium for identifying an illegal refueling station.
Background
The illegal refueling station is hidden in places and modes and mainly focuses on urban and rural junctions, national road sections and the like, the illegal refueling station is simple and crude in facilities, small in scale and low in investment, generally sold by renting resident bungalow or old factories, and the illegal refueling station obtains the customer source in modes of old people, large tool cars with large oil consumption on construction sites and the like, is hidden for a long time and is difficult to find in dark operation.
In order to further eliminate the hidden danger of safety accidents, guarantee the life and property safety of people, standardize the operation order of the finished oil market and seriously strike various behaviors of illegally building refueling sites, therefore, the technical problem of accurately and rapidly identifying the illegally operated refueling sites is urgently needed to be solved by technical personnel in the field.
Disclosure of Invention
The embodiment of the disclosure provides a method, a device, equipment and a storage medium for identifying an illegal refueling station. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In a first aspect, an embodiment of the present disclosure provides a method for identifying an illegal refueling station, including:
matching the stop data of the vehicle with the interest point data to obtain a stop data set of a gas station;
screening abnormal refueling vehicles which are not in a gas station stop data set according to the track data in a preset time period of the vehicles;
clustering stop points of the vehicles refueling abnormally, and taking a clustering area not containing preset interest points as an abnormal area;
and judging whether the vehicles in the abnormal area meet the preset refueling condition or not, and if so, determining that the abnormal area is an illegal refueling station.
In an optional embodiment, before the step of matching the stop data of the vehicle with the point of interest data to obtain the gas station stop data set, the method further includes:
acquiring track data and national interest point data of vehicles;
and judging whether the vehicle stops according to the time information and the speed information in the track data to obtain stop data of the vehicle.
In an optional embodiment, matching the stop data of the vehicle with the point of interest data to obtain a gas station stop data set includes:
calculating the distance between the target stop point and the gas station interest point contained in the area where the target stop point is located;
and when the distance is smaller than the preset distance threshold value and the stop time length is within the first preset stop time length interval, the target stop point stops for the gas station, and the target stop point is added into the stop data set of the gas station.
In an optional embodiment, screening abnormal refueling vehicles not in the gas station stop data set according to the trajectory data within the preset time period of the vehicle comprises:
calculating the operation mileage of the vehicle and the stop point of the vehicle according to the track data in the preset time period of the vehicle;
when the operating mileage is more than or equal to the preset operating mileage, the vehicle is an operating vehicle;
when none of the operating vehicle stop points are located in the gas station stop data set, the operating vehicle is an abnormally refueled vehicle.
In an optional embodiment, clustering the stop points of the abnormally-fueled vehicle, and taking a clustering region not containing the preset interest point as the abnormal region, includes:
clustering the stop points of the abnormal refueling vehicles by a k-means clustering algorithm to obtain a plurality of clustering areas;
and acquiring the interest point type in each clustering area, and taking the clustering area not containing the preset interest point as an abnormal area.
In an optional embodiment, the determining whether the vehicle in the abnormal region meets a preset refueling condition, and if the preset refueling condition is met, determining that the abnormal region is an illegal refueling station includes:
calculating the parking time and the parking times of the vehicle in the abnormal area;
when the parking time of the vehicle is in the second preset parking time interval and the parking times are in the preset parking time interval, the vehicle is a suspected illegal refueling vehicle;
and when the number of suspected illegal refueling vehicles in the abnormal area is within the preset number interval, the abnormal area is an illegal refueling station.
In an optional embodiment, after the illegal refueling station is identified, the method further comprises the following steps:
acquiring the geographical position information of the illegal refueling station;
and sending the geographical position information to the user terminal for display.
In a second aspect, an embodiment of the present disclosure provides an apparatus for identifying an illegal refueling station, including:
the matching module is used for matching the stop data of the vehicle with the interest point data to obtain a stop data set of the gas station;
the screening module is used for screening abnormal refueling vehicles which are not in the gas station stop data set according to the track data in the preset time period of the vehicles;
the clustering module is used for clustering stop points of the abnormal refueling vehicles and taking a clustering area which does not contain a preset interest point as an abnormal area;
and the identification module is used for judging whether the vehicles in the abnormal area meet the preset refueling condition or not, and if the preset refueling condition is met, the abnormal area is an illegal refueling station.
In a third aspect, the disclosed embodiments provide an apparatus for identifying an illegal fueling station, including a processor and a memory storing program instructions, where the processor is configured to execute the method for identifying an illegal fueling station provided by the above embodiments when executing the program instructions.
In a fourth aspect, the disclosed embodiments provide a computer readable medium having stored thereon computer readable instructions executable by a processor to implement a method for identifying an illegal fueling station as provided by the above embodiments.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the illegal refueling station identification method provided by the embodiment of the disclosure, data analysis is performed through recent travel track data of a truck and POI (Point of Interest) data of national gas stations, and the illegal refueling station is automatically identified through technical means such as stop Point clustering and elimination, so that a powerful basis is provided for hitting the illegal refueling station, and a technical means is provided for centralized improvement and treatment of a finished oil market.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic flow chart illustrating a method of identifying illegal fueling stations in accordance with an exemplary embodiment;
FIG. 2 is a schematic diagram illustrating a method of identifying an illegal refueling station in accordance with an exemplary embodiment;
FIG. 3 is a diagram illustrating an illegal fueling station identification according to an exemplary embodiment;
FIG. 4 is a schematic diagram illustrating an arrangement for identifying illegal refueling stations in accordance with an exemplary embodiment;
FIG. 5 is a schematic diagram illustrating an apparatus for identifying illegal refueling stations in accordance with an exemplary embodiment;
FIG. 6 is a schematic diagram illustrating a computer storage medium in accordance with an exemplary embodiment.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of systems and methods consistent with certain aspects of the invention, as detailed in the appended claims.
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
Fig. 1 is a flow chart illustrating a method of identifying an illegal fueling station, according to an exemplary embodiment, and with reference to fig. 1, the method specifically includes the following steps.
S101, the stop data of the vehicle is matched with the interest point data to obtain a stop data set of the gas station.
In one possible implementation, before performing step S101, the method further includes acquiring trajectory data and national point of interest data of the vehicle.
For example, GPS track data of a plurality of vehicles may be acquired, where a GPS track point is vehicle position data reported in real time by a GPS (global positioning System) device deployed on a vehicle. Generally, when the GPS device reports in real time, the reporting time interval can be set according to the actual situation, and the time interval is preferably 10S in the present application. It should be noted that, in the application, besides the vehicle is provided with the GPS device to report the trajectory data of the vehicle in real time, the Beidou device can also be used to position and report the trajectory of the vehicle.
And then national point of interest data is obtained according to a national POI information database in the network, for example, the national point of interest data is obtained through a Baidu POI database, and the national point of interest data is obtained through a Goods POI database.
And further, judging whether the vehicle stops according to the time information and the speed information in the track data to obtain stop data of the vehicle.
Specifically, a stop point is calculated according to a track time axis, for example, when the speed is less than 5 km/h, the stop point is used as a stop base point, the distance between each subsequent point and the base point is calculated, if the continuous time is less than or equal to 200 m and the duration is greater than 2 minutes, the base point is marked as a stop starting point, the stop starting time of the base point is used as the stop starting time of the current stop, the stop longitude and the stop longitude of the base point are used as the stop point longitude and the stop longitude of the current stop, all subsequent travel track points are continuously judged, one point is found, the distance between the point and the base point is greater than 200 m, the duration exceeds 2 minutes, the stop of the current stop is marked, and the time difference between the end point and the base point is used as the total stop time of the current stop. And obtaining the stop data of the vehicle.
Further, the step of matching the stop data of the vehicle with the point of interest data to obtain a stop data set of the gas station comprises the following steps: calculating the distance between the target stop point and the gas station interest point contained in the area where the target stop point is located; and when the distance is smaller than the preset distance threshold value and the stop time length is within the first preset stop time length interval, the target stop point stops for the gas station, and the target stop point is added into the stop data set of the gas station.
In a possible implementation manner, the target stop point is a stop point to be calculated, the distance between the target stop point and a service station interest point in an area where the target stop point is located is calculated, when the distance is smaller than a preset distance threshold value and the stop duration is within a first preset stop duration interval, the target stop point stops for the service station, and the target stop point is added into a service station stop data set. The distance threshold and the first preset stop duration interval can be set by a person skilled in the art according to actual conditions. The gas station parking data set comprises license plate numbers, license plate colors, parking starting time, parking ending time, parking duration, POI _ ID, POI names, parking distances, parking longitudes and parking latitudes of vehicles parked in the gas station.
In a possible implementation manner, the method further comprises the step of determining whether the target stop point is a stop of a gas station according to the road network data. For each target stop point to be calculated, if the distance between the target stop point to be calculated and a gas station POI point in the area where the target stop point is located is smaller than a first distance threshold value, determining whether the distance between the gas station POI point and a corresponding gas station road is smaller than a second distance threshold value; and if the distance is smaller than the second distance threshold, determining that the target stop point is a stop of the gas station. And if the distance between the target stop point and the corresponding gas station road is not less than the second distance threshold value, the target stop point and the gas station POI point are positioned on the same side of the corresponding gas station road, and the distance between the target stop point and the corresponding gas station road is greater than a third distance threshold value, determining that the target stop point stops for the gas station. Wherein the first distance threshold is greater than the second distance threshold, which is greater than the third distance threshold.
By analyzing historical track data of a large number of vehicles, a gas station stop data set of the vehicles can be obtained.
S102, screening abnormal refueling vehicles which are not in the gas station stop data set according to the track data in the preset time period of the vehicles.
Through the above steps, the refuelling situation of all vehicles nationwide has been calculated, and if the vehicle is normally operated but is not refueled, that is, the stop points of the vehicle are not all in the gas station stop data set, the vehicle may be suspected to be refueled at other illegal gas stations.
In one embodiment, abnormally refueled vehicles that are not in the gas station stop data set are filtered out based on trajectory data for a preset period of time for the vehicle. Specifically, track data of a plurality of vehicles in a recent period of time is acquired, the operating mileage of the vehicles is calculated according to the track data in a preset period of time of the vehicles, for example, the latest report of the vehicles is 10 days, and when the operating mileage of a certain day is greater than the preset operating mileage, it is determined that the vehicles are normally operated on the certain day.
And calculating the stopping point according to the track data of the normally operated vehicle, and when the stopping point of the normally operated vehicle is contained in the gas station stopping data set, indicating that the vehicle is a normally refueled vehicle. When all the stop points of the normally operating vehicle are not located in the gas station stop data set, the operating vehicle is an abnormally-fueled vehicle.
S103, clustering the stop points of the vehicles refueling abnormally, and taking the clustering area not containing the preset interest points as the abnormal area.
Further, the stop points of the abnormal refueling vehicles are clustered through a k-means clustering algorithm to obtain a plurality of clustering areas. In one possible implementation, the k-means clustering algorithm includes the following steps:
1. randomly selecting k points as a clustering center;
2. calculating the distance from each point to k clustering centers respectively, and then dividing the point to the nearest clustering center, thus forming k clusters;
3. recalculating the centroid of each cluster;
4. and repeating the steps 2-4 until the position of the mass center is not changed or the set iteration number is reached.
In another possible implementation manner, other clustering algorithms such as a DBSCAN clustering algorithm may also be used, which is not specifically limited in this embodiment.
And searching POI points in a preset range of each clustering area, further classifying the types of the POI points, and if the preset range of the clustering area does not contain the POI points or POI points which are strongly associated with freight transportation, such as ports, docks, railway stations, airport freight transportation, logistics parks, industrial parks, outdoor parking lots, farmer markets, furniture and building material markets, gas stations, service areas and the like, the clustering area is an abnormal area.
According to the step, by clustering the stop points of the vehicles which are abnormally refueled and combining POI data, the abnormal area where the vehicles always stop abnormally is obtained through analysis.
S104, judging whether the vehicles in the abnormal area meet the preset refueling condition or not, and if so, determining that the abnormal area is an illegal refueling station.
Further, the parking behavior of the vehicle in the abnormal area is analyzed to determine whether the abnormal area is an illegal fueling station.
In an optional embodiment, the parking duration and the parking times of the vehicle in the abnormal area are firstly calculated, and when the parking duration of the vehicle is in the second preset parking duration interval and the parking times are in the preset parking times interval, the vehicle is a suspected illegally-refueled vehicle. Further, when the number of suspected illegal refueling vehicles in the abnormal area is within the preset number interval, the abnormal area is an illegal refueling station. For example, within a week, the number of vehicles in the area with abnormal stops is between [20-100] vehicles, and the area may be an illegal refueling station.
Fig. 3 is a diagram illustrating the identification of an illegal fueling station according to an exemplary embodiment, where the illegal fueling station may be located in a certain hidden small area on a map as shown in fig. 3, and the identified illegal fueling station is marked and displayed. In one exemplary scenario, after identifying the illegal fueling station, the method further comprises: the method comprises the steps of obtaining geographic position information of the illegal refueling station, for example, obtaining longitude and latitude information of the illegal refueling station, wherein the longitude and latitude is (longitude: 112.75, latitude: 37.68), converting the obtained longitude and latitude information into a 'Shanxi Shanzhong City elm Source vortex-village east outer ring crossroad' through geographic information service, and sending the converted geographic position information to a user terminal for displaying. The user terminal comprises a display screen, a personal computer, a tablet computer and other equipment.
To facilitate understanding of the method for identifying an illegal fueling station provided by the embodiments of the present application, reference is made to fig. 2. As shown in fig. 2, the method includes:
firstly, acquiring GPS track data reported on N days of a vehicle history and POI data of a gas station, obtaining stop data of the vehicle according to the track data of the vehicle, and matching the stop data of the vehicle with the POI data of the gas station to obtain a gas station stop data set s 0.
Furthermore, the stop data of the vehicle is obtained according to the trajectory data of the vehicle in the latest period of time, then classification judgment is carried out, and it is identified that the stop points of the vehicle do not have the vehicles in the gas station stop data set s0, and the vehicles do not stop at the gas station and may have abnormal refueling behavior.
Clustering the screened stop points of the stop vehicles without the gas stations to generate a plurality of clustering areas, screening by combining POI data, searching POI points in a preset range of each clustering area, and filtering the clustering areas containing the POI points strongly associated with freight transportation to obtain abnormal clustering areas which do not contain the POI points or the POI points strongly associated with freight transportation, such as ports and docks, railway stations, airport freight transportation, logistics parks, industrial parks, gas stations, service areas and the like.
The parking behavior of the vehicles in the abnormal clustering area is analyzed to determine whether the abnormal area is an illegal refueling station.
According to the illegal refueling station identification method provided by the embodiment of the disclosure, data analysis is performed through recent travel track data of a truck and POI data of national gas stations, and the illegal refueling station is automatically identified through technical means such as stop point clustering and elimination, so that a powerful basis is provided for hitting the illegal refueling station, and a technical means is provided for centralized improvement and treatment of a finished oil market.
The disclosed embodiment also provides an apparatus for identifying an illegal refueling station, which is used for executing the method for identifying an illegal refueling station of the above embodiment, and as shown in fig. 4, the apparatus includes:
the matching module 401 is configured to match the stop data of the vehicle with the point of interest data to obtain a stop data set of the gas station;
a screening module 402, configured to screen an abnormal refueling vehicle that is not in the gas station stop data set according to trajectory data within a preset time period of the vehicle;
the clustering module 403 is configured to cluster stop points of the abnormal refueling vehicle, and use a clustering region that does not include a preset interest point as an abnormal region;
the identification module 404 is configured to determine whether a vehicle in the abnormal area meets a preset refueling condition, and if the vehicle meets the preset refueling condition, the abnormal area is an illegal refueling station.
It should be noted that, when the apparatus for identifying an illegal fueling station provided in the above embodiment executes the method for identifying an illegal fueling station, only the division of the above functional modules is taken as an example, in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules, so as to complete all or part of the above described functions. In addition, the device for identifying the illegal refueling station and the method for identifying the illegal refueling station provided by the embodiment belong to the same concept, and the embodiment of the method embodies the implementation process which is detailed in the method embodiment and is not repeated herein.
The embodiment of the present disclosure further provides an electronic device corresponding to the method for identifying an illegal refueling station provided by the foregoing embodiment, so as to execute the method for identifying an illegal refueling station.
Please refer to fig. 5, which illustrates a schematic diagram of an electronic device according to some embodiments of the present application. As shown in fig. 5, the electronic apparatus includes: the processor 500, the memory 501, the bus 502 and the communication interface 503, wherein the processor 500, the communication interface 503 and the memory 501 are connected through the bus 502; the memory 501 stores a computer program that can be executed on the processor 500, and the processor 500 executes the computer program to execute the method for identifying an illegal fueling station provided by any of the foregoing embodiments of the present application.
The Memory 501 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 503 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The processor 500 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 500. The Processor 500 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 501, and the processor 500 reads the information in the memory 501, and completes the steps of the method in combination with the hardware thereof.
The electronic equipment provided by the embodiment of the application and the method for identifying the illegal refueling station provided by the embodiment of the application have the same inventive concept and have the same beneficial effects as the method adopted, operated or realized by the electronic equipment.
Referring to fig. 6, the computer readable storage medium is an optical disc 600, on which a computer program (i.e., a program product) is stored, and when the computer program is executed by a processor, the computer program performs the method for identifying an illegal fueling station according to any of the embodiments.
It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory, or other optical and magnetic storage media, which are not described in detail herein.
The computer-readable storage medium provided by the above-mentioned embodiment of the present application and the method for identifying an illegal fueling station provided by the embodiment of the present application have the same beneficial effects as the method adopted, operated or implemented by the application program stored in the computer-readable storage medium.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of identifying an illegal fueling station comprising:
matching the stop data of the vehicle with the interest point data to obtain a stop data set of a gas station;
screening abnormal refueling vehicles which are not in the gas station stop data set according to the track data in a preset time period of the vehicles;
clustering the stop points of the abnormal refueling vehicles, and taking a clustering area which does not contain a preset interest point as an abnormal area;
and judging whether the vehicles in the abnormal area meet a preset refueling condition or not, and if so, determining that the abnormal area is an illegal refueling station.
2. The method of claim 1, wherein before matching the vehicle stop data with the point of interest data to obtain the gas station stop data set, further comprising:
acquiring track data and national interest point data of vehicles;
and judging whether the vehicle stops according to the time information and the speed information in the track data to obtain stop data of the vehicle.
3. The method of claim 1, wherein matching the vehicle stop data with the point of interest data to obtain a gas station stop data set comprises:
calculating the distance between a target stop point and a gas station interest point contained in the area where the target stop point is located;
and when the distance is smaller than a preset distance threshold value and the stop time is within a first preset stop time interval, the target stop point stops for the gas station, and the target stop point is added into the stop data set of the gas station.
4. The method of claim 1, wherein screening abnormal refueling vehicles that are not in the gas station stop data set according to trajectory data within a preset time period of the vehicle comprises:
calculating the operation mileage of the vehicle and the stop point of the vehicle according to the track data in the preset time period of the vehicle;
when the operating mileage is more than or equal to a preset operating mileage, the vehicle is an operating vehicle;
when none of the operating vehicle stop points are located in the gas station stop data set, the operating vehicle is an abnormal refueling vehicle.
5. The method according to claim 1, wherein clustering the stop points of the abnormally-fueled vehicle, and regarding a clustering region not including a preset point of interest as an abnormal region, comprises:
clustering the stop points of the abnormal refueling vehicles by a k-means clustering algorithm to obtain a plurality of clustering areas;
and acquiring the interest point type in each clustering area, and taking the clustering area not containing the preset interest point as an abnormal area.
6. The method as claimed in claim 1, wherein determining whether the vehicle in the abnormal region meets a preset refueling condition, and if the preset refueling condition is met, the abnormal region is an illegal refueling station, comprising:
calculating the parking time and the parking times of the vehicles in the abnormal area;
when the parking time of the vehicle is in a second preset parking time interval and the parking times are in a preset parking time interval, the vehicle is a suspected illegal refueling vehicle;
and when the number of suspected illegal refueling vehicles in the abnormal area is within a preset number interval, the abnormal area is an illegal refueling station.
7. The method of claim 1, wherein upon identifying the illegitimate fueling station, further comprising:
acquiring the geographical position information of the illegal refueling station;
and sending the geographical position information to a user terminal for displaying.
8. An apparatus for identifying an illegal refueling station, comprising:
the matching module is used for matching the stop data of the vehicle with the interest point data to obtain a stop data set of the gas station;
the screening module is used for screening abnormal refueling vehicles which are not in the gas station stop data set according to the track data in a preset time period of the vehicles;
the clustering module is used for clustering the stop points of the abnormal refueling vehicles and taking a clustering area which does not contain a preset interest point as an abnormal area;
and the identification module is used for judging whether the vehicles in the abnormal area meet the preset refueling condition or not, and if the vehicles meet the preset refueling condition, the abnormal area is an illegal refueling station.
9. An apparatus for identifying an illegal refueling station comprising a processor and a memory storing program instructions, the processor being configured to execute the method of identifying an illegal refueling station according to any of claims 1 to 7 when executing the program instructions.
10. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement a method of identifying an unlawful refueling station as claimed in any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110951374.1A CN113821735B (en) | 2021-08-18 | 2021-08-18 | Method, device, equipment and storage medium for identifying illegal fueling station |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110951374.1A CN113821735B (en) | 2021-08-18 | 2021-08-18 | Method, device, equipment and storage medium for identifying illegal fueling station |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113821735A true CN113821735A (en) | 2021-12-21 |
| CN113821735B CN113821735B (en) | 2024-02-02 |
Family
ID=78913226
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110951374.1A Active CN113821735B (en) | 2021-08-18 | 2021-08-18 | Method, device, equipment and storage medium for identifying illegal fueling station |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113821735B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117893794A (en) * | 2023-12-21 | 2024-04-16 | 北京英视睿达科技股份有限公司 | Method, device, equipment and medium for identifying non-regular gas station |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140379523A1 (en) * | 2013-06-24 | 2014-12-25 | Hyundai Motor Company | System and method for monitoring gas station |
| CN106595685A (en) * | 2016-12-06 | 2017-04-26 | 北京中交兴路信息科技有限公司 | Gas station stop points identification method and device thereof |
| CN108021625A (en) * | 2017-11-21 | 2018-05-11 | 深圳广联赛讯有限公司 | Vehicle abnormality aggregation ground monitoring method and system, computer-readable recording medium |
| CN108170793A (en) * | 2017-12-27 | 2018-06-15 | 厦门市美亚柏科信息股份有限公司 | Dwell point analysis method and its system based on vehicle semanteme track data |
| US20180285371A1 (en) * | 2015-09-30 | 2018-10-04 | Baidu Online Network Technology (Beijibg) Co., Ltd | Method and apparatus for automatically discovering gas station poi, storage medium and device |
| CN111241120A (en) * | 2020-03-13 | 2020-06-05 | 中汽研(天津)汽车信息咨询有限公司 | Vehicle energy filling point analysis method and device, vehicle-mounted equipment and storage medium |
| CN111380541A (en) * | 2018-12-29 | 2020-07-07 | 沈阳美行科技有限公司 | Interest point determination method and device, computer equipment and storage medium |
| CN112348091A (en) * | 2020-11-10 | 2021-02-09 | 成都福立盟环保大数据有限公司 | Dual-clustering blackwork site identification algorithm based on GPS (global positioning system) of muck truck |
-
2021
- 2021-08-18 CN CN202110951374.1A patent/CN113821735B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140379523A1 (en) * | 2013-06-24 | 2014-12-25 | Hyundai Motor Company | System and method for monitoring gas station |
| US20180285371A1 (en) * | 2015-09-30 | 2018-10-04 | Baidu Online Network Technology (Beijibg) Co., Ltd | Method and apparatus for automatically discovering gas station poi, storage medium and device |
| CN106595685A (en) * | 2016-12-06 | 2017-04-26 | 北京中交兴路信息科技有限公司 | Gas station stop points identification method and device thereof |
| CN108021625A (en) * | 2017-11-21 | 2018-05-11 | 深圳广联赛讯有限公司 | Vehicle abnormality aggregation ground monitoring method and system, computer-readable recording medium |
| CN108170793A (en) * | 2017-12-27 | 2018-06-15 | 厦门市美亚柏科信息股份有限公司 | Dwell point analysis method and its system based on vehicle semanteme track data |
| CN111380541A (en) * | 2018-12-29 | 2020-07-07 | 沈阳美行科技有限公司 | Interest point determination method and device, computer equipment and storage medium |
| CN111241120A (en) * | 2020-03-13 | 2020-06-05 | 中汽研(天津)汽车信息咨询有限公司 | Vehicle energy filling point analysis method and device, vehicle-mounted equipment and storage medium |
| CN112348091A (en) * | 2020-11-10 | 2021-02-09 | 成都福立盟环保大数据有限公司 | Dual-clustering blackwork site identification algorithm based on GPS (global positioning system) of muck truck |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117893794A (en) * | 2023-12-21 | 2024-04-16 | 北京英视睿达科技股份有限公司 | Method, device, equipment and medium for identifying non-regular gas station |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113821735B (en) | 2024-02-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ahmed et al. | Errors in accident data, its types, causes and methods of rectification-analysis of the literature | |
| US20210375128A1 (en) | System and method for detection and quantification of irregular traffic congestion | |
| EP1627370B1 (en) | System and method for evaluating vehicle and operator performance | |
| CN112447041B (en) | Method and device for identifying operation behavior of vehicle and computing equipment | |
| CN113847925A (en) | Method, device, equipment and medium for detecting vehicle yaw based on track data | |
| US10489431B2 (en) | Digital location-based data methods and product | |
| CN113222331B (en) | Method, device, equipment and storage medium for identifying authenticity of vehicle accident | |
| CN115935056A (en) | Method, device and equipment for identifying false track of vehicle and storage medium | |
| CN113821735B (en) | Method, device, equipment and storage medium for identifying illegal fueling station | |
| US10163339B2 (en) | Monitoring traffic congestion | |
| CN113626656B (en) | Method, device, equipment and storage medium for identifying relationship type between enterprise and vehicle | |
| CN114202903A (en) | DEM data-based vehicle early warning method, device, equipment and storage medium | |
| CN114169588A (en) | Traffic capacity prediction method, device, equipment and storage medium | |
| US11506525B2 (en) | Method for verifying sensors in a sensor network, and sensor network | |
| CN115995151B (en) | Network vehicle-closing abnormal behavior detection method applied to city management | |
| CN113194408B (en) | Method, device and equipment for detecting Beidou signal coverage blind area and storage medium | |
| CN113611130B (en) | Method, system and storage medium for acquiring traffic flow of local and transit trucks | |
| CN114090709A (en) | Method for accurately and efficiently analyzing rental vehicle entering and exiting administrative region | |
| CN112991804B (en) | Stay area determination method and related device | |
| CN114664060A (en) | Traffic incident early warning method, device, equipment and storage medium | |
| CN114677231A (en) | Anti-fraud identification method and device for freight risk order, storage medium and terminal | |
| CN114140270A (en) | Method, system and storage medium for judging vehicle rescue based on vehicle driving data | |
| Buroni et al. | Cluster Analysis of On-Board-Unit Truck Big Data from the Brussels Capital Region | |
| CN114461933B (en) | Vehicle recommendation method, device and equipment based on periphery search and storage medium | |
| CN114140985B (en) | Vehicle fatigue early warning method, device, equipment and medium based on knowledge graph |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |