IoT-based Security Supervision System and Method for Regional Vehicle Information Platform

Abstract

The present invention discloses a security supervision system and method for a regional vehicle information platform based on the Internet of Things, which relates to the technical field of vehicle supervision. The supervision method includes the following steps: performing a risk assessment on the driving status of each authorized vehicle based on driving data to obtain the risk value of each driving record; obtaining the driving route in each driving record to obtain the driving area range; judging whether to track the subsequent driving route of the authorized vehicle based on the risk assessment situation; when tracking a certain authorized vehicle, analyzing the vehicle demand situation in the driving area range; judging whether to issue a vehicle dispatching warning for the driving area range based on the vehicle dispatching situation in the driving area range; when there is a vehicle dispatching warning in a certain driving area range, analyzing the vehicle dispatching situation in the adjacent area range and screening out the target vehicle for vehicle dispatching to the certain driving area range.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle supervision, and specifically to a security supervision system and method for a regional vehicle information platform based on the Internet of Things. Background Art

[0002] A regional vehicle information platform is an information system integrating functions such as vehicle management, dispatching, monitoring, and data analysis, aiming to improve the efficiency and safety of vehicle operations within a region; help collect and analyze vehicle operation data, identify potential safety hazards and operation bottlenecks, and support decision-making;

[0003] The regional vehicle information platform usually arranges vehicles within a fixed regional scope according to actual needs and operation strategies. The platform can identify high-demand areas based on historical data for vehicle dispatching, but it cannot cope with the occurrence of various emergencies. For example, during peak hours or when emergencies occur, there may be a lack of sufficient vehicles and drivers for dispatching within the region, seriously affecting the vehicle response efficiency and the riding experience of passengers. Summary of the Invention

[0004] The purpose of the present invention is to provide a security supervision system and method for a regional vehicle information platform based on the Internet of Things to solve the problems raised in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A security supervision method for a regional vehicle information platform based on the Internet of Things, the supervision method includes the following steps:

[0006] Step S100: Establish a vehicle data supervision platform to record the driving data of authorized vehicles, and generate corresponding driving records for each driving process of each authorized vehicle; perform a risk assessment on the driving status of each authorized vehicle based on the driving data of each authorized vehicle to obtain the risk values presented by each driving record;

[0007] Step S200: Obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving area range of the authorized vehicle; based on the risk assessment situation of the authorized vehicle, determine whether to track the subsequent driving routes of the authorized vehicle;

[0008] Step S300: When tracking a certain authorized vehicle, analyze the vehicle demand situation in the driving area range where the certain authorized vehicle is located; based on the vehicle dispatching situation in the driving area range, determine whether to issue a vehicle dispatching warning for the driving area range;

[0009] Step S400: When a vehicle scheduling warning occurs in a certain driving area range, analyze the vehicle scheduling situation in the adjacent area range; extract the driving routes of each authorized vehicle in the adjacent area range, and screen out the target vehicle for vehicle scheduling to the certain driving area range.

[0010] Further, step S100 includes the following steps:

[0011] Step S101: Conduct information authorization for all vehicles used for scheduling on the vehicle data supervision platform. When any authorized vehicle receives a scheduling reminder, start recording the driving data and driving route of the authorized vehicle until the vehicle completes the scheduling, and generate a driving record of the authorized vehicle.

[0012] Step S102: Arbitrarily obtain a driving record of a certain authorized vehicle, set risk assessment rules for the driving record in different dimensions, and respectively obtain the risk values of the driving record in different dimensions; accumulate the risk values in different dimensions to obtain the risk value presented by the certain authorized vehicle in the driving record; Conducting risk assessment on vehicles can help staff discover potential abnormal situations of vehicles in advance, and subsequent tracking can help staff conduct timely vehicle scheduling to avoid insufficient vehicle scheduling in the area.

[0013] Further, step S200 includes the following steps:

[0014] Step S201: Arbitrarily select a certain authorized vehicle, obtain the driving route in any driving record of the certain authorized vehicle, and respectively set the positions where the certain authorized vehicle is located when receiving the scheduling reminder and completing the scheduling as two feature points of the corresponding driving route.

[0015] Step S202: Extract the two feature points set in each driving record of the certain authorized vehicle, obtain the coordinate positions of each feature point and present them on the map, and connect any two feature points on the map to obtain a graph; The polygon formed by connecting several feature points on the graph boundary is used as the driving area range of the certain authorized vehicle; The point when receiving the scheduling reminder is the boarding point of the authorized vehicle, and the point when completing the scheduling is the alighting point of the authorized vehicle. By capturing these two feature points, a more accurate driving range can be obtained because the driving range will not deviate significantly from the boarding point and the alighting point. As long as there are enough feature points, most of the driving routes can be included.

[0016] Step S203: Sort each driving record of the authorized vehicle according to the record generation time, obtain the risk difference between any two adjacent driving records based on the risk values presented by any two adjacent driving records, and obtain a risk difference set; determine the positive and negative situations of each risk difference in the risk difference set; According to the formula:

[0017] ;

[0018] where i is a positive integer and i ∈ (1, a), a is the total number of risk differences in the risk difference set, ΔF i is the i-th risk difference in the risk difference set, and calculate the characteristic risk difference TF of the risk difference set; if there exists a risk difference ΔF that satisfies ΔF < TF and |ΔF| > TF, then set the previous driving record of the two driving records corresponding to the risk difference ΔF as the characteristic driving record; the risk value of the authorized vehicle normally increases slowly. If there is a decrease in the risk value, it means that the authorized vehicle has been repaired to restore its normal state. Therefore, the risk value presented by the driving record with a decreased risk value can accurately judge the standard for the vehicle to have an abnormality; and during the risk assessment process, there may be an error in the decrease of the risk value, but this error is within a small range and is quite different from the risk value change caused by maintenance. Therefore, the above formula can exclude the occurrence of errors;

[0019] Step S204: Extract the characteristic driving records of all authorized vehicles, obtain the risk value of each characteristic driving record, and select the smallest risk value as the vehicle risk threshold F max ; Select the largest risk difference ΔF max from the risk difference set, and obtain the characteristic coefficient β = TF / ΔF max , According to the formula:

[0020] ;

[0021] Calculate the target risk value F for tracking the authorized vehicle

[0022] yc

[0023] ; When the risk value presented by a driving record of an authorized vehicle exceeds the target risk value, track the authorized vehicle; if it is necessary to track the authorized vehicle, it means that the vehicle has a certain risk but does not affect normal driving at present. Therefore, through the above judgment of risk differences, only the risk threshold for the vehicle to have an abnormality can be obtained, and for the risk value that needs to be tracked, the characteristic coefficient needs to be calculated through the change degree of the risk difference in order to further obtain the target risk value.

[0024] Further, step S300 includes the following steps:

[0025] Step S301: Set the risk value presented by the latest generated driving record of a certain authorized vehicle as F ’ , if F ’ > F yc , then obtain the driving area range of the certain authorized vehicle; extract each feature point in the driving area range, randomly select a feature point, and obtain the number of records where the feature point is also a feature point in all other driving records as M, and obtain the scheduling frequency D of the feature point = M / M total , where M total is the total number of driving records recorded on the vehicle data supervision platform; the frequency of a feature point appearing in a driving record can directly reflect the scheduling frequency of the feature point;

[0026] Step S302: Locate the current positions of each authorized vehicle, count the number of vehicles in the driving area range as N, obtain the driving routes of each authorized vehicle in the driving area, where it is set that the number of routes of the j-th authorized vehicle that contain the feature point is R j , and the number of driving routes of the j-th authorized vehicle is S j , and obtain the route proportion η j = R j / S j ; if η j > D, then the j-th authorized vehicle is a schedulable vehicle; count the number of schedulable vehicles in the driving area range as X, if X / N < D, then issue a vehicle scheduling warning for the driving area range; based on the number of times an authorized vehicle passes through a feature point among the above feature points, which can reflect the influence of the authorized vehicle's abnormality on the scheduling frequency of the feature point, and then by analyzing the scheduling frequencies of the other vehicles in the same area to the feature point, it is possible to obtain whether the scheduling frequency of the feature point can be compensated by the other vehicles in the same area. If not, it means that other vehicles are needed for supplementary scheduling.

[0027] Further, step S400 includes the following steps:

[0028] Step S401: Set that there is a vehicle scheduling warning in a driving area range, obtain each driving area range that has the same driving area range as the driving area range, and set them as several scheduling areas;

[0029] Step S402: Arbitrarily select a scheduling area to obtain the authorized vehicles corresponding to the scheduling area; obtain the same area between the scheduling area and the driving area range where vehicle scheduling warning occurs, and obtain the number of feature points Z existing for the authorized vehicles in the same area; count the number of records containing a number of feature points in the same area in each driving record of the authorized vehicles, and obtain the scheduling frequency f of the authorized vehicles in the same area sim ;

[0030] Step S403: Respectively obtain the scheduling frequencies of each feature point of the authorized vehicles in the scheduling area, and calculate the average scheduling frequency f of the authorized vehicles ave , if f sim < f ave , then set the authorized vehicle as a schedulable vehicle, and perform vehicle scheduling for the authorized vehicle towards the driving area range

[0031] To better implement the above method, a regional vehicle information platform security supervision system is also proposed. The supervision system includes a vehicle status analysis module, a vehicle route analysis module, a vehicle scheduling warning module, and a real-time vehicle scheduling module;

[0032] The vehicle status analysis module is used to establish a vehicle data supervision platform to record the driving data of authorized vehicles, and generate corresponding driving records for each driving process of each authorized vehicle; based on the driving data of each authorized vehicle, perform a risk assessment on the driving status of each authorized vehicle to obtain the risk values presented by each driving record;

[0033] The vehicle route analysis module is used to obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving area range of the authorized vehicle; based on the risk assessment situation of the authorized vehicle, determine whether to track the subsequent driving routes of the authorized vehicle;

[0034] The vehicle scheduling warning module is used to analyze the vehicle demand situation in the driving area range where a certain authorized vehicle is located when tracking a certain authorized vehicle; based on the vehicle scheduling situation in the driving area range, determine whether to issue a vehicle scheduling warning for the driving area range;

[0035] The real-time vehicle scheduling module is used to analyze the vehicle scheduling situation in the adjacent area range when there is a vehicle scheduling warning in a certain driving area range; extract the driving routes of each authorized vehicle in the adjacent area range, and screen out the target vehicles for vehicle scheduling towards the certain driving area range

[0036] Furthermore, the vehicle status analysis module includes a driving record generation unit and a vehicle risk assessment unit;

[0037] A driving record generation unit is used to establish a vehicle data supervision platform to record the driving data of authorized vehicles and generate corresponding driving records for each driving process of each authorized vehicle; a vehicle risk assessment unit is used to conduct a risk assessment on the driving status of each authorized vehicle based on the driving data of each authorized vehicle to obtain the risk values presented by each driving record.

[0038] Further, the vehicle route analysis module includes a regional scope division unit and a vehicle route tracking unit;

[0039] The regional scope division unit is used to obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving regional scope of the authorized vehicle; the vehicle route tracking unit is used to determine whether to track the subsequent driving route of the authorized vehicle based on the risk assessment of the authorized vehicle.

[0040] Further, the vehicle dispatching warning module includes a vehicle demand analysis unit and a dispatching warning judgment unit;

[0041] The vehicle demand analysis unit is used to analyze the vehicle demand situation in the driving regional scope of a certain authorized vehicle when tracking a certain authorized vehicle; the dispatching warning judgment unit is used to determine whether to issue a vehicle dispatching warning for the driving regional scope based on the vehicle dispatching situation in the driving regional scope.

[0042] Further, the real-time vehicle dispatching module includes a driving regional analysis unit and a vehicle dispatching implementation unit;

[0043] The driving regional analysis unit is used to analyze the vehicle dispatching situation in the adjacent regional scope when there is a vehicle dispatching warning in a certain driving regional scope; the vehicle dispatching implementation unit is used to extract the driving routes of each authorized vehicle in the adjacent regional scope and screen out the target vehicles for vehicle dispatching to the certain driving regional scope.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] 1. By analyzing the driving regions where authorized vehicles are usually located, the present invention obtains the vehicle dispatching situations in each region, which can help determine whether the vehicle dispatching in the current driving region is reasonable and avoid the occurrence of insufficient vehicle dispatching caused by emergencies.

[0046] 2. By tracking authorized vehicles with certain risk values and analyzing whether there will be a shortage of vehicles at each location due to the operation changes of the authorized vehicles according to the driving routes of the authorized vehicles, the safety of the authorized vehicles is also ensured; and vehicles are arranged in regions with less vehicle dispatching, improving the efficiency of vehicle dispatching and the riding experience of users.

[0047] 3. The present invention schedules the vehicles in adjacent areas, and reasonably schedules the areas with sufficient vehicle numbers without affecting the remaining areas, reducing resource consumption without affecting the overall vehicle scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the steps of the security supervision method for the regional vehicle information platform based on the Internet of Things;

[0049] Figure 2 It is a schematic diagram of the structure of the security supervision system for the regional vehicle information platform based on the Internet of Things. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] Embodiment: As Figures 1 to 2 shown, the present invention provides a security supervision method for a regional vehicle information platform based on the Internet of Things. The supervision method includes the following steps:

[0052] Step S100: Establish a vehicle data supervision platform to record the driving data of authorized vehicles, and generate corresponding driving records for each driving process of each authorized vehicle; based on the driving data of each authorized vehicle, conduct a risk assessment on the driving status of each authorized vehicle to obtain the risk values presented by each driving record;

[0053] Among them, step S100 includes the following steps:

[0054] Step S101: Authorize the information of all vehicles for scheduling on the vehicle data supervision platform. When any authorized vehicle receives a scheduling reminder, it starts to record the driving data and driving route of the authorized vehicle until the vehicle completes the scheduling, and generates a driving record of the authorized vehicle;

[0055] Step S102: Arbitrarily obtain a driving record of a certain authorized vehicle, set risk assessment rules for different dimensions of the driving record, and respectively obtain the risk values of the driving record in different dimensions; accumulate the risk values in different dimensions to obtain the risk value presented by the certain authorized vehicle in the driving record.

[0056] Step S200: Obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving area range of the authorized vehicle; based on the risk assessment of the authorized vehicle, determine whether to track the subsequent driving routes of the authorized vehicle;

[0057] Among them, step S200 includes the following steps:

[0058] Step S201: Arbitrarily select an authorized vehicle, obtain the driving route in any driving record of the authorized vehicle, and respectively set the positions where the authorized vehicle is located when receiving the dispatching reminder and completing the dispatching as two feature points of the corresponding driving route;

[0059] Step S202: Extract the two feature points set in each driving record of the authorized vehicle, obtain the coordinate positions of each feature point and present them on the map, and connect any two feature points on the map to obtain a graph; the polygon obtained by connecting several feature points on the graph boundary is used as the driving area range of the authorized vehicle;

[0060] Step S203: Sort the driving records of the authorized vehicle according to the record generation time, obtain the risk difference between any two adjacent driving records based on the risk values presented in any two adjacent driving records to obtain a risk difference set; determine the positive and negative situations of each risk difference in the risk difference set; according to the formula:

[0061] ;

[0062] Among them, i is a positive integer and i ∈ (1, a), a is the total number of risk differences in the risk difference set, ΔF i is the i-th risk difference in the risk difference set, calculate the characteristic risk difference TF of the risk difference set; if there exists a risk difference ΔF that satisfies ΔF < TF and |ΔF| > TF, then set the previous driving record of the two driving records corresponding to the risk difference ΔF as the characteristic driving record;

[0063] Example 1: Set the risk differences between the risk values presented in any two adjacent driving records of the authorized vehicle to be 1, 1, 2, -5, 1 respectively; obtain the characteristic risk difference as TF = (1 + 1 + 2 + 5 + 1) / 5 = 2. Since -5 < 2 and |-5| > 2, therefore, set the previous driving record of the two driving records related to the risk difference as the characteristic driving record, that is, the characteristic driving record is that the vehicle was repaired after this driving record, and the risk value presented by the characteristic driving record is relatively high;

[0064] Step S204: Extract the characteristic driving records of all authorized vehicles, obtain the risk value of each characteristic driving record, and select the smallest risk value as the vehicle risk threshold F max ; Select the largest risk difference ΔF from the set of risk differences max , and obtain the characteristic coefficient β = TF / ΔF max , according to the formula:

[0065] ;

[0066] Calculate the target risk value F for tracking the authorized vehicle yc ; When the risk value presented by a certain authorized vehicle in a driving record exceeds the target risk value, track the certain authorized vehicle.

[0067] Step S300: When tracking a certain authorized vehicle, analyze the vehicle demand situation in the driving area range where the certain authorized vehicle is located; based on the vehicle dispatching situation in the driving area range, determine whether to issue a vehicle dispatching warning for the driving area range;

[0068] Among them, step S300 includes the following steps:

[0069] Step S301: Set the risk value presented by a newly generated driving record of a certain authorized vehicle as F ’ , if F ’ > F yc , then obtain the driving area range of the certain authorized vehicle; extract each characteristic point in the driving area range, randomly select a characteristic point, and obtain the number of records where the characteristic point is also a characteristic point in all other driving records as M, and get the scheduling frequency D of the characteristic point = M / M total , where M total is the total number of driving records recorded on the vehicle data supervision platform;

[0070] Step S302: Locate the current positions of each authorized vehicle, count the number of vehicles in the driving area range as N, obtain the driving routes of each authorized vehicle in the driving area, where it is set that the number of routes of the jth authorized vehicle that contain the characteristic point is R j , and the number of driving routes of the jth authorized vehicle is S j , and get the route proportion η of the jth authorized vehicle j = R j / S j ; If η jIf it is greater than D, then the j-th authorized vehicle is a dispatchable vehicle; count the number of dispatchable vehicles in the driving area as X. If X / N < D, then issue a vehicle dispatch warning for the driving area.

[0071] Embodiment 2: If the dispatch frequency of a certain authorized vehicle at a feature point is 50%, then obtain that the number of the remaining authorized vehicles is 3. The numbers of the routes including the feature point are 10, 5, and 3 respectively, and the numbers of the driving routes are 30, 20, and 30 respectively. The route proportions are 33.3%, 25%, and 10% respectively, all of which are less than 50%. Therefore, it shows that the vehicle dispatch at the feature point is insufficient, and a vehicle dispatch warning needs to be issued for the area.

[0072] Step S400: When a vehicle dispatch warning occurs in a certain driving area, analyze the vehicle dispatch situation in the adjacent area; extract the driving routes of each authorized vehicle in the adjacent area, and screen out the target vehicles for vehicle dispatch to the certain driving area.

[0073] Among them, step S400 includes the following steps:

[0074] Step S401: Assume that a vehicle dispatch warning occurs in a driving area, obtain each driving area that has the same driving area as the driving area, and set them as several dispatch areas.

[0075] Step S402: Arbitrarily select a dispatch area to obtain the authorized vehicle corresponding to the dispatch area; obtain the same area between the dispatch area and the driving area where the vehicle dispatch warning occurs, and obtain that the number of feature points of the authorized vehicle in the same area is Z; count the number of records of several feature points including the same area in each driving record of the authorized vehicle, and obtain that the dispatch frequency of the authorized vehicle in the same area is f sim ;

[0076] Step S403: Respectively obtain the dispatch frequency of each feature point of the authorized vehicle in the dispatch area, and calculate the average dispatch frequency f of the authorized vehicle ave If f sim < f ave , then set the authorized vehicle as a dispatchable vehicle, and dispatch the authorized vehicle to the driving area.

[0077] Regional vehicle information platform security supervision system. The supervision system includes a vehicle status analysis module, a vehicle route analysis module, a vehicle dispatch warning module, and a real-time vehicle dispatch module.

[0078] The vehicle status analysis module is used to establish a vehicle data supervision platform to record the driving data of authorized vehicles, and generate corresponding driving records for each driving process of each authorized vehicle; based on the driving data of each authorized vehicle, conduct a risk assessment on the driving status of each authorized vehicle to obtain the risk values presented by each driving record.

[0079] The vehicle route analysis module is used to obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving area range of the authorized vehicle; based on the risk assessment of the authorized vehicle, determine whether to track the subsequent driving routes of the authorized vehicle.

[0080] The vehicle dispatching warning module is used to analyze the vehicle demand situation in the driving area range of a certain authorized vehicle when tracking a certain authorized vehicle; extract the target areas with abnormal vehicle dispatching in the driving area range, and based on the vehicle dispatching situation in the driving area range, determine whether to issue a vehicle dispatching warning for the driving area range.

[0081] The real-time vehicle dispatching module is used to analyze the vehicle dispatching situation in the adjacent area range when a vehicle dispatching warning occurs in a certain driving area range; extract the driving routes of each authorized vehicle in the adjacent area range, and based on the relevance between the driving route and the certain driving area range, screen out the target vehicles for vehicle dispatching to the certain driving area range.

[0082] Among them, the vehicle status analysis module includes a driving record generation unit and a vehicle risk assessment unit;

[0083] The driving record generation unit is used to establish a vehicle data supervision platform to record the driving data of authorized vehicles, and generate corresponding driving records for each driving process of each authorized vehicle; the vehicle risk assessment unit is used to conduct a risk assessment on the driving status of each authorized vehicle based on the driving data of each authorized vehicle to obtain the risk values presented by each driving record.

[0084] Among them, the vehicle route analysis module includes an area range division unit and a vehicle route tracking unit;

[0085] The area range division unit is used to obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving area range of the authorized vehicle; the vehicle route tracking unit is used to determine whether to track the subsequent driving routes of the authorized vehicle based on the risk assessment of the authorized vehicle.

[0086] Among them, the vehicle dispatching warning module includes a vehicle demand analysis unit and a dispatching warning judgment unit;

[0087] A vehicle demand analysis unit, which is used to analyze the vehicle demand situation in the driving area range of a certain authorized vehicle when tracking the certain authorized vehicle; A dispatching early warning judgment unit, which is used to judge whether to issue a vehicle dispatching early warning for the driving area range based on the vehicle dispatching situation in the driving area range.

[0088] Among them, the real-time vehicle dispatching module includes a driving area analysis unit and a vehicle dispatching implementation unit;

[0089] The driving area analysis unit is used to analyze the vehicle dispatching situation in the adjacent area range when a vehicle dispatching early warning occurs in a certain driving area range; The vehicle dispatching implementation unit is used to extract the driving routes of each authorized vehicle in the adjacent area range and screen out the target vehicles for vehicle dispatching to the certain driving area range.

[0090] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A regional vehicle information platform security supervision method based on the Internet of Things, characterized by: The supervision method comprises the following steps: Step S100: Establish a vehicle data supervision platform to record the driving data of authorized vehicles, and generate corresponding driving records for each driving process of each authorized vehicle; perform risk assessment on the driving status of each authorized vehicle based on the driving data of each authorized vehicle, and obtain the risk value presented by each driving record; Step S200: Obtain the driving routes presented in each driving record of any authorized vehicle to obtain the driving area of ​​the authorized vehicle; based on the risk assessment of the authorized vehicle, determine whether to track the subsequent driving route of the authorized vehicle; Step S300: when tracking an authorized vehicle, analyzing the vehicle demand situation in the driving area where the authorized vehicle is located; based on the vehicle dispatch situation in the driving area, determining whether to issue a vehicle dispatch warning for the driving area; Step S400: When a vehicle dispatch warning occurs in a certain driving area, the vehicle dispatch situation in the adjacent area is analyzed; the driving routes of each authorized vehicle in the adjacent area are extracted, and the target vehicle is selected for vehicle dispatch to the certain driving area; The step S200 includes the following steps: Step S201: randomly selecting an authorized vehicle, obtaining a driving route in any driving record of the authorized vehicle, and setting the location of the authorized vehicle when receiving a dispatch reminder and completing the dispatch as two feature points of the corresponding driving route; Step S202: extracting two feature points set in each driving record of the authorized vehicle, obtaining the coordinate position of each feature point and presenting them on a map, connecting any two feature points on the map to obtain a graph; connecting a plurality of feature points on the boundary of the graph to obtain a polygon as the driving area range of the authorized vehicle; Step S203: Sort the driving records of the authorized vehicle according to the time when the records were generated, obtain the risk difference between any two adjacent driving records based on the risk values ​​presented by any two adjacent driving records, and obtain a risk difference set; determine the positive or negative status of each risk difference in the risk difference set; according to the formula: ； Where i is a positive integer and i∈(1,a), a is the total number of risk differences in the risk difference set, ΔF i is the i-th risk difference in the risk difference set, and a characteristic risk difference TF of the risk difference set is calculated; if there is a risk difference ΔF satisfying ΔF<TF and |ΔF|>TF, the previous driving record of the two driving records corresponding to the risk difference ΔF is set as the characteristic driving record; Step S204: Extract the characteristic driving records of all authorized vehicles, obtain the risk value of each characteristic driving record, and select the risk value with the smallest value as the vehicle risk threshold F max ; Select the risk difference value ΔF with the largest value from the risk difference set max , we get the characteristic coefficient β=TF / ΔF max , according to the formula: ； Calculate the target risk value F for tracking the authorized vehicle yc When the risk value presented by a certain authorized vehicle in a driving record exceeds the target risk value, the authorized vehicle is tracked.

2. The method for security supervision of regional vehicle information platform based on Internet of Things according to claim 1 is characterized by: The step S100 includes the following steps: Step S101: Authorizing all vehicles used for dispatching on the vehicle data supervision platform. When any authorized vehicle receives a dispatch reminder, it starts recording the driving data and driving route of the authorized vehicle until the vehicle completes the dispatch, generating a driving record of the authorized vehicle. Step S102: arbitrarily obtain a driving record of an authorized vehicle, set risk assessment rules of different dimensions for the driving record, and obtain risk values ​​of the driving record in different dimensions respectively; accumulate the risk values ​​in different dimensions to obtain the risk value presented by the authorized vehicle in the driving record.

3. The method for security supervision of regional vehicle information platform based on Internet of Things according to claim 2 is characterized in that: The step S300 includes the following steps: Step S301: Set the risk value of a newly generated driving record of an authorized vehicle to F ’ , if F ’ >F yc , then obtain the driving area of ​​the authorized vehicle; extract each feature point in the driving area, arbitrarily select a feature point, obtain the number of records of the feature point in all other driving records that are also feature points, and obtain the dispatch frequency D=M / M of the feature point total , where M total The total number of driving records recorded on the vehicle data supervision platform; Step S302: Locate the current location of each authorized vehicle, count the number of vehicles in the driving area as N, obtain the driving routes of each authorized vehicle in the driving area, and set the number of routes containing the feature points in the driving route of the jth authorized vehicle as R. j , and the number of driving routes of the jth authorized vehicle is S j , the route proportion of the jth authorized vehicle is η j =R j / S j If η j >D, the jth authorized vehicle is a dispatchable vehicle; the number of dispatchable vehicles in the driving area is counted as X, and if X / N<D, a vehicle dispatch warning is issued for the driving area.

4. The method for security supervision of regional vehicle information platform based on Internet of Things according to claim 3 is characterized in that: The step S400 includes the following steps: Step S401: setting a driving area range where a vehicle dispatch warning occurs, obtaining each driving area range that has the same driving area range as the driving area range, and setting them as a plurality of dispatch areas; Step S402: arbitrarily select a dispatch area and obtain the authorized vehicle corresponding to the dispatch area; obtain the same area between the dispatch area and the driving area where the vehicle dispatch warning occurs, and obtain the number of feature points of the authorized vehicle in the same area as Z; count the number of records containing several feature points in the same area in each driving record of the authorized vehicle, and obtain the dispatch frequency of the authorized vehicle in the same area as f sim ; Step S403: Obtain the dispatch frequency of each feature point of the authorized vehicle in the dispatch area respectively, and calculate the average dispatch frequency f of the authorized vehicle ave , if f sim <f ave , the authorized vehicle is set as a dispatchable vehicle, and the authorized vehicle is dispatched to the driving area.

5. A regional vehicle information platform security supervision system, used to execute the regional vehicle information platform security supervision method based on the Internet of Things according to any one of claims 1 to 4, characterized in that: The supervision system includes a vehicle status analysis module, a vehicle route analysis module, a vehicle dispatch warning module and a real-time vehicle dispatch module; The vehicle status analysis module is used to establish a vehicle data supervision platform to record the driving data of authorized vehicles and generate corresponding driving records for each driving process of each authorized vehicle; based on the driving data of each authorized vehicle, the driving status of each authorized vehicle is risk assessed to obtain the risk value presented by each driving record; The vehicle route analysis module is used to obtain the driving route presented in each driving record of any authorized vehicle, and obtain the driving area of ​​the authorized vehicle; based on the risk assessment of the authorized vehicle, determine whether to track the subsequent driving route of the authorized vehicle; The vehicle dispatch warning module is used to analyze the vehicle demand situation in the driving area where the authorized vehicle is located when tracking the authorized vehicle; based on the vehicle dispatch situation in the driving area, determine whether to issue a vehicle dispatch warning for the driving area; The real-time vehicle dispatch module is used to analyze the vehicle dispatch situation in an adjacent area when a vehicle dispatch warning occurs in a certain driving area; extract the driving routes of each authorized vehicle in the adjacent area, and screen out the target vehicle for vehicle dispatch to the certain driving area.

6. The regional vehicle information platform safety supervision system according to claim 5 is characterized by: The vehicle status analysis module includes a driving record generation unit and a vehicle risk assessment unit; The driving record generation unit is used to establish a vehicle data supervision platform to record the driving data of authorized vehicles and generate a corresponding driving record for each driving process of each authorized vehicle; the vehicle risk assessment unit is used to perform a risk assessment on the driving status of each authorized vehicle based on the driving data of each authorized vehicle to obtain the risk value presented by each driving record.

7. The regional vehicle information platform safety supervision system according to claim 5 is characterized by: The vehicle route analysis module includes an area range division unit and a vehicle route tracking unit; The area range division unit is used to obtain the driving route presented in each driving record of any authorized vehicle to obtain the driving area range of the authorized vehicle; the vehicle route tracking unit is used to determine whether to track the subsequent driving route of the authorized vehicle based on the risk assessment of the authorized vehicle.

8. The regional vehicle information platform safety supervision system according to claim 5 is characterized by: The vehicle dispatch warning module includes a vehicle demand analysis unit and a dispatch warning judgment unit; The vehicle demand analysis unit is used to analyze the vehicle demand situation in the driving area where a certain authorized vehicle is located when tracking the authorized vehicle; the dispatch warning judgment unit is used to judge whether to issue a vehicle dispatch warning for the driving area based on the vehicle dispatch situation in the driving area.

9. The regional vehicle information platform safety supervision system according to claim 5 is characterized by: The real-time vehicle dispatch module includes a driving area analysis unit and a vehicle dispatch execution unit; The driving area analysis unit is used to analyze the vehicle dispatch situation in an adjacent area when a vehicle dispatch warning occurs in a certain driving area; the vehicle dispatch execution unit is used to extract the driving routes of each authorized vehicle in the adjacent area, and screen out the target vehicle for vehicle dispatch to the certain driving area.

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