An intelligent community ground vehicle management method and system based on artificial intelligence

Abstract

The application is suitable for the field of smart community, and provides a smart community ground vehicle management method and system based on artificial intelligence. The method comprises the following steps: binding and associating an outside visitor vehicle and a visited household in a bidirectional manner, so as to uniquely correspond the visitor vehicle information and the household account; managing the visitor vehicle entering process by adopting a reservation system, and performing compliance auditing on the reservation information; constructing a mechanism for identifying illegal parking behaviors and tracing responsibilities, and if the visitor vehicle violates the parking management rules, deducting the integral of the associated visited household account; establishing a ladder type management model of the integral of the visited household, and opening the management authority of the visitor vehicle according to the integral level and different welfare treatment; the method and system can clearly define the illegal responsibility subject through bidirectional binding and responsibility tracing, improve the passing efficiency through the reservation system and intelligent auditing, and stimulate the enthusiasm of the household in participating in the management through the integral ladder management. The parking order of the community is optimized, and the management cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of smart communities, and particularly relates to a smart community ground vehicle management method and system based on artificial intelligence. BACKGROUND

[0002] With the advancement of smart community construction, the intelligent demand for ground vehicle management is growing. Traditional communities manage external visitor vehicles mainly through temporary registration, manual review or simple license plate recognition technology, which has problems such as low management efficiency, unclear responsibility tracing, and insufficient participation of residents, etc. For example, the process of visitor vehicle entering is complicated, it is difficult to accurately locate the responsibility subject for illegal parking behavior, and there is a lack of differentiated incentive mechanism for the management authority of residents, resulting in high cost of community parking order maintenance and the experience of residents needs to be improved.

[0003] In the prior art, although some systems try to realize visitor reservation through informatization means, they generally lack deep binding of responsibility association between visitor vehicles and residents, and do not establish a ladder management system based on resident credit. How to realize fine management of visitor vehicles through technical means while ensuring community safety, and at the same time encourage residents to actively participate in community governance, has become a technical problem to be solved in the field of smart community ground vehicle management. SUMMARY

[0004] The purpose of the present application is to provide a smart community ground vehicle management method and system based on artificial intelligence, which aims to solve the problems raised in the background technology.

[0005] The present application is implemented in the following way. On the one hand, a smart community ground vehicle management method based on artificial intelligence, the method comprising:

[0006] The external visitor vehicle and the visited resident are associated in a bidirectional binding manner, and the visitor vehicle information is uniquely corresponding to the resident account;

[0007] The visitor vehicle entering process is managed by reservation system, and the reservation information is audited for compliance;

[0008] A mechanism for identifying illegal parking behavior and tracing responsibility is constructed, and if the visitor vehicle violates the parking management rules, the associated visited resident account is deducted points;

[0009] A ladder management model of visited points is established, and different welfare treatment of visitor vehicle management authority is opened according to the point level.

[0010] As a further scheme of the present application, the bidirectional binding association of the external visitor vehicle and the visited resident, and the unique correspondence of the visitor vehicle information to the resident account specifically comprises:

[0011] Collecting license plate information, reservation time, and access object data of the visitor vehicle;

[0012] The visitor vehicle and the household account are bound in a two-way binding relationship through blockchain technology or a unique index of a database.

[0013] The uniqueness of the binding relationship is verified by a hash function.

[0014] ;

[0015] In the formula, is a visitor vehicle identification code, is a reservation timestamp, is a visited household name, is a pre-stored binding hash value.

[0016] As a further scheme of the present application, the visitor vehicle entry process managed by reservation and the compliance audit of the reservation information specifically includes:

[0017] The visited household initiates visitor vehicle reservation through a mobile terminal application.

[0018] Visitor vehicle reservation information is collected and verified, and the vehicle reservation information includes visitor identity, vehicle information, and access period.

[0019] The audit is performed based on community parking capacity and period limit rules, and a dynamic access credential is calculated and generated.

[0020] The calculation process of the dynamic access credential is as follows:

[0021] ;

[0022] In the formula, the is a peak period weight, is a reservation duration factor, is a period conflict coefficient, is a household point level correction, is a corresponding weight coefficient.

[0023] When the community parking capacity is saturated, a reservation failure credential is generated.

[0024] When the community parking capacity is not saturated, and , a reservation pass credential is generated.

[0025] When the community parking capacity is not saturated, and , a system review notice is generated.

[0026] When the community parking capacity is not saturated, and , a reservation failure and alternative period pass is generated.

[0027] As a further scheme of the present application, the construction of the illegal parking behavior identification and responsibility tracing mechanism, if the visitor vehicle violates the parking management rules, the associated visitor household account is implemented with point deduction, specifically includes:

[0028] The associated visitor household account is located through a bidirectional binding relationship;

[0029] Intelligent cameras, ground coils or sensor networks are deployed at targeted positions in the community to collect vehicle parking data in real time;

[0030] The AI vision algorithm is used to identify illegal behaviors and deduct points;

[0031] The illegal behaviors include occupying fire access, non-parking, non-correct parking direction, and overtime parking;

[0032] The point deduction amount of overtime parking is calculated by the following formula:

[0033] ;

[0034] In the formula, is the overtime deduction coefficient, is the illegal level coefficient, is the actual parking time, is the reservation allowed parking time.

[0035] As a further scheme of the present application, the construction of the illegal parking behavior identification and responsibility tracing mechanism, if the visitor vehicle violates the parking management rules, the associated visitor household account is implemented with point deduction, specifically includes:

[0036] The point deduction rules corresponding to different illegal behaviors are preset, and the point value deducted by a single illegal behavior is positively correlated with the severity of the illegal behavior; the point deduction record is synchronized to the household account and generates a notification, and the cumulative deduction formula for multiple illegal behaviors is:

[0037] ;

[0038] In the formula, is the first illegal behavior basic deduction, is the repeated illegal behavior incremental coefficient, is the number of illegal behaviors in the past 30 days.

[0039] As a further scheme of the present application, the visitor household point is divided into basic level, silver level, gold level, and diamond level in the ladder type point management model, and different levels correspond to different monthly reservation times. The calculation method of the monthly visitor vehicle reservation times corresponding to different levels is:

[0040] ;

[0041] wherein, is the basic level reservation times, default 3 times / month, is the integral-time conversion coefficient, increase once every 10 points, is the current integral value of the visited household, and when , .

[0042] As a further scheme of the present application, in another aspect, a wisdom community ground vehicle management system based on artificial intelligence, the system comprises:

[0043] A two-way binding module is configured to two-way bind and associate a visiting guest vehicle with a visited household, and uniquely correspond the guest vehicle information with the household account;

[0044] A reservation management module is configured to manage the guest vehicle access process by adopting a reservation system;

[0045] An audit module is configured to conduct compliance audit on the reservation information;

[0046] A positive feedback module is configured to build a mechanism for identifying illegal parking behavior and tracing responsibility, and if the guest vehicle violates the parking management rules, the integral of the associated visited household account is deducted;

[0047] A ladder management module is configured to establish a ladder management model for the integral of the visited household, and open different welfare treatments of the guest vehicle management authority according to the integral level.

[0048] As a further scheme of the present application, the positive feedback module specifically comprises:

[0049] A positioning unit is configured to locate the associated visited household account through the two-way binding relationship;

[0050] A real-time acquisition unit is configured to deploy intelligent cameras, ground coils or sensor networks at targeted positions in the community to acquire real-time vehicle parking data;

[0051] An identification and deduction unit is configured to identify illegal behavior by using AI visual algorithm and deduct the integral.

[0052] As a further scheme of the present application, the positive feedback module specifically further comprises:

[0053] An integral deduction unit is configured to preset integral deduction rules corresponding to different illegal behaviors, and the integral value deducted by a single illegal behavior is positively correlated with the severity of the illegal behavior;

[0054] A synchronous notification unit is configured to synchronize the integral deduction record to the household account and generate a notification.

[0055] The application provides a kind of intelligent community ground vehicle management method and system based on artificial intelligence, the method and system are clearly responsible subject by two-way binding and responsibility traceability;Reservation system and intelligent audit improve traffic efficiency;Integral ladder management stimulates the enthusiasm of residents to participate in management. Realize community parking order optimization, management cost reduction, significantly improve community security and resident satisfaction. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 It is a kind of main flow chart of intelligent community ground vehicle management method based on artificial intelligence.

[0057] Figure 2 It is a kind of flow chart for uniquely corresponding visitor vehicle information and resident account in the intelligent community ground vehicle management method based on artificial intelligence by two-way binding and associating external visitor vehicle and visited resident.

[0058] Figure 3 It is a kind of flow chart for adopting reservation system to manage visitor vehicle entry and conducting compliance audit on reservation information in the intelligent community ground vehicle management method based on artificial intelligence.

[0059] Figure 4 It is a kind of flow chart for constructing rule violation parking behavior identification and responsibility traceability mechanism in the intelligent community ground vehicle management method based on artificial intelligence, if visitor vehicle violates parking management rules, implement integral deduction on associated visited resident account.

[0060] Figure 5 It is a kind of flow chart for constructing rule violation parking behavior identification and responsibility traceability mechanism in the intelligent community ground vehicle management method based on artificial intelligence, if visitor vehicle violates parking management rules, implement integral deduction on associated visited resident account.

[0061] Figure 6 It is a kind of main structure diagram of intelligent community ground vehicle management system based on artificial intelligence.

[0062] Figure 7 It is a kind of structure block diagram of positive feedback module first embodiment in the intelligent community ground vehicle management system based on artificial intelligence.

[0063] Figure 8 It is a kind of structure block diagram of positive feedback module second embodiment in the intelligent community ground vehicle management system based on artificial intelligence. DETAILED DESCRIPTION

[0064] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0065] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0066] This invention provides an artificial intelligence-based smart community ground vehicle management method and system, which solves the technical problems in the background art.

[0067] like Figure 1 The diagram shown is a main flowchart of an artificial intelligence-based smart community ground vehicle management method according to an embodiment of the present invention. The artificial intelligence-based smart community ground vehicle management method includes:

[0068] Step S100: Two-way binding and association between external visitor vehicles and visited residents, uniquely linking visitor vehicle information with resident accounts;

[0069] Step S200: Implement an appointment system to manage visitor vehicle entry and conduct compliance review of appointment information;

[0070] Step S300: Establish a mechanism for identifying and tracing responsibility for illegal parking. If a visitor's vehicle violates parking management rules, points will be deducted from the associated resident's account.

[0071] Step S400: Establish a tiered management model for visitor points, and grant visitor vehicle management permissions with different benefits based on the point level;

[0072] The embodiment is applied to collect license plate information, reservation time and other data in the process of two-way binding, and to realize one-to-one binding of the visiting vehicle and the visited household by using blockchain technology or database unique index. The core purpose is to break the dilemma of unclear responsibility in traditional management, establish clear responsibility traceability chain, ensure that each visiting vehicle entering the community is associated with a specific household, avoid the situation that no one is responsible after the violation occurs, and improve the rigor and standardization of management from the source. The vehicle entry management adopts the reservation system. After the household initiates the reservation through the mobile terminal, the system combines the community parking capacity, time limit for road use rules, uses artificial intelligence algorithm to audit the visitor identity, vehicle information, access time and other compliance, and generates dynamic access credentials. This step avoids congestion during peak hours by planning vehicle entry and exit in advance, and improves the efficiency of community vehicle access. On the other hand, the strict audit mechanism can effectively prevent potential security risks, ensure the authenticity of the visitor's identity and the purpose of the vehicle entering the community, and protect the safety of community residents and their property. For the problem of illegal parking, real-time data is collected by intelligent cameras, ground coils and other devices, and AI vision algorithm is used to accurately identify illegal behavior. Once the violation is found, the associated visited household account will be deducted points. This mechanism changes the situation of lagging behind and poor effect in traditional management, and by linking the violation responsibility with the household points, it encourages the household to actively control the visitor's parking behavior, forming a self-management mode of "household-visitor", strengthening the responsibility constraint, and reducing the cost of property management. In addition, a visited household point ladder management model is constructed, and the households are divided into different levels such as basic level, silver level, gold level and diamond level according to the points. Each level corresponds to different visitor vehicle management permissions and welfare treatment. The model is incentive-oriented, and uses points as a quantitative indicator to link the degree of household participation in community parking order maintenance with the rights and interests they can enjoy, to stimulate the enthusiasm of households in actively participating in community management, to promote the community to form a good governance ecology of co-construction, co-governance and co-sharing, and to ultimately achieve the multiple goals of optimizing community parking order, reducing management cost and improving resident satisfaction.

[0073] As shown in Figure 2 As a preferred embodiment of the present application, the two-way binding associates the visiting vehicle with the visited household, and the unique correspondence of the visitor vehicle information and the household account specifically includes:

[0074] Step S101: Collecting license plate information, reservation time, and access object data of the visitor vehicle;

[0075] Step S102: Realizing the two-way binding relationship of the visitor vehicle and the household account by using blockchain technology or database unique index;

[0076] Step S103: The uniqueness of the binding relationship is verified by a hash function:

[0077] ;

[0078] wherein, is a visitor vehicle identification code, is a reservation timestamp, is a visited household name, is a pre-stored binding hash value;

[0079] In the application of the embodiment, the core information of the visitor vehicle is first comprehensively collected, covering the vehicle identification code VIN, the reservation timestamp T, and the visited household name UID key data. The vehicle identification code, as the "digital identity card" of the vehicle, has uniqueness and can accurately lock a specific vehicle; the reservation timestamp T records the planned time period of the vehicle entering the community, which is used for subsequent time compliance verification; the visited household name clearly defines the responsible subject and associates the vehicle with the household. In the data processing and storage link, the blockchain technology or the database unique index is used to realize the two-way binding relationship between the visitor vehicle and the household account. The blockchain technology, with its decentralized and tamper-proof characteristics, stores the binding information in the form of a distributed ledger, ensuring the security and credibility of the data; the database unique index optimizes the data structure to ensure data integrity while improving data query and call efficiency, meeting the needs of high-frequency information interaction of community vehicle management. To further ensure the uniqueness and accuracy of the binding relationship, a hash function is introduced for verification. Through the calculation of the hash function, the collected key information is encrypted and operated to generate a unique hash value, which is compared with the pre-stored binding hash value . If they are consistent, it proves that the binding relationship has not been tampered with and is unique and effective; if they are not consistent, the system immediately triggers an abnormal warning and prompts the management personnel to conduct manual verification.

[0080] As shown in Figure 3 , as a preferred embodiment of the present application, the visitor vehicle entry process managed by reservation and the compliance audit of reservation information specifically includes:

[0081] Step S201: The visited household initiates a visitor vehicle reservation through a mobile terminal application;

[0082] Step S202: Collect and verify visitor vehicle reservation information;

[0083] The vehicle reservation information includes visitor identity, vehicle information, and access period;

[0084] Step S203: Based on the community parking capacity and period limit rule, the audit is performed, and a dynamic access credential is calculated and generated;

[0085] The calculation process of the dynamic access credential is:

[0086] ;

[0087] In the formula, the is a peak period weight, is a reservation duration factor, is a period conflict coefficient, is a household score level correction, is a corresponding weight coefficient;

[0088] When the community parking capacity is saturated, a reservation failure voucher is generated;

[0089] When the community parking capacity is not saturated, and , a reservation pass voucher is generated;

[0090] When the community parking capacity is not saturated, and , a system review notice is generated;

[0091] When the community parking capacity is not saturated, and , a reservation failure and alternative period notice is generated;

[0092] In the application of the embodiment, in the reservation initiation stage, the household submits the visitor vehicle reservation application conveniently through the mobile terminal application. This design breaks the limitations of traditional offline registration or telephone reservation. The household only needs to input the visitor identity information, vehicle license plate, and expected access period on the mobile terminal to complete the reservation process. The popularity of mobile terminals not only improves the convenience of household operation, but also initiates the core compliance audit mechanism after the system receives the reservation information. The community parking capacity, period restriction rules, and other management strategies are converted into executable calculation logic. In terms of parking capacity, the system monitors the number of idle parking spaces in the community in real time, and judges whether there are sufficient parking spaces based on the reservation information, to avoid parking chaos caused by excessive vehicle influx. At the same time, the period restriction rules are audited, and dynamic access vouchers are calculated and generated. The calculation items include the peak period weight (1 for 7:00-9:00 in the morning and 17:00-19:00 in the evening, and 0.5 for other periods), the reservation duration factor (0.1 weight per hour for more than 4 hours), the period conflict coefficient (0-1 overlap rate with existing reservations), the household score level correction (diamond level 0.8, gold level 0.9, silver level 1.0, and basic level 1.2).

[0093] As shown in Figure 4 , as a preferred embodiment of the present application, the construction of the illegal parking behavior identification and responsibility tracing mechanism includes:

[0094] Step S301: Locate the associated visitor household account through a bidirectional binding relationship;

[0095] Step S302: Deploy intelligent cameras, ground coils or sensor networks at targeted locations within the community to collect real-time vehicle parking data;

[0096] Step S303: Identify violations using AI vision algorithms and deduct points;

[0097] The violations include occupying fire access, non-parking, incorrect parking direction, and overtime parking;

[0098] Wherein, the point deduction amount for overtime parking is calculated by the following formula:

[0099] ;

[0100] In the formula, is the overtime deduction coefficient, is the violation level coefficient, is the actual parking time, is the reservation allowed parking time;

[0101] It should be understood that relying on the intelligent sensing network deployed within the community, including high-definition cameras, ground coils, and parking sensors, real-time vehicle parking data is collected. High-definition cameras can capture the specific location, posture, and surrounding environment information of the vehicle through wide-angle coverage and high-definition imaging; ground coils and parking sensors can accurately determine the parking state and vehicle parking duration through electromagnetic induction and pressure monitoring. These multi-source sensing devices form a comprehensive and dead-angle-free data collection network, providing real-time and accurate data basis for violation identification. In the data processing link, AI vision algorithms play a core role. Based on a deep learning model, the system constructs a violation behavior detection engine with strong feature extraction and pattern recognition capabilities through training on a large number of violation parking samples (such as occupying fire access, non-parking, and overtime parking scenarios). In the identification of fire access violations, the algorithm can automatically identify the vehicle outline and occupancy state in the access area, combined with the pre-set access boundary model, to quickly determine whether there is a violation; for overtime parking behavior, the system monitors the time stamp and parking occupancy state, and determines overtime according to the reservation duration rule. Once a violation is identified, the system immediately activates the responsibility tracing mechanism. Based on the bidirectional binding relationship between the visitor vehicle and the visited household established in claim 2, the violating vehicle is accurately matched to the responsible household account, and in terms of violation handling, the system implements punishment on the responsible household account according to the pre-set point deduction rules. The point deduction amount is not only related to the severity of the violation, but also accurately calculated through a quantitative formula, which takes into account the violation level coefficient Fire access occupancy , common area overtime , overtime time difference and basic deduction coefficient , ensure that the punishment is matched with the violation behavior. At the same time, the violation record and the integral change information are synchronized to the mobile terminal of the resident in real time, forming a transparent management feedback.

[0102] As shown in Figure 5 , as a preferred embodiment of the present application, the construction of the violation parking behavior identification and responsibility tracing mechanism includes:

[0103] Step S311: presetting the integral deduction rules corresponding to different violation behaviors, and the integral value deducted by a single violation is positively correlated with the severity of the violation;

[0104] Step S312: the integral deduction record is synchronized to the resident account and a notification is generated;

[0105] The cumulative deduction formula for multiple violations is:

[0106] ;

[0107] In the formula, is the basic deduction for the first violation, is the repeated violation incremental coefficient, is the number of violations in the past 30 days;

[0108] In the application of the present embodiment, in order to deal with the repeated violation problem, an incremental cumulative deduction formula is added, through the exponential growth of the punishment, a strong deterrent to habitual behavior is formed, and in the time dimension, a sliding window mechanism is used to dynamically calculate the violation frequency. By maintaining the violation record timestamp for the past 30 days, combined with the time decay algorithm, it is ensured that the punishment reflects the recent behavior performance and avoids the long-term cumulative effect of historical records. When the violation behavior exceeds the 30-day tracing period, the count is automatically reset.

[0109] As a preferred embodiment of the present application, the stepwise integral management model divides the visitor resident integral into basic level, silver level, gold level and diamond level, and different levels correspond to different monthly reservation times. The calculation method of the monthly visitor vehicle reservation times corresponding to different levels is:

[0110] ;

[0111] In the formula, is the basic level reservation times, which is 3 times / month by default, is the integral-time conversion coefficient, which increases by one time every 10 minutes, is the current integral value of the visited household, and when , ;

[0112] The integral-privilege dynamic mapping mechanism is set, the basic privilege is maintained when the user is at the integral basic level, and it is ensured that all households enjoy the minimum service, the integral is converted into actual convenience when the user is at the silver level, forming continuous motivation, and the user can open exclusive services through a higher threshold when the user is at the gold level and the brick level.

[0113] As shown in Figure 6 , as another preferred embodiment of the present application, in another aspect, an artificial intelligence intelligent community ground vehicle management system, the system comprises:

[0114] The bidirectional binding module 100 is used for bidirectional binding and association of the external visitor vehicle and the visited household, and uniquely corresponds the visitor vehicle information and the household account;

[0115] The reservation management module 200 is used for managing the visitor vehicle entering process by reservation system;

[0116] The audit module 300 is used for compliance auditing of the reservation information;

[0117] The positive feedback module 400 is used for constructing a violation parking behavior identification and responsibility tracing mechanism, and if the visitor vehicle violates the parking management rules, the integral of the associated visited household account is deducted;

[0118] The ladder type management module 500 is used for establishing a ladder type management model of the visited integral, and opening the visitor vehicle management privilege of different welfare treatment according to the integral level.

[0119] In the application of the present embodiment, the bidirectional binding module 100 bidirectionally binds and associates the external visitor vehicle and the visited household, and uniquely corresponds the visitor vehicle information and the household account, the reservation management module 200 manages the visitor vehicle entering process by reservation system, the audit module 300 audits the compliance of the reservation information, the positive feedback module 400 constructs a violation parking behavior identification and responsibility tracing mechanism, and if the visitor vehicle violates the parking management rules, the integral of the associated visited household account is deducted, and the ladder type management module 600 establishes a ladder type management model of the visited integral, and opens the visitor vehicle management privilege of different welfare treatment according to the integral level.

[0120] As shown in Figure 7 , as another preferred embodiment of the present application, the positive feedback module 400 specifically comprises:

[0121] The positioning unit 401 is used for positioning the associated visited household account through the bidirectional binding relationship;

[0122] The real-time acquisition unit 402 is configured to deploy intelligent cameras, ground coils or sensor networks at targeted positions in the community to acquire vehicle parking data in real time.

[0123] The identification and deduction unit 403 is configured to identify illegal behaviors by using an AI vision algorithm and deduct points.

[0124] In the application, the positioning unit 401 positions the associated visitor household account through a bidirectional binding relationship, the real-time acquisition unit 402 deploys intelligent cameras, ground coils or sensor networks at targeted positions in the community to acquire vehicle parking data in real time, and the identification and deduction unit 403 identifies illegal behaviors by using an AI vision algorithm and deducts points.

[0125] As shown in Figure 8 As another preferred embodiment of the present application, the positive feedback module 400 further comprises:

[0126] The point deduction unit 404 is configured to preset point deduction rules corresponding to different illegal behaviors, and the point value deducted for a single illegal behavior is positively correlated with the severity of the illegal behavior.

[0127] The synchronous notification unit 405 is configured to synchronize the point deduction record to the household account and generate a notification.

[0128] In the application, the point deduction unit 404 presets point deduction rules corresponding to different illegal behaviors, and the point value deducted for a single illegal behavior is positively correlated with the severity of the illegal behavior, and the synchronous notification unit 405 synchronizes the point deduction record to the household account and generates a notification.

[0129] The above embodiment of the present application provides an artificial intelligence intelligent community ground vehicle management method and an artificial intelligence intelligent community ground vehicle management system. In the two-way binding link, the license plate information, reservation time and other data are collected, and the blockchain technology or database unique index is used to realize one-to-one binding of the visiting vehicle and the visited household. The core purpose is to break the dilemma of unclear responsibility subject in traditional management, establish clear responsibility traceability chain, ensure that each visiting vehicle entering the community can form a responsibility association with a specific household, avoid the situation that no one is responsible after the violation occurs, and improve the rigor and standardization of management from the source. The vehicle entry management adopts the reservation system. After the household initiates the reservation through the mobile terminal, the system combines the community parking capacity, time limit for road use rules, uses the artificial intelligence algorithm to audit the visitor identity, vehicle information, access time and other compliance, and generates a dynamic access credential. This step avoids congestion during peak hours by planning vehicle entry and exit in advance, and improves the efficiency of community vehicle access. On the other hand, the strict audit mechanism can effectively prevent potential security risks, ensure the authenticity of the visitor's identity and the compliance of the purpose, and protect the safety of the community residents and their property. For the problem of illegal parking, real-time data is collected by means of intelligent cameras, ground coils and other devices, and AI vision algorithm is used to accurately identify illegal behaviors. Once the violation is found, the associated visited household account is deducted. This mechanism changes the situation of lagging behind and poor effect in traditional management, and by linking the illegal responsibility with the household points, the household actively restricts the visitor's parking behavior, forming a self-management mode of "household-visitor", strengthening the responsibility restriction, and reducing the cost of property management. In addition, a visited household point ladder management model is constructed, and the households are divided into different levels such as basic level, silver level, gold level and diamond level according to the points. Each level corresponds to different visitor vehicle management permissions and welfare treatment. The model is incentive-oriented, and uses points as a quantitative indicator to link the degree of household participation in community parking order maintenance with the rights and interests they can enjoy, motivating households to actively participate in community management, promoting the community to form a benign governance ecology of co-construction, co-governance and sharing, and ultimately achieving the multiple goals of optimizing community parking order, reducing management cost and improving resident satisfaction. The method and system can clearly identify the responsibility subject of the violation through two-way binding and responsibility traceability, improve the access efficiency through reservation and intelligent audit, and stimulate the enthusiasm of households in participating in management through point ladder management. The community parking order is optimized, the management cost is reduced, and the safety and satisfaction of the community are significantly improved.

[0130] In order to enable the above method and system to run smoothly, the system can include more or fewer components than described above, or combine certain components, or different components, such as input and output devices, network access devices, buses, processors and memories.

[0131] The processor can be a central processing unit, and can also be other general purpose processors, digital signal processors, application specific integrated circuits, programmable logic devices, discrete gates or transistor logic components, discrete hardware components, etc. The general purpose processor can be a microprocessor or can also be any conventional processor. The processor is the control center of the system, and is connected with various parts by various interfaces and lines.

[0132] Any combination of the technical features in the above-described embodiments can be made, and in order to make the description simple, all possible combinations of the technical features in the above-described embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered that it is within the scope of the description.

[0133] The above-described embodiments only express several implementation manners of the present application, the description is relatively specific and detailed, but it should not be understood as a limitation on the patent scope of the present application. It should be pointed out that, for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

[0134] The above-described is only the preferred embodiment of the present application, and does not limit the present application, any modification, equivalent replacement and improvement within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A smart community ground vehicle management method based on artificial intelligence, characterized in that, The method includes: Two-way binding links visitor vehicles with visited residents, uniquely matching visitor vehicle information with resident accounts; A reservation system is adopted to manage the entry process for visitor vehicles, and the reservation information is subject to compliance review. Establish a mechanism for identifying and holding accountable illegal parking behavior. If a visitor's vehicle violates parking management rules, points will be deducted from the associated resident's account. Establish a tiered management model based on visitor points, and grant visitor vehicle management permissions with different benefits according to the point level; The aforementioned management of visitor vehicle entry using a reservation system, and the compliance review of reservation information, specifically includes: The residents being visited can make a reservation for a visitor's vehicle via a mobile application; Collect and verify visitor vehicle reservation information, which includes visitor identity, vehicle information, and visit time period; Based on the community's parking capacity and time-limited traffic rules, a dynamic access pass is calculated and generated. The calculation process for the dynamic access pass is as follows: ； In the formula, the Weighted by peak hours, For reservation duration factor, This represents the time-segment conflict coefficient. Resident points level adjustment These are the corresponding weighting coefficients; When the community parking capacity is full, a reservation failure certificate is generated. When the community's parking capacity is not saturated, and Generate an appointment approval certificate; When the community's parking capacity is not saturated, and Generate a system review notification; When the community's parking capacity is not saturated, and Generate notifications for failed reservations and alternative time slots; The mechanism for identifying and holding accountable those who violate parking rules, specifically including deducting points from the associated resident's account if a visitor's vehicle violates parking management rules, includes: The system locates the associated visited resident accounts through a two-way binding relationship. Deploy smart cameras, inductive loops, or sensor networks at targeted locations within the community to collect vehicle parking data in real time; Use AI visual algorithms to identify violations and deduct points accordingly; The violations include blocking fire lanes, parking outside designated parking spaces, parking in the wrong direction, and parking beyond the permitted time limit; The points deduction for overstaying are calculated using the following formula: ； In the formula, This is the penalty coefficient for exceeding the time limit. This represents the violation level coefficient. This refers to the actual parking time. Parking is permitted for a specified time by reservation; The mechanism for identifying and holding accountable those who violate parking rules, which includes deducting points from the associated resident's account if a visitor's vehicle violates parking management rules, further includes: The system pre-determines point deduction rules for different violations, with the point deduction for a single violation being positively correlated with the severity of the violation; point deduction records are synchronized to the resident's account and a notification is generated. The formula for cumulative deductions for multiple violations is as follows: ； In the formula, The first violation will result in a basic deduction of points. The coefficient for repeated violations is the incrementing factor. This refers to the number of violations recorded over a 30-day period.

2. The method for managing ground vehicles in a smart community based on artificial intelligence according to claim 1, characterized in that, The two-way binding link between visiting vehicles and visited residents, uniquely mapping visitor vehicle information to resident accounts, specifically includes: Collect visitor vehicle license plate information, appointment time, and visitor data; A two-way binding relationship between visitor vehicles and resident accounts can be achieved through blockchain technology or unique database indexes; The uniqueness of the binding relationship is verified using a hash function: ； In the formula, For visitor vehicle identification numbers, For reservation timestamps, The name of the resident being visited. Pre-stored binding hash value.

3. The method for managing ground vehicles in a smart community based on artificial intelligence according to claim 1, characterized in that, The tiered management model categorizes visitor / resident points into Basic, Silver, Gold, and Diamond levels, with each level corresponding to a different monthly reservation limit. The calculation method for the monthly visitor vehicle reservation limit for each level is as follows: ； In the formula, The basic booking limit is 3 bookings per month by default. This is the integral-to-degree conversion factor, which increases once every 10 points. The current points value of the visited resident, and when hour, .

4. A smart community ground vehicle management system based on artificial intelligence, characterized in that, The system employs the AI-based smart community ground vehicle management method as described in any one of claims 1-3, wherein the system comprises: The two-way binding module is used to link external visitor vehicles with the visited residents, uniquely matching visitor vehicle information with resident accounts; The appointment management module is used to manage the visitor vehicle entry process using an appointment system. The review module is used to review the compliance of appointment information; The positive feedback module is used to build a mechanism for identifying and tracing responsibility for illegal parking. If a visitor's vehicle violates parking management rules, points will be deducted from the associated resident's account. The tiered management module is used to establish a tiered management model based on visitor points, and to grant different levels of visitor vehicle management permissions based on the point level. The positive feedback module specifically includes: Location unit, used to locate the associated visited resident account through a two-way binding relationship; The real-time acquisition unit is used to deploy smart cameras, ground loop coils, or sensor networks at targeted locations within the community to collect vehicle parking data in real time. The identification and deduction unit is used to identify violations and deduct points using AI vision algorithms; The positive feedback module specifically also includes: The points deduction unit is used to preset the points deduction rules for different violations. The points deducted for a single violation are positively correlated with the severity of the violation. The synchronization notification unit is used to synchronize points deduction records to the resident's account and generate a notification.

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