Parking management method based on smart community closed management

Abstract

The invention relates to the technical field of parking management, and particularly discloses a parking management method based on smart community closed management, comprising the following steps: S1, acquiring a monitoring video, intercepting a target video, and recording the duration of the acquired target video as a target duration; counting the number of the target parking spaces of the same type, and calculating a mean value of target durations corresponding to the target parking spaces of the same type; s2, calculating sorting values, and marking the type of the target parking space corresponding to the maximum sorting value as an ideal type; obtaining a target position, calculating a selection distance based on the target position, and determining a target building according to the selection distance; s3, determining a real-time building and a real-time type corresponding to the real-time vehicle, and determining a recommended parking space A; and determining a target route from the real-time vehicle to the recommended parking space A, and recommending the target route to the user. According to the invention, the parking convenience of the user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of parking management, and particularly to a parking management method based on the closed management of an intelligent community. Background Art

[0002] The closed management system of an intelligent community consists of a cloud platform and front-end intelligent sensing devices. The platform provides remote supervision and operation management services for the community property. Through the platform, the property can centrally manage the access control and parking situations of community residents and visitors, realizing the centralized control of people, vehicles, and objects in the community.

[0003] During the parking process, users usually choose a suitable parking method according to the specific situation of the parking space, such as reverse parking into the garage or parallel parking, etc. However, different users may have different levels of proficiency in these parking methods. For example, some users are more proficient in reverse parking into the garage, so when they choose a parking space, they tend to look for those parking spaces suitable for reverse parking. In this process, users usually do not know the exact location of the parking space and often need to rely on themselves to find a suitable parking space, which makes the entire parking process lack convenience. Summary of the Invention

[0004] The purpose of the present invention is to provide a parking management method based on the closed management of an intelligent community, and solve the following technical problems:

[0005] Different users may have different levels of proficiency in these parking methods. For example, some users are more proficient in reverse parking into the garage, so when they choose a parking space, they tend to look for those parking spaces suitable for reverse parking. In this process, users usually do not know the exact location of the parking space and often need to rely on themselves to find a suitable parking space, which makes the entire parking process lack convenience.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A parking management method based on the closed management of an intelligent community includes the following steps:

[0008] S1: Obtain the surveillance video inside the intelligent community, intercept the surveillance video from the time point when the user starts parking to the time point when the parking ends, and record it as the target video. Calculate a sorting value based on the target video. The sorting value is used to measure the proficiency of the user when parking in different types of parking spaces, and determine the ideal type based on the sorting value;

[0009] S2: Determine the target building of the user according to the position where the user leaves the surveillance screen after parking. The target building is the building that the user goes to after parking;

[0010] S3: Denote the vehicles entering the smart community as real-time vehicles, determine the target building and ideal type corresponding to the real-time vehicle, and denote them as the real-time building and real-time type. Determine the parking space with the shortest distance between the types belonging to the real-time type and the real-time building, and denote it as the recommended parking space A;

[0011] Obtain all the feasible routes between the real-time vehicle and the recommended parking space A, denote the shortest feasible route as the target route, and recommend to the user to go to the recommended parking space A along the target route.

[0012] As a further solution of the present invention: In the step S1, the following steps are further included:

[0013] When the number of the target videos is less than the preset number threshold, the subsequent steps are not executed.

[0014] As a further solution of the present invention: In the step S3, the following steps are further included:

[0015] When the length of the target route is greater than or equal to the preset length threshold, remove the recommended parking space A and obtain a new recommended parking space.

[0016] As a further solution of the present invention: In the step S2, the process of determining the target building specifically includes:

[0017] When the type of the parking space where the user parks belongs to the ideal type, determine the position where the user leaves the monitoring screen for the last time within the preset time period, denote it as the target position, obtain the shortest distance between a single target position and building i, calculate the sum of the shortest distances as the pending distance of building i, and calculate the average value of the pending distance of building i as the selected distance Di;

[0018] Obtain the minimum selected distance Dmin=(Djh), the selected distance set Djh=(D 1 , D 2 , …, Dn), and take the building corresponding to the minimum selected distance as the target building, where n represents the total number of buildings.

[0019] As a further solution of the present invention: In the step S2, when there are two or more sorting values that are the same and the largest, take the sorting value with a larger number of target parking spaces as the largest sorting value.

[0020] As a further solution of the present invention: In the step S2, when two or more selected distances are the same and the shortest, the following steps are executed:

[0021] Mark the buildings corresponding to the same and shortest selected distances as the buildings to be selected, sort the pending distances corresponding to the buildings to be selected in descending order to obtain the distance sorting;

[0022] Obtain the candidate building with the shortest distance at the sorting position of the c-th in the obtained distance sorting, and record that the selection value of this candidate building is incremented by 1;

[0023] Take the candidate building corresponding to the maximum selection value as the target building.

[0024] As a further solution of the present invention: in the process of obtaining the above-mentioned distance sorting, the following steps are further included:

[0025] Obtain the total number of undetermined distances in the distance sorting, obtain the minimum total number X, if the total number Y of undetermined distances in the distance sorting y > X, then starting from the first undetermined distance in the distance sorting y, retain the first X undetermined distances in the distance sorting y to obtain a new distance sorting y.

[0026] As a further solution of the present invention: in step S3, when the distances of two or more feasible routes are the same and the shortest, select the feasible route with the smallest number of people as the target route.

[0027] As a further solution of the present invention: in step S1, the process of determining the ideal type specifically includes:

[0028] Obtain the duration of the target video, denoted as the target duration;

[0029] Denote the parking space where the user parks as the target parking space, count the number m of target parking spaces of the same type, and calculate the average value t of the target durations corresponding to the target parking spaces of the same type;

[0030] Calculate the sorting value K = η * m / t, where η is a preset correction coefficient, and denote the type of the target parking space corresponding to the maximum sorting value as the ideal type

[0031] Advantages of the present invention: In this solution, by obtaining the surveillance video and calculating the parking time, parking space type, and target duration, the specific situation during the parking process can be accurately understood; by statistically calculating the average parking duration of the same type of parking space, it helps to analyze which types of parking spaces are used more frequently and have relatively short or long parking times, which provides data support for subsequent parking space recommendations and enables a more scientific assessment of the utilization of parking spaces; detailed historical data is provided for the subsequent steps of parking space selection and route planning, thereby improving the accuracy and practicality of the solution recommendations; by calculating the sorting value and finding the target parking space type corresponding to the maximum sorting value, an ideal parking space selection based on historical data and parking behavior is provided for the user, that is, according to the user's historical parking behavior, it is determined which type of parking space the user is good at parking in, such as a parking space that requires reverse parking or a side parking space, etc.; through the screening of the ideal parking space type, parking spaces and routes are recommended to the user without the user having to search on their own, which not only improves the speed at which the car owner finds a parking space, but also reduces the overall parking waiting time and energy consumption by reducing the driving time of the vehicle in the community, further enhancing the user's parking experience and the utilization efficiency of the parking lot. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The present invention will be further described below with reference to the accompanying drawings.

[0033] Figure 1 is a flowchart of a parking management method based on the closed management of a smart community according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying 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 of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] Please refer to Figure 1 as shown, the present invention is a parking management method based on the closed management of a smart community, including the following steps:

[0036] S1: Obtain the surveillance video inside the smart community, intercept the surveillance video within the time period from the time point when the user starts parking to the time point when the parking ends, and record it as the target video. Calculate the sorting value based on the target video. The sorting value is used to measure the proficiency of the user when parking in different types of parking spaces, and determine the ideal type based on the sorting value;

[0037] S2: Determine the target building of the user according to the position where the user leaves the surveillance screen after parking. The target building is the building that the user goes to after parking;

[0038] S3: Denote the vehicles entering the smart community as real-time vehicles, determine the target building and ideal type corresponding to the real-time vehicle, and denote them as the real-time building and real-time type. Determine the parking space with the shortest distance from the real-time building among those whose type belongs to the real-time type, and denote it as the recommended parking space A;

[0039] Obtain all the feasible routes between the real-time vehicle and the recommended parking space A, denote the shortest feasible route as the target route, and recommend to the user to go to the recommended parking space A along the target route.

[0040] It should be noted that by obtaining the surveillance video and calculating the parking time, parking space type, and target duration, the specific situation during the parking process can be accurately understood; by statistically averaging the parking durations of the same type of parking spaces, it helps to analyze which types of parking spaces are used more frequently and have relatively shorter or longer parking times, which provides data support for subsequent parking space recommendations and enables a more scientific assessment of the usage of parking spaces; it provides detailed historical data for parking space selection and path planning in subsequent steps, thereby improving the accuracy and practicality of the scheme recommendation; by calculating the sorting value and finding the target parking space type corresponding to the maximum sorting value, an ideal parking space selection based on historical data and parking behavior is provided for the user, that is, according to the user's historical parking behavior, it is determined which type of parking space the user is good at parking in, such as a parking space that requires reverse parking or a side parking space, etc.; through the screening of the ideal parking space type, parking spaces and routes are recommended to the user without the user having to search on their own, which not only improves the speed of the car owner to find a parking space, but also reduces the overall parking waiting time and energy consumption by reducing the driving time of the vehicle in the community, further enhancing the user's parking experience and the utilization efficiency of the parking lot;

[0041] It can be understood that the surveillance video is based on the mutual cooperation of the surveillance devices within the smart community, and the target duration can be intercepted in a manual manner or selectively achieved through a pre-trained artificial intelligence model; the method steps for training the artificial intelligence model are already relatively mature and will not be elaborated here;

[0042] It should be noted that the ideal type is the type of parking space that the user is good at parking in, screened according to the user's historical behavior;

[0043] In another preferred embodiment of the present invention, in the step S1, the following steps are further included:

[0044] When the number of the target videos is less than the preset number threshold, the subsequent steps are not executed.

[0045] It is worth noting that the risk of performing invalid or incorrect analysis when the data is insufficient or of substandard quality is avoided. If the number of target videos is too small, it may not be possible to provide sufficient parking behavior data to support accurate parking space selection and route recommendation, thus avoiding parking recommendation errors caused by incomplete data.

[0046] In another preferred embodiment of the present invention, in step S3, the following steps are further included:

[0047] When the length of the target route is greater than or equal to a preset length threshold, remove the recommended parking space A and obtain a new recommended parking space.

[0048] In another preferred embodiment of the present invention, in step S2, the process of determining the target building specifically includes:

[0049] When the type of the parking space where the user parks belongs to the ideal type, determine the position where the user leaves the monitoring screen for the last time within a preset time period, record it as the target position, obtain the shortest distance between a single target position and building i, calculate the sum of the shortest distances as the pending distance of building i, and calculate the average value of the pending distance of building i as the selection distance Di;

[0050] Obtain the minimum selection distance Dmin=(Djh), the selection distance set Djh=(D 1 , D 2 , …, Dn), and take the building corresponding to the minimum selection distance as the target building, where n represents the total number of buildings.

[0051] In another preferred embodiment of the present invention, in step S2, when there are two or more sorting values that are the same and the largest, take the sorting value with a larger number of target parking spaces as the largest sorting value.

[0052] It is worth noting that when there are two or more sorting values that are the same and the largest, the following method can also be used to determine the ideal type:

[0053] Obtain the target duration of target parking spaces of the same type, sort them in chronological order, calculate the target duration difference ΔTf = Tf - Tf- 1 , where Tf represents the target duration at the fth position in the sorting. If the target duration difference ΔTf ≤ 0, record the target duration difference ΔTf as the preferred difference, count the total number of preferred differences, and take the type of target parking space corresponding to the largest total number as the target type;

[0054] In another preferred embodiment of the present invention, in step S2, when two or more selection distances are the same and the shortest, perform the following steps:

[0055] Mark the building corresponding to the same and shortest selected route as the building to be selected, and sort the undetermined routes corresponding to the buildings to be selected in descending order to obtain a route sorting;

[0056] Obtain the building to be selected with the shortest route at the c-th sorting position in the obtained route sorting, and record that the selection value of the building to be selected is incremented by 1;

[0057] Take the building to be selected corresponding to the maximum selection value as the target building.

[0058] In another preferred embodiment of the present invention, during the process of obtaining the route sorting, the following steps are further included:

[0059] Obtain the total number of undetermined routes in the route sorting, obtain the minimum total number X. If the total number Y of undetermined routes in the route sorting y > X, then starting from the first undetermined route in the route sorting y, retain the first X undetermined routes in the route sorting y to obtain a new route sorting y.

[0060] In another preferred embodiment of the present invention, in step S3, when the distances of two or more feasible routes are the same and the shortest, select the feasible route with the fewest number of people as the target route.

[0061] In another preferred embodiment of the present invention, in step S1, the process of determining the ideal type specifically includes:

[0062] Obtain the duration of the target video and record it as the target duration;

[0063] Record the parking space where the user parks as the target parking space, count the number m of target parking spaces of the same type, and calculate the average value t of the target durations corresponding to the target parking spaces of the same type;

[0064] Calculate the sorting value K = η * m / t, where η is a preset correction coefficient, and record the type of the target parking space corresponding to the maximum sorting value as the ideal type

[0065] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the patent coverage scope of the present invention.

Claims

1. A parking management method based on closed management of smart communities, characterized in that: The following steps are involved: S1: Obtain surveillance video inside the smart community, intercept the surveillance video from the time when the user starts parking to the time when the user finishes parking, record it as the target video, calculate the ranking value based on the target video, the ranking value is used to measure the user's proficiency in parking in different types of parking spaces, and determine the ideal type based on the ranking value; S2: determining the user's target building according to the location where the user leaves the monitoring screen after parking, where the target building is the building that the user goes to after parking; S3: Record the vehicles entering the smart community as real-time vehicles, determine the target building and ideal category corresponding to the real-time vehicles, and record them as the real-time building and the real-time category, and determine the parking space that belongs to the real-time category and has the shortest distance to the real-time building, and record it as the recommended parking space A; All feasible routes between the real-time vehicle and the recommended parking space A are obtained, the shortest feasible route is recorded as the target route, and the user is recommended to go to the recommended parking space A along the target route.

2. A parking management method based on closed management of smart communities according to claim 1, characterized in that: The step S1 further includes the following steps: When the number of the target videos is less than a preset number threshold, subsequent steps are not executed.

3. A parking management method based on closed management of smart communities according to claim 1, characterized in that: The step S3 further includes the following steps: When the length of the target route is greater than or equal to a preset length threshold, the recommended parking space A is removed and a new recommended parking space is obtained.

4. A parking management method based on closed management of smart communities according to claim 1, characterized in that: In step S2, the process of determining the target building specifically includes: When the type of parking space where the user parks belongs to the ideal type, determine the location where the user last left the monitoring screen within the preset time period, record it as the target location, obtain the shortest distance between a single target location and building i, calculate the sum of the shortest distances as the pending distance of building i, and calculate the average of the pending distances of building i as the selected distance Di; Get the minimum selected distance Dmin=(Djh), select the distance set Djh=(D1, D2, ..., Dn), and take the building corresponding to the minimum selected distance as the target building, where n represents the total number of buildings.

5. The parking management method based on closed management of smart community according to claim 1 is characterized in that: In the step S2, when there are two or more ranking values ​​that are the same and the largest, the ranking value with a larger number of target parking spaces is taken as the largest ranking value.

6. A parking management method based on closed management of smart communities according to claim 1, characterized in that: In step S2, when two or more selected distances are the same and the shortest, the following steps are performed: Mark the buildings corresponding to the same and shortest selected distances as buildings to be selected, and sort the pending distances corresponding to the buildings to be selected in descending order to obtain a distance sorting; Obtain the shortest building to be selected at the c-th position in the distance sorting, and add 1 to the selection value of the building to be selected; The building to be selected corresponding to the maximum selection value is taken as the target building.

7. A parking management method based on closed management of smart communities according to claim 6, characterized in that: The process of obtaining the route ranking also includes the following steps: The total number of pending distances in the distance sorting is obtained, and the minimum total number X is obtained. If the total number Y of pending distances in the distance sorting y>X, then starting from the first pending distance in the distance sorting y, the first X pending distances in the distance sorting y are retained to obtain a new distance sorting y.

8. The parking management method based on closed management of smart community according to claim 1 is characterized in that: In step S3, when two or more feasible routes have the same distance and are the shortest, the feasible route with the least number of people is selected as the target route.

9. The parking management method based on closed management of smart community according to claim 1 is characterized in that: In step S1, the process of determining the ideal type specifically includes: Obtaining the duration of the target video, recorded as target duration; The parking space where the user parks is recorded as the target parking space, the number of target parking spaces of the same type m is counted, and the mean value t of the target duration corresponding to the target parking spaces of the same type is calculated; The ranking value K=η*m / t is calculated, where η is a preset correction coefficient, and the type of the target parking space corresponding to the maximum ranking value is recorded as the ideal type.

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