A big data intelligent park management system

Abstract

The present invention discloses a big data intelligent park management system, which relates to the technical field of intelligent parks. Its technical key points include a data processing module, a parking space data acquisition module, a data analysis module, and a user terminal module. Among them, the parking space data acquisition module is used to collect the usage data of each private parking space, monitor the usage data of private parking spaces in the past six months, with one day as a monitoring cycle, and collect whether there is a private vehicle in the private parking space every 15 minutes. The data processing module is connected to the parking space data acquisition module and is used to receive and process the usage data of each private parking space. Among them, a data storage unit is provided in the data processing module. The user terminal module is connected to the data storage unit, obtains the basic information of the user and the required parking duration, and sends the obtained basic information and parking duration to the data storage unit. The data analysis module is connected to the data processing module and can improve the utilization rate of parking space resources in the park.

Description

Technical Field

[0001] The present invention relates to the technical field of smart parks, and particularly to a big data smart park management system. Background Art

[0002] A "smart park" is an intelligent management system established on the basis of park informatization construction, which helps the park establish a unified internal and external service operation platform, improves the park service efficiency, connects each data collection point and equipment control point through Internet of Things technology, and the park management system uses cloud computing, big data, and Internet technology to store, analyze, and judge data, and intelligently allocate resources.

[0003] With the growth of the number of motor vehicles and the shortage of urban land, whether it is a commercial park, an industrial science and technology park or a residential community, the shortage of parking spaces has become the norm. Now, parks generally manage parking spaces by the method of fixed parking spaces + temporary parking spaces. Generally, the number of fixed parking spaces is reserved according to the number of signed owners, and the remaining parking spaces are used as temporary parking spaces. When the temporary parking spaces in the park are used up, even if there are still many fixed parking spaces, other vehicles are not allowed to use them, resulting in the failure to make more full use of resources.

[0004] Patent Publication No. CN109493638B discloses a method and device for optimizing the management of parking spaces in a park, which includes receiving the entry information of a user's vehicle sent by the user terminal; receiving the target location information of the user sent by the user terminal; obtaining the public parking space information of the target location information according to the user's target location information; if the public parking space information is full, obtaining the private parking space information of the target location information; if the private parking space information is not full, obtaining and sending the first parking space information to the user terminal from the private parking space information.

[0005] In view of the above related technologies, although some private parking spaces in the park are utilized, they are allocated only when they have not been used for several consecutive days. For users with private parking spaces, the usage is often extremely frequent, and thus the private parking spaces will be in a long-term use state. The number of private parking spaces that have not been used for several consecutive days is very small, and thus the number of private parking spaces that can be allocated is very small. Among the vehicles entering the park, there are many vehicles that stay for a short time. During the time these vehicles stay, it still does not affect the normal use of private parking spaces. Therefore, the utilization rate of parking space resources is still not high. Therefore, in order to further improve the utilization rate of parking space resources, the present invention provides a big data smart park management system. Summary of the Invention

[0006] (1) Technical Problems to be Solved

[0007] Aiming at the deficiencies of the prior art, the present invention provides a big data smart park management system that can improve the utilization rate of parking space resources in the park.

[0008] (2) Technical Solution

[0009] To achieve the above object, the present invention provides the following technical solution: A big data intelligent park management system, including a data processing module, a parking space data acquisition module, a data analysis module, and a user terminal module, wherein;

[0010] The parking space data acquisition module is used to collect the usage data of each private parking space, monitor the usage data of private parking spaces in the past six months, with one day as a monitoring cycle, and collect whether there is a private vehicle in the private parking space every 15 minutes;

[0011] The data processing module is connected to the parking space data acquisition module and is used to receive and process the usage data of each private parking space. Among them, a data storage unit is provided in the data processing module, and the data storage unit is used to store the data processed by the data processing module;

[0012] The user terminal module is connected to the data storage unit, obtains the basic information of the user and the required parking duration, and sends the obtained basic information and parking duration to the data storage unit;

[0013] The data analysis module is connected to the data processing module, analyzes the data in the data storage unit to obtain data analysis information, and sends the data analysis information to the user terminal module; The specific analysis steps are as follows:

[0014] Step 1: Obtain the usage data of each private parking space in the past six months and the parking duration of the user;

[0015] Step 2: According to the formula

[0016]

[0017] Obtain the time points when parking can be done in each private parking space; among them, the minimum k is the parking coefficient, Nx is the number of times without parking at a certain time point in the past six months, 180 is the total number of times the parking space data acquisition module collects the usage data of private parking spaces in the past six months. Among them, when the value obtained by

[0018]

[0019] is greater than K, then this time point meets the parking requirements, and the time period from the previous time point to this time point can be used for the user to park. When the value obtained is less than K, then this time point does not meet the parking requirements, and the time period from the previous time point to this time point cannot be used for the user to park;

[0020] Step 3: Obtain the private parking spaces that meet the parking within the parking duration period;

[0021] Step 4: After obtaining multiple eligible private parking spaces, recommend private parking spaces for the user based on the larger value obtained through

[0022]

[0023] the user's basic information.

[0024] Preferably, mark the number of times that no private vehicle has parked in a private parking space in half a year as N1, N2, Nx... N96, and obtain the parking duration of the user as m; through the formula

[0025] ,

[0026] where Qy represents the coefficient that the owner of the private parking space will not use the private parking space during the parking duration, Ns is the number of times that no private vehicle has parked in the private parking space in the half year corresponding to the collection time point corresponding to the start time in the parking duration,

[0027]

[0028] and Nt is the number of times that no private vehicle has parked in the private parking space in the half year corresponding to the collection time point corresponding to the end time in the parking duration.

[0029] Preferably, only obtain the number of times that no private vehicle has parked in a private parking space on all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays or Sundays in half a year and mark them as T1, T2...; through the formula

[0030] ,

[0031] where Z is the total number of days of all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays or Sundays in half a year.

[0032] Preferably, extract the minimum number of times that no private vehicle has parked during the stay duration, and the minimum number of times extracted is Na, and through the formula

[0033] ,

[0034] For private parking spaces with a P value greater than 0.1, they are not recommended as the first choice, and the Qc and P values of each recommended private parking space are displayed together.

[0035] Preferably, the basic information input by the user terminal includes the building to go to, mobile phone number and name; the data analysis module searches for private parking spaces for the user with the building to go to as the center; when the owner of the private parking space arrives at the park, the data processing module notifies the user occupying the parking space to move the vehicle by phone or text message, and the data analysis module recommends private parking spaces for the user again.

[0036] Preferably, the data processing module is further connected to a reputation evaluation module, which rates the reputation of users. When the data analysis module notifies a user to move their vehicle, if the user moves their vehicle within the specified time for two consecutive times, they are rated as Class A; if the user fails to move their vehicle within the specified time once, they are rated as Class B; if the user fails to move their vehicle on time three consecutive times, they are rated as Class C. The data analysis module gives priority to recommending private parking spaces to Class A users. For Class A users, it gives priority to recommending users with more consecutive compliance records. When there are no public parking spaces in the park, Class C users are not allowed to enter the park.

[0037] Preferably, the parking space data acquisition module is connected to a timing module. When a user fails to move their vehicle within the specified time, the timing module starts timing. When the user's vehicle leaves the park, the data processing module charges an additional fee for the user's vehicle based on the time recorded by the timing module and transfers the additional fee to the user terminal of the private parking space owner.

[0038] Preferably, a positioning module is connected in the user terminal module. Through this positioning module, the vehicle usage information of the private parking space owner outside the park is obtained, and the data processing module records the route of the private owner returning to the park in the past six months. At the time points when private parking spaces can be recommended to users, when the owner of the private parking space moves their vehicle, the data analysis module determines whether the owner is returning to the park based on the route information of the owner returning to the park and whether the distance from the park is getting closer.

[0039] (III) Beneficial Effects

[0040] Compared with the prior art, the present invention provides a big data intelligent park management system, which has the following beneficial effects:

[0041] 1. By collecting the usage data of each private parking space through the parking space data acquisition module, the data processing module obtains the basic information of users and the parking duration through the user terminal, analyzes the data in the data storage unit through the data analysis module, and recommends private parking spaces to users based on the relatively large value obtained and the basic information of users. It can recommend suitable private parking spaces to users during their parking duration, improving the utilization rate of park resources and reducing the difficulty of managing the park;

[0042]

[0043] 2. By separately calculating the usage situations of private parking spaces on all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, or Sundays in half a year and using the value of Qc combined with P to distinguish the usage situations of private parking spaces, it can recommend suitable private parking spaces to users extremely accurately;

[0044] 2. By separately calculating the usage situations of private parking spaces on all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, or Sundays in half a year and using the value of Qc combined with P to distinguish the usage situations of private parking spaces, it can recommend suitable private parking spaces to users extremely accurately;

[0045] 3. By setting up a reputation evaluation module and using it to rate the reputation of users, users can be divided into three different levels: A, B, and C. This not only improves the enthusiasm of users to move their cars, but also screens out users with relatively low compliance ability and retains users with strong compliance ability, so as to recommend private parking spaces only for users with strong compliance ability;

[0046] 4. By connecting a positioning module to the user terminal module and obtaining the vehicle usage information of the private parking space owner outside the park through this positioning module, it is possible to obtain the route of the owner returning to the park in the past six months. Among the time points when private parking spaces can be recommended to users, when the owner of the private parking space moves the vehicle, it is possible to judge whether the owner is returning to the park based on the vehicle usage information. When the owner returns to the park through the common route, the data processing module will notify the user to move the vehicle via text message or phone call. When the owner is not driving on the common route but is getting closer to the park, and when the owner drives to a point five kilometers away from the community, the data processing module will notify the user to move the vehicle via text message or phone call, ensuring that when the owner arrives at their private parking space, there is no vehicle affecting their experience of using the private parking space.

[0047] The above description is only an overview of the technical solution of the present invention. In order to be able to more clearly understand the technical means of the present invention and implement it in accordance with the content of the specification, the following takes the preferred embodiments of the present invention and describes them in detail in conjunction with the accompanying drawings. The specific implementation manners of the present invention are given in detail by the following embodiments and their accompanying drawings. Brief Description of the Drawings

[0048] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0049] Figure 1 It is a flow diagram in the present invention. Detailed Embodiments

[0050] The following combines the attached Figure 1 The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention. In the following paragraphs, the present invention is described more specifically by way of example with reference to the accompanying drawings. It should be noted that the drawings are all in a very simplified form and use non-precise scales, only for the purpose of conveniently and clearly assisting in explaining the purpose of the embodiments of the present invention.

[0051] It should be noted that when a component is referred to as "fixed to" another component, it can be directly on the other component or there may also be an intermediate component. When a component is considered to be "connected to" another component, it can be directly connected to the other component or there may be an intermediate component at the same time. When a component is considered to be "disposed on" another component, it can be directly disposed on the other component or there may be an intermediate component at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used in this article are only for the purpose of illustration.

[0052] Unless otherwise defined, all technical and scientific terms used in this article have the same meaning as commonly understood by those skilled in the technical field to which this invention belongs. The terms used in the description of this invention in this article are only for the purpose of describing specific embodiments and are not intended to limit this invention. The term "and / or" used in this article includes any and all combinations of one or more of the related listed items.

[0053] Embodiment 1:

[0054] As shown in FIG. 1, the present invention provides a big data intelligent park management system, which includes: a data processing module, a parking space data acquisition module, a data analysis module, and a user terminal module;

[0055] Among them, the parking space data acquisition module is used to collect the usage data of each private parking space. The parking space data acquisition module can be a collection camera, which monitors and collects the usage data of each private parking space in real time. Each collection camera can monitor more than one private parking space at the same time. The parking space data acquisition module monitors the usage data of private parking spaces in the past six months, with one day as a monitoring cycle, and collects whether there is a private vehicle in the private parking space every 15 minutes. And the monitored usage data is updated every day to ensure the accuracy of the data;

[0056] The data processing module is connected to the parking space data acquisition module and is used to receive and process the usage data of each private parking space. Among them, a data storage unit is provided in the data processing module, and the data storage unit is used to store the data processed by the data processing module;

[0057] The client module is connected to the data storage unit. The client module consists of a client APP and a QR code, which obtains the basic information of the user and the parking duration required, and sends the obtained basic information and parking duration to the data storage unit. The user inputs their basic information and parking duration through the APP or by scanning the QR code. For some users who often enter and leave the park, they can give priority to using the APP, which is beneficial for them to enter the park faster. Some users who rarely enter the park can choose to enter by scanning the QR code, avoiding the situation of congestion at the park entrance caused by downloading the APP when entering the park, providing convenience for users with different needs.

[0058] The data analysis module is connected to the data processing module, analyzes the data in the data storage unit to obtain data analysis information, and sends the data analysis information to the client module. The specific analysis steps are as follows:

[0059] Step 1: Obtain the usage data of each private parking space within half a year and the parking duration of the user.

[0060] Step 2: According to the formula

[0061]

[0062] Obtain the time points when each private parking space can be parked; where k is the minimum parking coefficient, Nx is the number of times without parking at a certain time point within half a year, and 180 is the total number of times the parking space data acquisition module collects the usage data of private parking spaces within half a year. Among them,

[0063]

[0064] When the obtained value is greater than K, the time point meets the parking requirements, and the time period from the previous time point to this time point can be used for the user to park. When the obtained value is less than K, the time point does not meet the parking requirements, and the time period from the previous time point to this time point cannot be used for the user to park. Mark all the time periods that cannot be used for the user to park. Then, among the parking durations, only when all time periods can be used for the user to park, the private parking space is recommended to the user for parking. The value of K can be set to 0.8, or it can be set according to the actual situation. For example, if the scarcity of public parking spaces in the park is high and there are often situations where temporary vehicles have no public parking spaces to park, the value of K can be reduced. If the situation where temporary vehicles have no public parking spaces to park in the park is less, the value of K can be increased. The management staff can adjust the size of the K value, which is beneficial for reducing the management difficulty of the park management staff and also makes it more convenient for users to park.

[0065] Step 3: Obtain the private parking spaces that meet the parking requirements within the time period of the parking duration.

[0066] Step 4: After obtaining multiple qualified private parking spaces, through

[0067]

[0068] When the obtained value is relatively large and the user's basic information is available, private parking spaces can be recommended to the user. More than three private parking spaces can be recommended to the user at the same time, and the more than three parking spaces are sorted in sequence. While assisting the user in making a choice, it also enables the user to select the most suitable private parking space according to their own situation.

[0069] Furthermore, when the user temporarily parks the vehicle in the park, in most cases, it will exceed 15 minutes, which is a time period composed of multiple time points. If only relying on the value of a single time point in the time period, it is difficult to accurately recommend private parking spaces to the user. Mark the number of times that no private vehicle has parked in a private parking space in half a year as N1, N2, Nx... N96, and the number of times corresponding to the time points that do not meet the parking requirements is not considered. Obtain the parking duration of the user as m; through the formula

[0070] ,

[0071] where Qy represents the coefficient that the owner of the private parking space will not use the private parking space during the parking duration, Ns is the number of times that no private vehicle has parked in the private parking space in half a year corresponding to the collection time point corresponding to the start time in the parking duration,

[0072]

[0073] and Nf is the number of times that no private vehicle has parked in the private parking space in half a year corresponding to the collection time point corresponding to the end time in the parking duration; through the value of Qy, it can be more intuitive and accurate to obtain whether the owner will use their private parking space during the parking duration, and it can more accurately recommend suitable private parking spaces to the user.

[0074] Embodiment 2:

[0075] There are certain differences in the vehicle usage situation of each person every day of the week. The main reason is the difference in different working hours. Most work has the main rest time concentrated on Saturday and Sunday. There is also a part of the work with only Sunday as the rest time, and there is also a part of the work with the rest time during Monday to Friday. Most car owners also have a large difference in the vehicle usage situation during working hours and non-working hours. Therefore, the situation of the car owner using their private parking space varies greatly in a week. In order to more accurately recommend private parking spaces to the user and also to avoid bringing inconvenience to the car owner, separately obtain the number of times that no private vehicle has parked in the private parking space on all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, or Sundays in half a year and mark them as T1, T2...; through the formula

[0076] ,

[0077] Among them, Z is the total number of days of all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, or Sundays in half a year, and Qc reflects the usage of private parking spaces by car owners on all Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, or Sundays in the recent half year. According to the value of Qc, the accuracy of recommending private parking spaces to users can be further improved.

[0078] Furthermore, in some extreme cases, among multiple time points corresponding to the parking duration, the number of times a private vehicle is parked is mostly concentrated at a certain time point. Even if the value of Qc or Qy is large, the probability that the car owner uses their private parking space during the parking duration is also large. Therefore, to avoid such extreme cases, extract the minimum number of times when no private vehicle is parked during the parking duration. The extracted minimum number is Na, and through the formula

[0079] ,

[0080] For private parking spaces with a P value greater than 0.1, they are not recommended as the first choice to avoid misleading users to select such parking spaces. The value of Qc and P is displayed for each recommended private parking space. Since the parking duration is the duration input by the user according to the actual situation, some users may input a relatively long parking duration, and the above extreme cases occur. The time point with the most times of parking a private vehicle is mostly distributed in the last time period of the parking duration. Since the parking space data acquisition module collects private parking space data every 15 minutes, and the situation where the vehicle stays in the parking space for at most 15 minutes after parking is extremely rare. Therefore, such extreme cases are mostly distributed in the last time period of the parking duration. Users who choose this parking space only need to drive the vehicle away from the private parking space 15 minutes in advance at most. For some users who can leave in advance, choosing such a private parking space is a relatively good choice.

[0081] Embodiment 3:

[0082] The basic information input by the user terminal includes the building to go to, mobile phone number, and name;

[0083] The data analysis module searches for private parking spaces for the user with the building to go to as the center, collects the private parking space information around the building to go to by the camera, sends the private parking space information to the data processing module, and the data analysis module searches for suitable private parking spaces;

[0084] After the owner's parking space is occupied, it is inevitable that the owner will not use their private parking space in the previous habit, and the situation where the private parking space is occupied when the owner arrives at the park will occur. To avoid causing trouble to the owner, the data processing module notifies the user occupying the parking space to move the vehicle by phone or text message, and the data analysis module recommends a private parking space for the user again. To reduce the owner's waiting time, when the owner drives to the community gate and the vehicle of the owner is recognized, the data processing module immediately calls the user occupying the parking space to quickly transfer the vehicle;

[0085] For the above situation, even if some users receive a phone call notification, they will not move the vehicle quickly, and even there will be a situation where they will not move the vehicle. To avoid such a situation, the data processing module is also connected to a credit evaluation module. The credit evaluation module rates the credit of the user. When the data analysis module notifies the user to move the vehicle, if the user moves the vehicle within the specified time for two consecutive times, it is rated as A level. If the user fails to move the vehicle within the specified time once, it is rated as B level. If the user fails to move the vehicle on time three consecutive times, it is rated as C level. The data analysis module preferentially recommends private parking spaces for A-level users. For A-level users, those with more consecutive compliance times are preferentially recommended. When there are no public parking spaces in the park for C-level users, they are not allowed to enter the park. This can not only improve the enthusiasm of users to move the vehicle, but also screen out users with lower compliance ability and retain users with strong compliance ability, so as to recommend private parking spaces only for users with strong compliance ability;

[0086] To further improve the enthusiasm of users to move the vehicle and avoid causing losses to the owner, the parking space data acquisition module is connected to a timing module. This timing module can be a timer. When the user fails to move the vehicle within the specified time, the timer starts timing. When the user's vehicle leaves the park, the data processing module charges the user's vehicle an additional fee according to the time recorded by the timing module, and transfers the additional fee charged to the user terminal of the private parking space owner. The parking space data acquisition module sends the time recorded by the timer to the data processing module. The additional fee is charged in addition to the basic fee required to enter the park. For the temporary parking space obtained by the user through leasing, the basic fee of the park parking lot is not charged, but the additional fee is still charged.

[0087] Embodiment 4:

[0088] A positioning module is connected in the client module. Through this positioning module, the vehicle usage information of the private parking space owner outside the park is obtained. The positioning navigation satellite is used to locate the client of the owner, and the vehicle usage information of the owner is obtained. The client sends the vehicle usage information to the data processing module. The data processing module records the route of the private owner returning to the park in the past six months. Among the time points when the private parking space can be recommended to the user, when the owner of the private parking space moves the vehicle, the data analysis module determines whether the owner is returning to the park according to whether the route information of the owner returning to the park is getting closer to the park. When the owner returns to the park through the common route, the data processing module notifies the user to transfer the parking space by text message or phone call. When the owner is not driving on the common route but is getting closer to the park, and when the owner drives to a distance of five kilometers from the community, the data processing module notifies the user to transfer the parking space by text message or phone call, further ensuring that when the owner arrives at his private parking space, there is no vehicle affecting his experience of using the private parking space.

[0089] As described above, it is only the preferred embodiment of the present invention and does not impose any form of limitation on the present invention. Any ordinary technician in the industry can smoothly implement the present invention as shown in the accompanying drawings of the specification and as described above. However, any equivalent changes made by those skilled in the art within the scope of the technical solution of the present invention by using the technical content disclosed above, such as slight modifications, decorations, and evolutions, are equivalent embodiments of the present invention. At the same time, any equivalent changes, modifications, and evolutions made to the above embodiments based on the essential technology of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A big data smart park management system, characterized by: It includes a data processing module, a parking space data collection module, a data analysis module and a user terminal module, wherein; The parking space data collection module is used to collect the usage data of each private parking space, monitor the usage data of private parking spaces in the past six months, one day is a monitoring cycle, and collects whether there is a private vehicle in the private parking space every fifteen minutes; The data processing module is connected to the parking space data collection module and is used to receive and process the usage data of each private parking space, wherein the data processing module is provided with a data storage unit, and the data storage unit is used to store the data processed by the data processing module; The user terminal module is connected to the data storage unit to obtain basic information of the user and the required docking time, and sends the obtained basic information and docking time to the data storage unit; The data analysis module is connected to the data processing module, analyzes the data in the data storage unit, obtains data analysis information, and sends the data analysis information to the user end module; the specific analysis steps are: Step 1: Obtain the usage data of each private parking space within six months and the user's parking time; Step 2: According to the formula Get the time point when each private parking space can be parked; where the minimum k is the parking coefficient, Nx is the number of times there is no parking at a certain time point within half a year, and 180 is the total number of times the parking space data collection module collects private parking space usage data in half a year. When the obtained value is greater than K, the time point meets the docking requirements, and the user can dock during the period from the previous time point to the current time point. When the obtained value is less than K, the time point does not meet the docking requirements, and the user cannot dock during the period from the previous time point to the current time point. Step 3: Obtain a private parking space that meets the parking time period; Step 4: After obtaining multiple eligible private parking spaces, The larger the value obtained and the basic information of the user, the private parking space is recommended to the user; The number of times that no private vehicles were parked in the private parking spaces in half a year is marked as N1, N2, Nx...N96, Get the user's parking time as m; through the formula , Among them, Qy represents the coefficient that the owner of a private parking space will not use the private parking space during the parking time, Ns is the number of times that no private vehicles are parked in the private parking space in the six months corresponding to the collection time point corresponding to the start time of the parking time, The number of times that no private vehicles were parked in the private parking spaces in the six months corresponding to the collection time point corresponding to the end time of the parking duration; Get only the number of private parking spaces without private vehicles parked on Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays or Sundays in half a year, marked as T1, T2...; through the formula , Where Z is the total number of Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, or Sundays in half a year.

2. A big data smart park management system according to claim 1, characterized in that: Extract the minimum number of times that no private vehicle stops during the stay time. The minimum number of times extracted is Na, and the formula is used , The private parking spaces with a P value greater than 0.1 are not recommended as the first ones, and the Qc and P values ​​are displayed together for each recommended private parking space.

3. A big data smart park management system according to claim 1, characterized in that: The basic information input by the user terminal includes the building to be visited, mobile phone number and name; The data analysis module searches for a private parking space for the user with the building being visited as the center of the circle; When the owner of a private parking space arrives at the park, the data processing module notifies the user occupying the parking space to move the car by phone or text message, and the data analysis module recommends a private parking space to the user again.

4. A big data smart park management system according to claim 3, characterized in that: The data processing module is also connected to a reputation evaluation module, which rates the user's reputation. When the data analysis module notifies the user to move the car, if the user moves the car within the specified time twice in a row, the user is classified as Class A, if the user fails to move the car within the specified time once, the user is classified as Class B, and if the user fails to move the car on time three times in a row, the user is classified as Class C. The data analysis module gives priority to recommending private parking spaces to Class A users, and for Class A users, it gives priority to recommending users with more consecutive compliance times. Class C users are not allowed to enter the park when there are no public parking spaces in the park.

5. A big data smart park management system according to claim 4, characterized in that: The parking space data collection module is connected to a timing module. When the user fails to move the vehicle within the specified time, the timing module starts timing. When the user's vehicle leaves the park, the data processing module charges the user's vehicle an additional fee based on the time recorded by the timing module, and the additional fee is deposited into the user terminal of the private parking space owner.

6. A big data smart park management system according to any one of claims 1 to 5, characterized in that: The user-end module is connected to a positioning module, which is used to obtain the car usage information of the private parking space owner outside the park, and the data processing module is used to record the route of the private parking space owner returning to the park in the past six months. When the private parking space owner moves the vehicle at a time point when the private parking space can be recommended to the user, the data analysis module determines whether the owner is returning to the park based on the route information of the owner's return to the park and whether the distance to the park is getting closer.

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