Personnel dispatching method based on smart parking lot

Abstract

The present invention relates to the field of personnel scheduling technology, and specifically to a personnel scheduling method based on a smart parking lot. The present invention obtains a dynamic model of the parking lot by analyzing the comprehensive data of the parking lot, and obtains future traffic flow prediction information of the parking lot by analyzing the dynamic model of the parking lot and the historical data of the parking lot, and performs corresponding personnel scheduling according to the future traffic flow prediction information, thereby increasing the personnel scheduling efficiency of the parking lot and ensuring excellent service of the parking lot; and obtains personnel scheduling instructions by performing a comprehensive analysis of regional parking lot data and personnel demand prediction information of each parking lot, and monitors the personnel scheduling of each parking lot to perform data deviation analysis, and makes real-time adjustments according to the data deviation, so as to deploy personnel in multiple parking lots in the region, ensure that personnel in each parking lot are evenly distributed, and ensure efficient personnel work scheduling.

Description

Technical Field

[0001] The present invention relates to the technical field of personnel dispatching, and in particular to a personnel dispatching method based on a smart parking lot. Background Art

[0002] With the acceleration of urbanization and the continuous growth of car ownership, the smart parking industry has gradually emerged; smart parking uses technologies such as the Internet of Things and artificial intelligence to realize the intelligent management and operation of parking lots. At present, smart parking has covered parking guidance, parking lot management, reverse car search and other aspects, providing car owners with a more convenient parking experience. The existing smart parking lot staff scheduling method only schedules staff for a single parking lot. When scheduling multiple parking lots in the area, it is impossible to efficiently and accurately schedule staff work, resulting in problems such as uneven staff distribution and slow response speed in the parking lot. Summary of the invention

[0003] The present invention provides a personnel dispatching method based on a smart parking lot to solve the above-mentioned technical problems.

[0004] The first aspect of the present invention provides a personnel dispatching method based on a smart parking lot, comprising the following steps:

[0005] Step 1, data acquisition unit: obtain comprehensive parking data of each parking lot through cameras and sensors and upload the comprehensive parking data to the database; the comprehensive parking data includes parking lot image information, parking lot vehicle information and parking lot map information.

[0006] Step 2: Parking lot data analysis: Obtain comprehensive parking lot data and analyze the comprehensive parking lot data to obtain a dynamic model of each parking lot, and conduct a comprehensive analysis of the dynamic model of the parking lot and the historical data of the corresponding parking lot to obtain future traffic flow prediction information.

[0007] As a preferred embodiment of the present invention, the comprehensive parking lot data is analyzed, and the specific analysis method is as follows:

[0008] The corresponding parking lot image information, parking lot vehicle information and parking lot map information are obtained based on the comprehensive data of each parking lot. The parking lot map information is identified to obtain the parking space layout, number of parking spaces and lane settings of the parking lot. A parking lot layout model is generated based on the parking space layout, number of parking spaces and lane settings of the parking lot. The usage signals of each parking space in the layout model are analyzed. The license plate information of the parked vehicles in the parking lot is obtained based on the parking lot image information. The license plate information of the parked vehicles is matched with the layout model of the parking lot to obtain the parking position of the parked vehicles. The parking space at the parking position is marked as an occupied parking space. The occupied parking space is used as the usage signal of the corresponding parking space, and the occupied parking space is matched with the parking lot vehicle information to obtain the parking information of the occupied parking space. A dynamic model of the parking lot is generated based on the parking space usage signals and parking information of each parking space in the parking lot.

[0009] The parking lot vehicle information includes the license plate information, entry time, parking space information and vehicle image of the parked vehicles; the parking quality of the vehicles parked in the parking lot is analyzed: the vehicle image is identified to obtain the body dimensions of the parked vehicle in all directions, and a three-dimensional image of the parked vehicle is obtained based on the body dimensions of the parked vehicle in all directions. The three-dimensional image of the parked vehicle is overlapped and compared with the corresponding parking space to obtain the parking deviation of the corresponding three-dimensional model of the parked vehicle, and the parking deviation of the three-dimensional model is identified to obtain the entry depth value, body inclination and entry deviation size.

[0010] Obtain a preset standard value of the parking depth for parked vehicles, calculate the parking depth value of the current parked vehicle and the parking depth standard value to obtain the parking depth difference of the current parked vehicle, compare the parking depth difference with the set parking difference threshold, and when the parking depth difference is greater than the set parking difference threshold, mark the value obtained by subtracting the parking difference threshold from the parking depth difference as the parking depth impact index; compare the vehicle body inclination with the set inclination threshold, mark the vehicle body inclination that exceeds the inclination threshold as abnormal inclination, divide the abnormal inclination into multiple abnormal inclination intervals, each abnormal inclination interval corresponds to an abnormal inclination impact value, match the abnormal inclination of the current parked vehicle with the multiple abnormal inclination intervals, and obtain the abnormal inclination impact value of each current parked vehicle; as above, obtain the abnormal deviation size impact value corresponding to the parking deviation size corresponding to each parked vehicle.

[0011] A right triangle is constructed with the values ​​of the abnormal inclination impact value and the abnormal deviation size impact value as the two right-angled sides of the right triangle. A straight line perpendicular to the right triangle is drawn with the intersection of the two right-angled sides as the starting point. The length of the straight line is equal to the value of the storage depth impact index. A triangular pyramid is then constructed with the right triangle and the straight line. The volume of the triangular pyramid is calculated and the value of the volume is marked as the parking impact value. The parking impact value is compared with the set threshold. When the parking impact value is greater than the threshold, the parked vehicle corresponding to the parking space is marked as an abnormally parked vehicle, and a corresponding abnormal response dispatch instruction is generated for the abnormally parked vehicle.

[0012] As a preferred implementation of the present invention, a comprehensive analysis is performed on the dynamic model of the parking lot and the historical data of the corresponding parking lot. The specific analysis method is as follows:

[0013] Take one day as the unit monitoring time, set one week as the small cycle according to the date setting, and set one month as the large cycle; identify the dynamic model of the parking lot within the unit monitoring time to obtain the total number of parked vehicles in the parking lot, obtain the total number of parked vehicles in the parking lot within the unit monitoring time, identify the historical data of the parking lot to obtain multiple historical small cycles corresponding to the historical large cycle, and obtain the total number of historical parked vehicles at each unit monitoring time within the historical small cycle through identification. Based on the total number of historical parked vehicles at each unit monitoring time within the historical small cycle, obtain the fluctuation curve of the total number of parked vehicles within the historical small cycle, and obtain the fluctuation curve of the parked vehicles corresponding to the historical large cycle according to the fluctuation curve of the total number of parked vehicles in each historical small cycle.

[0014] Match the current large cycle with the corresponding historical large cycle to obtain the historical small cycle corresponding to the current parking lot small cycle, identify the fluctuation curve of the total number of parked vehicles in the historical small cycle to obtain the curve trend, and obtain the traffic flow change information corresponding to the historical small cycle according to the curve trend. When the curve trend corresponding to the fluctuation curve of the total number of parked vehicles continues to rise, the traffic flow growth is used as the corresponding traffic flow change information, and the real-time fluctuation curve of the total number of parked vehicles in the current small cycle is overlapped and compared with the historical fluctuation curve of the total number of parked vehicles corresponding to the historical small cycle to obtain the curve difference of multiple unit detection time, calculate and sum the curve differences to obtain the total curve difference corresponding to the real-time fluctuation curve of the total number of parked vehicles in the current small cycle, obtain the set difference interval, compare the total curve difference corresponding to the current small cycle with the difference interval, and when the total curve difference exceeds the curve difference, the corresponding future traffic flow prediction information is generated as an increase in traffic flow, otherwise, the corresponding future traffic flow prediction information is generated as a decrease in traffic flow information.

[0015] Step 3: Personnel demand prediction: Obtain future traffic flow prediction information and analyze the future traffic flow prediction information to obtain the personnel demand prediction information corresponding to each parking lot.

[0016] As a preferred implementation of the present invention, the future traffic flow prediction information is analyzed, and the specific analysis method is as follows:

[0017] The total number of parked vehicles in each parking lot is obtained and the total number of parked vehicles is identified to obtain the traffic flow information of each parking lot within the unit monitoring time. The traffic flow index of each parking lot is calculated by the traffic flow information and the unit detection time. The traffic flow index is divided into multiple traffic flow index intervals. Each traffic flow index interval corresponds to a personnel demand index. The traffic flow index corresponding to the current parking lot is matched with multiple traffic flow index intervals to obtain the personnel demand index corresponding to the current parking lot. Future prediction information is obtained and the future traffic flow prediction information is identified. When the future traffic flow prediction information is an increase in traffic flow, the predicted increase in traffic flow corresponding to the increase in traffic flow is counted, the current traffic flow index is added to the predicted increase in traffic flow to calculate the predicted traffic flow index, the predicted traffic flow index is matched with multiple traffic flow index intervals to obtain the personnel demand index corresponding to the predicted traffic flow, the personnel demand index corresponding to the predicted traffic flow is subtracted from the personnel demand index corresponding to the current parking lot to obtain the personnel demand index change value. Otherwise, a predicted reduction in traffic flow is obtained, and the corresponding personnel demand index change value is obtained based on the predicted reduction in traffic flow. The personnel demand prediction information is obtained based on the personnel demand index change value.

[0018] Step 4: Regional personnel coordination: Obtain regional parking lot data within the area and conduct a comprehensive analysis of the regional parking lot data and the personnel demand forecast information of each parking lot to obtain personnel dispatch instructions.

[0019] As a preferred embodiment of the present invention, a comprehensive analysis is performed on the regional parking lot data and the personnel demand forecast information of each parking lot. The specific analysis method is as follows:

[0020] The regional parking lot data is identified to obtain the parking lot address and regional personnel information within the set area, the personnel demand forecast information of each parking lot is obtained and the personnel demand forecast information is identified to obtain the number change information of each parking lot, the number of parking lots with increased personnel demand is counted, and the total increase in personnel demand corresponding to the number of parking lots with increased personnel demand is identified. Similarly, the total decrease in personnel demand corresponding to the number of parking lots with reduced personnel demand is obtained, the total decrease in personnel demand is added to the total number of remaining resting personnel to obtain the total number of personnel to be deployed, the total increase in personnel demand is compared with the total number of personnel to be deployed, and when the total increase in personnel demand is greater than the total number of personnel to be deployed, a personnel supply shortage instruction is generated, based on the personnel supply shortage instruction, the corresponding number of personnel demand of each parking lot with increased personnel demand is compared, and the proportion of personnel demand of each parking lot with increased personnel demand is obtained, and the proportion of personnel demand and the total number of personnel to be deployed are calculated to obtain the personnel scheduling information of each parking lot with increased personnel demand.

[0021] Identify the regional personnel information of each person to be deployed, obtain the address information of each person, match the address information of each person to be deployed with the address information of each parking lot, obtain the preferred personnel corresponding to each parking lot, obtain the preferred personnel corresponding to each parking lot based on the personnel deployment information of each parking lot, and generate the dispatch instructions for the corresponding personnel based on the pre-selected personnel.

[0022] Step 5: Personnel dispatch execution: Obtain personnel dispatch instructions and perform corresponding personnel dispatch according to the personnel dispatch instructions.

[0023] Step 6: Real-time monitoring and adjustment: Monitor the personnel dispatch of each parking lot to obtain the current parking lot monitoring information, match the current parking lot monitoring information with the future traffic flow prediction information to obtain the data deviation, and make real-time adjustments based on the data deviation.

[0024] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0025] 1. The present invention obtains a dynamic model of the parking lot by analyzing the comprehensive data of the parking lot, and obtains future traffic flow prediction information of the parking lot by analyzing the dynamic model of the parking lot and the historical data of the parking lot, and makes corresponding personnel dispatch according to the future traffic flow prediction information, thereby increasing the personnel dispatch efficiency of the parking lot and ensuring excellent service of the parking lot.

[0026] 2. The present invention obtains personnel dispatch instructions by comprehensively analyzing the regional parking lot data and the personnel demand forecast information of each parking lot, monitors the current personnel dispatch of each parking lot to perform data deviation analysis, and makes real-time adjustments based on the data deviation to deploy personnel in multiple parking lots in the region, ensuring uniform distribution of personnel in each parking lot and efficient personnel work dispatch. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0028] Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 In an embodiment of the present invention, an embodiment of a personnel dispatching method based on a smart parking lot includes the following steps:

[0031] Step 1, data acquisition unit: obtain comprehensive parking data of each parking lot through cameras and sensors and upload the comprehensive parking data to the database; the comprehensive parking data includes parking lot image information, parking lot vehicle information and parking lot map information.

[0032] Step 2: Parking lot data analysis: Obtain comprehensive parking lot data and analyze the comprehensive parking lot data to obtain a dynamic model of each parking lot, and conduct a comprehensive analysis of the dynamic model of the parking lot and the historical data of the corresponding parking lot to obtain future traffic flow prediction information.

[0033] The comprehensive data of parking lots is analyzed in the following specific ways:

[0034] The corresponding parking lot image information, parking lot vehicle information and parking lot map information are obtained based on the comprehensive data of each parking lot. The parking lot map information is identified to obtain the parking space layout, number of parking spaces and lane settings of the parking lot. A parking lot layout model is generated based on the parking space layout, number of parking spaces and lane settings of the parking lot. The usage signals of each parking space in the layout model are analyzed. The license plate information of the parked vehicles in the parking lot is obtained based on the parking lot image information. The license plate information of the parked vehicles is matched with the layout model of the parking lot to obtain the parking position of the parked vehicles. The parking space at the parking position is marked as an occupied parking space. The occupied parking space is used as the usage signal of the corresponding parking space, and the occupied parking space is matched with the parking lot vehicle information to obtain the parking information of the occupied parking space. A dynamic model of the parking lot is generated based on the parking space usage signals and parking information of each parking space in the parking lot.

[0035] The parking lot vehicle information includes the license plate information, entry time, parking space information and vehicle image of the parked vehicles; the parking quality of the vehicles parked in the parking lot is analyzed: the vehicle image is identified to obtain the body dimensions of the parked vehicle in all directions, and a three-dimensional image of the parked vehicle is obtained based on the body dimensions of the parked vehicle in all directions. The three-dimensional image of the parked vehicle is overlapped and compared with the corresponding parking space to obtain the parking deviation of the corresponding three-dimensional model of the parked vehicle, and the parking deviation of the three-dimensional model is identified to obtain the entry depth value, body inclination and entry deviation size.

[0036] Obtain a preset standard value of the parking depth for parked vehicles, calculate the parking depth value of the current parked vehicle and the parking depth standard value to obtain the parking depth difference of the current parked vehicle, compare the parking depth difference with the set parking difference threshold, and when the parking depth difference is greater than the set parking difference threshold, mark the value obtained by subtracting the parking difference threshold from the parking depth difference as the parking depth impact index; compare the vehicle body inclination with the set inclination threshold, mark the vehicle body inclination that exceeds the inclination threshold as abnormal inclination, divide the abnormal inclination into multiple abnormal inclination intervals, each abnormal inclination interval corresponds to an abnormal inclination impact value, match the abnormal inclination of the current parked vehicle with the multiple abnormal inclination intervals, and obtain the abnormal inclination impact value of each current parked vehicle; as above, obtain the abnormal deviation size impact value corresponding to the parking deviation size corresponding to each parked vehicle.

[0037] A right triangle is constructed with the values ​​of the abnormal inclination impact value and the abnormal deviation size impact value as the two right-angled sides of the right triangle. A straight line perpendicular to the right triangle is drawn with the intersection of the two right-angled sides as the starting point. The length of the straight line is equal to the value of the storage depth impact index. A triangular pyramid is then constructed with the right triangle and the straight line. The volume of the triangular pyramid is calculated and the value of the volume is marked as the parking impact value. The parking impact value is compared with the set threshold. When the parking impact value is greater than the threshold, the parked vehicle corresponding to the parking space is marked as an abnormally parked vehicle, and a corresponding abnormal response dispatch instruction is generated for the abnormally parked vehicle.

[0038] A comprehensive analysis is conducted on the dynamic model of the parking lot and the historical data of the corresponding parking lot. The specific analysis method is as follows:

[0039] Take one day as the unit monitoring time, set one week as the small cycle according to the date setting, and set one month as the large cycle; identify the dynamic model of the parking lot within the unit monitoring time to obtain the total number of parked vehicles in the parking lot, obtain the total number of parked vehicles in the parking lot within the unit monitoring time, identify the historical data of the parking lot to obtain multiple historical small cycles corresponding to the historical large cycle, and obtain the total number of historical parked vehicles at each unit monitoring time within the historical small cycle through identification. Based on the total number of historical parked vehicles at each unit monitoring time within the historical small cycle, obtain the fluctuation curve of the total number of parked vehicles within the historical small cycle, and obtain the fluctuation curve of the parked vehicles corresponding to the historical large cycle according to the fluctuation curve of the total number of parked vehicles in each historical small cycle.

[0040] Match the current large cycle with the corresponding historical large cycle to obtain the historical small cycle corresponding to the current parking lot small cycle, identify the fluctuation curve of the total number of parked vehicles in the historical small cycle to obtain the curve trend, and obtain the traffic flow change information corresponding to the historical small cycle according to the curve trend. When the curve trend corresponding to the fluctuation curve of the total number of parked vehicles continues to rise, the traffic flow growth is used as the corresponding traffic flow change information, and the real-time fluctuation curve of the total number of parked vehicles in the current small cycle is overlapped and compared with the historical fluctuation curve of the total number of parked vehicles corresponding to the historical small cycle to obtain the curve difference of multiple unit detection time, calculate and sum the curve differences to obtain the total curve difference corresponding to the real-time fluctuation curve of the total number of parked vehicles in the current small cycle, obtain the set difference interval, compare the total curve difference corresponding to the current small cycle with the difference interval, and when the total curve difference exceeds the curve difference, the corresponding future traffic flow prediction information is generated as an increase in traffic flow, otherwise, the corresponding future traffic flow prediction information is generated as a decrease in traffic flow information.

[0041] Step 3: Personnel demand prediction: Obtain future traffic flow prediction information and analyze the future traffic flow prediction information to obtain the personnel demand prediction information corresponding to each parking lot.

[0042] The future traffic flow prediction information is analyzed, and the specific analysis method is as follows:

[0043] The total number of parked vehicles in each parking lot is obtained and the total number of parked vehicles is identified to obtain the traffic flow information of each parking lot within the unit monitoring time. The traffic flow index of each parking lot is calculated by the traffic flow information and the unit detection time. The traffic flow index is divided into multiple traffic flow index intervals. Each traffic flow index interval corresponds to a personnel demand index. The traffic flow index corresponding to the current parking lot is matched with multiple traffic flow index intervals to obtain the personnel demand index corresponding to the current parking lot. Future prediction information is obtained and the future traffic flow prediction information is identified. When the future traffic flow prediction information is an increase in traffic flow, the predicted increase in traffic flow corresponding to the increase in traffic flow is counted, the current traffic flow index is added to the predicted increase in traffic flow to calculate the predicted traffic flow index, the predicted traffic flow index is matched with multiple traffic flow index intervals to obtain the personnel demand index corresponding to the predicted traffic flow, the personnel demand index corresponding to the predicted traffic flow is subtracted from the personnel demand index corresponding to the current parking lot to obtain the personnel demand index change value. Otherwise, a predicted reduction in traffic flow is obtained, and the corresponding personnel demand index change value is obtained based on the predicted reduction in traffic flow. The personnel demand prediction information is obtained based on the personnel demand index change value.

[0044] Step 4: Regional personnel coordination: Obtain regional parking lot data within the area and conduct a comprehensive analysis of the regional parking lot data and the personnel demand forecast information of each parking lot to obtain personnel dispatch instructions.

[0045] Comprehensive analysis of regional parking lot data and personnel demand forecast information of each parking lot is carried out. The specific analysis method is as follows:

[0046] The regional parking lot data is identified to obtain the parking lot address and regional personnel information within the set area, the personnel demand forecast information of each parking lot is obtained and the personnel demand forecast information is identified to obtain the number change information of each parking lot, the number of parking lots with increased personnel demand is counted, and the total increase in personnel demand corresponding to the number of parking lots with increased personnel demand is identified. Similarly, the total decrease in personnel demand corresponding to the number of parking lots with reduced personnel demand is obtained, the total decrease in personnel demand is added to the total number of remaining resting personnel to obtain the total number of personnel to be deployed, the total increase in personnel demand is compared with the total number of personnel to be deployed, and when the total increase in personnel demand is greater than the total number of personnel to be deployed, a personnel supply shortage instruction is generated, based on the personnel supply shortage instruction, the corresponding number of personnel demand of each parking lot with increased personnel demand is compared, and the proportion of personnel demand of each parking lot with increased personnel demand is obtained, and the proportion of personnel demand and the total number of personnel to be deployed are calculated to obtain the personnel scheduling information of each parking lot with increased personnel demand.

[0047] Identify the regional personnel information of each person to be deployed, obtain the address information of each person, match the address information of each person to be deployed with the address information of each parking lot, obtain the preferred personnel corresponding to each parking lot, obtain the preferred personnel corresponding to each parking lot based on the personnel deployment information of each parking lot, and generate the dispatch instructions for the corresponding personnel based on the pre-selected personnel.

[0048] Step 5: Personnel dispatch execution: Obtain personnel dispatch instructions and perform corresponding personnel dispatch according to the personnel dispatch instructions.

[0049] Step 6: Real-time monitoring and adjustment: Monitor the personnel dispatch of each parking lot to obtain the current parking lot monitoring information, match the current parking lot monitoring information with the future traffic flow prediction information to obtain the data deviation, and make real-time adjustments based on the data deviation.

[0050] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A personnel dispatching method based on a smart parking lot is characterized by: The steps include: Step 1: Collect comprehensive parking lot data of each parking lot through cameras and sensors and upload the comprehensive parking lot data to a database; Step 2: Obtain comprehensive parking lot data and analyze the comprehensive parking lot data to obtain a dynamic model of each parking lot, and conduct a comprehensive analysis of the dynamic model of the parking lot and the historical data of the corresponding parking lot to obtain future traffic flow prediction information; The comprehensive data of the parking lot is analyzed, and the specific analysis method is as follows: Obtain corresponding parking lot image information, parking lot vehicle information and parking lot map information based on comprehensive data of each parking lot, identify the parking lot map information to obtain the parking space layout, number of parking spaces and lane settings of the parking lot, generate a parking lot layout model based on the parking space layout, number of parking spaces and lane settings of the parking lot, analyze usage signals of each parking space in the layout model, obtain license plate information of parked vehicles in the parking lot based on the parking lot image information, match the license plate information of the parked vehicles with the layout model of the parking lot to obtain the parking position of the parked vehicles, mark the parking space at the parking position as an occupied parking space, use the occupied parking space as the usage signal of the corresponding parking space, match the occupied parking space with the parking lot vehicle information to obtain the parking information of the occupied parking space, and generate a dynamic model of the parking lot based on the parking space usage signals and parking information of each parking space in the parking lot; The parking lot vehicle information includes the license plate information, entry time, parking space information and vehicle image of the parked vehicle; the parking quality of the parked vehicles in the parking lot is analyzed: the vehicle image is identified to obtain the body size of the parked vehicle in all directions, and a three-dimensional image of the parked vehicle is obtained based on the body size of the parked vehicle in all directions. The three-dimensional image of the parked vehicle is overlapped and compared with the corresponding parking space to obtain the parking deviation of the corresponding three-dimensional model of the parked vehicle, and the parking deviation of the three-dimensional model is identified to obtain the entry depth value, body inclination and entry deviation size; Obtain a preset standard value of the parking depth for the parked vehicle, calculate the parking depth value of the current parked vehicle and the parking depth standard value to obtain the parking depth difference of the current parked vehicle, compare the parking depth difference with the set parking difference threshold, and when the parking depth difference is greater than the set parking difference threshold, mark the value obtained by subtracting the parking difference threshold from the parking depth difference as the parking depth impact index; compare the vehicle body inclination with the set inclination threshold, mark the vehicle body inclination exceeding the inclination threshold as abnormal inclination, divide the abnormal inclination into multiple abnormal inclination intervals, each abnormal inclination interval corresponds to an abnormal inclination impact value, match the abnormal inclination of the current parked vehicle with the multiple abnormal inclination intervals, and obtain the abnormal inclination impact value of each current parked vehicle; As above, the abnormal deviation dimension impact value corresponding to the parking deviation dimension of each parked vehicle is obtained; A right triangle is constructed with the values ​​of the abnormal inclination impact value and the abnormal deviation size impact value as the two right-angled sides of the right triangle. A straight line perpendicular to the right triangle is drawn with the intersection of the two right-angled sides as the starting point. The length of the straight line is equal to the value of the storage depth impact index. A triangular pyramid is then constructed with the right triangle and the straight line. The volume of the triangular pyramid is calculated and the value of the volume is marked as the parking impact value. The parking impact value is compared with the set threshold. When the parking impact value is greater than the threshold, the parked vehicle corresponding to the parking space is marked as an abnormally parked vehicle, and a corresponding abnormal response dispatch instruction is generated for the abnormally parked vehicle. A comprehensive analysis is performed on the dynamic model of the parking lot and the historical data of the corresponding parking lot. The specific analysis method is as follows: Take one day as the unit monitoring time, set one week as the small cycle according to the date setting, and set one month as the large cycle; identify the dynamic model of the parking lot within the unit monitoring time, obtain the total number of parked vehicles in the parking lot, obtain the total number of parked vehicles in the parking lot within the unit monitoring time, identify the historical data of the parking lot to obtain multiple historical small cycles corresponding to the historical large cycle, obtain the total number of historical parked vehicles of each unit monitoring time within the historical small cycle through identification, obtain the total number of historical parked vehicles of each unit monitoring time within the historical small cycle based on the total number of historical parked vehicles of each unit monitoring time within the historical small cycle, and obtain the fluctuation curve of the total number of parked vehicles within the historical small cycle according to the fluctuation curve of the total number of parked vehicles in each historical small cycle, and obtain the fluctuation curve of the parked vehicles corresponding to the historical large cycle according to the fluctuation curve of the total number of parked vehicles in each historical small cycle; Match the current large cycle with the corresponding historical large cycle to obtain the historical small cycle corresponding to the current parking lot small cycle, identify the fluctuation curve of the total number of parked vehicles in the historical small cycle to obtain the curve trend, and obtain the traffic flow change information corresponding to the historical small cycle according to the curve trend. When the curve trend corresponding to the fluctuation curve of the total number of parked vehicles continues to rise, the traffic flow growth is used as the corresponding traffic flow change information, and the real-time fluctuation curve of the total number of parked vehicles in the current small cycle is overlapped and compared with the historical fluctuation curve of the total number of parked vehicles corresponding to the historical small cycle to obtain the curve difference of multiple unit detection time, calculate and sum the curve differences to obtain the total curve difference corresponding to the real-time fluctuation curve of the total number of parked vehicles in the current small cycle, and compare the total curve difference corresponding to the current small cycle with the set difference interval. When the total curve difference exceeds the curve difference, the corresponding future traffic flow prediction information is generated as traffic increase, otherwise, the corresponding future traffic flow prediction information is generated as traffic decrease information; Step 3: Obtain future traffic flow forecast information and analyze the future traffic flow forecast information to obtain personnel demand forecast information corresponding to each parking lot; Step 4: Obtain regional parking lot data in the area and conduct a comprehensive analysis of the regional parking lot data and the personnel demand forecast information of each parking lot to obtain personnel dispatch instructions; Step 5: Obtain personnel dispatch instructions and perform corresponding personnel dispatch according to the personnel dispatch instructions; Step 6: Monitor the personnel dispatch of each parking lot to obtain the current parking lot monitoring information, match the current parking lot monitoring information with the future traffic flow prediction information to obtain the data deviation, and make real-time adjustments based on the data deviation.

2. The personnel dispatching method based on smart parking lot according to claim 1 is characterized in that: The future traffic flow prediction information is analyzed, and the specific analysis method is as follows: The total number of parked vehicles in each parking lot is obtained and the total number of parked vehicles is identified to obtain the traffic flow information of each parking lot within the unit monitoring time. The traffic flow index of each parking lot is calculated by the traffic flow information and the unit detection time. The traffic flow index is divided into multiple traffic flow index intervals. Each traffic flow index interval corresponds to a personnel demand index. The traffic flow index corresponding to the current parking lot is matched with multiple traffic flow index intervals to obtain the personnel demand index corresponding to the current parking lot. Future prediction information is obtained and the future traffic flow prediction information is identified. When the future traffic flow prediction information is an increase in traffic flow, the predicted increase in traffic flow corresponding to the increase in traffic flow is counted, the current traffic flow index is added to the predicted increase in traffic flow to calculate the predicted traffic flow index, the predicted traffic flow index is matched with multiple traffic flow index intervals to obtain the personnel demand index corresponding to the predicted traffic flow, the personnel demand index corresponding to the predicted traffic flow is subtracted from the personnel demand index corresponding to the current parking lot to obtain the personnel demand index change value. Otherwise, a predicted reduction in traffic flow is obtained, and the corresponding personnel demand index change value is obtained based on the predicted reduction in traffic flow. The personnel demand prediction information is obtained based on the personnel demand index change value.

3. The personnel dispatching method based on smart parking lot according to claim 1 is characterized in that: A comprehensive analysis is performed on the parking lot data of the area and the personnel demand forecast information of each parking lot. The specific analysis method is as follows: Identify the regional parking lot data to obtain the parking lot address and regional personnel information within the set area, obtain the personnel demand forecast information of each parking lot and identify the personnel demand forecast information to obtain the number of people change information of each parking lot, count the number of parking lots with increased personnel demand, and identify the total increase in personnel demand corresponding to the number of parking lots with increased personnel demand. Similarly, obtain the total decrease in personnel demand corresponding to the number of parking lots with reduced personnel demand, add the total decrease in personnel demand to the total number of remaining resting personnel to obtain the total number of personnel to be deployed, compare the total increase in personnel demand with the total number of personnel to be deployed, and generate a personnel supply shortage instruction when the total increase in personnel demand is greater than the total number of personnel to be deployed, based on the personnel supply shortage instruction, compare the corresponding number of personnel demand of each parking lot with increased personnel demand, obtain the proportion of personnel demand of each parking lot with increased personnel demand, calculate the proportion of personnel demand and the total number of personnel to be deployed to obtain the personnel dispatch information of each parking lot with increased personnel demand; Identify the regional personnel information of each person to be deployed, obtain the address information of each person, match the address information of each person to be deployed with the address information of each parking lot, obtain the preferred personnel corresponding to each parking lot, obtain the preferred personnel corresponding to each parking lot based on the personnel deployment information of each parking lot, and generate the dispatch instructions for the corresponding personnel based on the pre-selected personnel.

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