CN113516851A - Parking stall monitored control system based on big data - Google Patents
Parking stall monitored control system based on big data Download PDFInfo
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- CN113516851A CN113516851A CN202110326073.XA CN202110326073A CN113516851A CN 113516851 A CN113516851 A CN 113516851A CN 202110326073 A CN202110326073 A CN 202110326073A CN 113516851 A CN113516851 A CN 113516851A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/73—Querying
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
Abstract
The invention discloses a parking space monitoring system based on big data, which comprises a data acquisition module, a data processing module, a data analysis module, an early warning prompt module and a monitoring evidence collection module; the data acquisition module is used for acquiring a parking information set and a parking in-out information set in a parking space, wherein the parking information set comprises parking space coordinate information, parking space type information and parking space use information, the parking in-out information set comprises parking vehicle section information, parking in-out information and parking out-of-out information, and the parking information set and the parking in-out-of-out information set are sent to the data processing module together; the data processing module is used for receiving the parking information set and the parking warehousing-out information set and performing processing operation; the problem of need the manual work to look over the video recording when the parking is wiped and is bumped among the current scheme and pursue the responsibility and investigate and lead to inefficiency and can not arrange in time that personnel handle and handle the vehicle that the parking was paid the expense unusually is solved.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a parking space monitoring system based on big data.
Background
The parking space management system is a set of network system which is set up by a computer, network equipment and parking space management equipment and is used for managing vehicle access in parking spaces, traffic flow guidance in a parking lot and parking fee collection. Is a necessary tool for professional parking management companies. The early-stage system records the vehicle access information through manual charging and an induction card, and completes the functions of charging strategy realization, charging account management, parking space or parking lot equipment control and the like through management software.
However, the existing big data-based parking space monitoring system has the following defects: the problem of low efficiency caused by manual checking of video recording and tracking inspection during parking wiping and collision and the problem that personnel cannot be arranged in time to handle and the vehicle with abnormal parking payment can not be handled.
Disclosure of Invention
The invention aims to provide a parking space monitoring system, electronic equipment and a computer readable storage medium based on big data, and mainly aims to solve the problems that efficiency is low due to the fact that people need to check video recording traceability check manually when parking is bumped, and people cannot be arranged to process timely and to process vehicles with parking payment abnormity, so that unattended intelligent parking management requirements are really realized, parking management manpower management cost can be reduced, time of car owners is greatly saved, and good parking experience is provided for car owners to agent.
The purpose of the invention can be realized by the following technical method: a parking space monitoring system based on big data comprises a data acquisition module, a data processing module, a data analysis module, an early warning prompt module and a monitoring evidence collection module;
the data acquisition module is used for acquiring a parking information set and a parking in-out information set in a parking space, wherein the parking information set comprises parking space coordinate information, parking space type information and parking space use information, the parking in-out information set comprises parking vehicle section information, parking in-out information and parking out-of-out information, and the parking information set and the parking in-out-of-out information set are sent to the data processing module together;
the data processing module is used for receiving the parking information set and the parking warehousing-out information set and carrying out processing operation to obtain parking space coordinate processing information, parking vehicle type processing information, parking space use processing information, parking vehicle section processing information, parking warehousing-in processing information and parking warehousing-out processing information; and send it to the data analysis module together;
the data analysis module is used for analyzing the received data to obtain a data analysis set, the data analysis set comprises a plurality of ordered bit matching values and vehicle matching values, and the data analysis set is sent to the early warning prompt module;
the early warning prompt module is used for receiving a data analysis set and performing early warning analysis operation, and comprises the following specific steps:
the method comprises the following steps: receiving a plurality of ordered bit-match values Q in a data analysis setwpNumber of cars Qcp；
Step two: marking a preset standard position matching threshold value as Y1, marking a preset standard vehicle matching threshold value as Y2, and respectively comparing and judging the standard position matching threshold value and the standard vehicle matching threshold value with a position matching value and a vehicle matching value;
step three: if QwpIf the parking position is less than or equal to Y1, judging that the parking vehicle corresponding to the matching value is normally parked in the garage and generating a first normal signal; if Qwp>Y1, judging that the parking vehicle corresponding to the matching value enters and exits the garage and is abnormally parked, generating a first alarm signal, marking the parking vehicle corresponding to the matching value as a first abnormal vehicle, and marking the parking space corresponding to the first abnormal vehicle as a parking space to be analyzed;
if QcpIf the parking vehicle is not more than Y2, judging that the parking vehicle corresponding to the matching value is normal in ex-warehouse settlement and generating a second normal signal; if Qcp>Y2, judging that the parking vehicle corresponding to the matching value is abnormal in the warehouse-out settlement, generating a second alarm signal, and marking the parking vehicle corresponding to the matching value as a second abnormal vehicle;
step four: combining the marked first alarm signal, the marked first abnormal vehicle and the corresponding parking space to be analyzed, and the marked second alarm signal and the marked second abnormal vehicle to obtain an early warning analysis set, carrying out early warning prompt according to the early warning analysis set, and sending the early warning analysis set to a monitoring evidence collection module;
and the monitoring evidence collection module is used for analyzing and collecting evidence of vehicles with abnormal parking in the warehouse and vehicles with abnormal ex-warehouse settlement according to the early warning analysis set.
Further, the data processing module is used for receiving the parking information set and the parking warehousing information set and performing processing operation, and the specific steps comprise:
s21: receiving a parking information set and a parking warehousing-out information set, and acquiring parking space coordinate information, parking space type information and parking space use information in the parking information set;
s22: marking the coordinate of each parking space in the parking space coordinate information as TCZi, wherein i is 1,2.. n; establishing a coordinate system by taking the entrance as an original point, performing ascending arrangement according to the distance between the coordinates of the parking stalls and the original point, and combining the coordinates of the parking stalls to obtain coordinate processing information of the parking stalls;
s23: setting the unparked parking spaces with both sides unparked in the parking space type information as a first parking space weight, and marking the unparked parking spaces as YTCi, i is 1,2.. n; setting an unpark position with one side being unparked in the parking position type information as a second parking position weight, and marking the unpark position as ETCi, wherein i is 1,2.. n; setting the unworked parking spaces with both sides parked in the parking space type information as a third parking space weight, and marking the third parking space weight as STCi, wherein i is 1,2.. n; combining the marked first parking space weight, the marked second parking space weight and the marked third parking space weight to obtain parking space type processing information;
s24: marking the starting parking time in the parking space use information as KTSi, wherein i is 1,2.. n; marking the parking stopping time in the parking space use information as JTSi, wherein i is 1,2.. n; acquiring a parking time mark TSLi, wherein i is 1,2.. n; combining the marked starting parking time, ending parking time and parking duration to obtain parking space use processing information;
s25: acquiring a parking in-out information set comprising parking vehicle section information, parking in-out information and parking out-of-out information;
s26: marking a plurality of road sections in the parking vehicle road section information as TCLi, wherein i is 1,2.. n; setting different corresponding road section preset values when two sides of different road sections stop, matching a plurality of road sections in the road section information of the parking vehicle with all the road sections to obtain the corresponding road section preset values, and marking the road section preset values as LYi, wherein i is 1,2. Combining the marked road sections and corresponding road section preset values thereof to obtain parking vehicle road section processing information;
s27: marking the parking license plate in the parking and warehousing information as RCBi, wherein i is 1,2.. n; marking the historical arrearage in the parking and warehousing information as LQFi, i is 1,2.. n; marking the parking space entering time length as TRSi, wherein i is 1,2.. n; combining the marked warehousing license plate, the historical arrearages and the parking space entering duration to obtain parking warehousing processing information;
s28: marking the license plate of the fee evasion vehicle in the parking and ex-warehouse information as TCBi, wherein i is 1,2.. n; marking the vehicle fee corresponding to the license plate of the vehicle with the fee of fee evasion as TCFi, wherein i is 1,2.. n; marking the parking departure time length as TCSi, wherein i is 1,2.. n; and combining the marked license plate of the fee evasion vehicle and the corresponding fee evasion vehicle and the parking space leaving time length to obtain parking and leaving warehouse processing information.
Further, the specific steps of the data analysis module for performing analysis operation on the received data include:
s31: receiving marked first parking space weight YTCi, second parking space weight ETci, third parking space weight STCi, starting parking time KTSi, ending parking time JTSi, parking time TSLi, a plurality of road sections TCLi, road section preset values LYi, warehousing license plates RCBi, historical arrearages LQFi, toll evasion TCFi, parking space entering time TRSi and parking space leaving time TCSi;
s32: obtaining a position matching value of the parking space to be parked by using a formula, wherein the formula is as follows:
wherein Q iswpExpressed as a bit matching value, alpha is expressed as a preset bit matching correction factor, a1, a2, a3 and a4 are expressed as different proportionality coefficients, and a1+ a2+ a3-a4 is not zero;
s33: performing descending order permutation and combination on a plurality of bit matching values;
s34: the vehicle matching value of the parking space to be parked is obtained by using a formula, wherein the formula is as follows:
wherein Q iscpThe vehicle matching value is expressed, mu is a preset vehicle matching correction factor, and b1 and b2 are different proportionality coefficients;
s35: and carrying out descending order arrangement and combination on the plurality of vehicle matching values.
Further, according to the early warning analysis set, early warning prompt is carried out, and the specific steps comprise:
s41: acquiring a first abnormal vehicle and a parking space to be analyzed corresponding to a first alarm signal in an early warning analysis set, acquiring time for generating the first alarm signal and marking the time as a monitoring time point, acquiring a starting time point of video backup to be performed according to preset monitoring time at the monitoring time point, marking the time point of leaving the first abnormal vehicle as an ending time point of the video backup to be performed, storing video of the first abnormal vehicle according to the starting time point and the ending time point, generating video evidence data and storing the video evidence data into a database;
s42: the method comprises the steps of obtaining working posts, working coordinates and working states of workers in a parking space, setting different working posts to correspond to different post preset values, matching the working posts of the workers with all the working posts to obtain corresponding post preset values, and marking the corresponding post preset values as GYi, wherein i is 1,2. Obtaining a distance value between the working coordinate and the parking space to be analyzed and marking the distance value as a distance to be measured DJi, wherein i is 1,2.. n; setting different working states corresponding to different worker-shaped preset values, matching the working states of workers with all the working states to obtain corresponding worker-shaped preset values, and marking the worker-shaped preset values as GZ, wherein i is 1,2.. n;
s43: normalizing the marked post preset value, the distance to be measured and the I-shaped preset value, and taking a value, and acquiring the I-shaped value of the first abnormal vehicle by using a formula, wherein the formula is as follows:
wherein Q isgpExpressing as a work piece value, expressing delta as a preset work piece correction factor, and expressing g1, g2 and g3 as different proportionality coefficients;
s44: and setting the staff corresponding to the maximum work matching value as the selected staff, and sending the coordinates of the parking space to be analyzed to the selected staff for checking according to the reserved mobile phone number.
Further, the monitoring and evidence collection module is used for analyzing and obtaining evidence of vehicles with abnormal parking in and out of the garage and vehicles with abnormal ex and out settlement according to the early warning analysis set, and comprises the following specific steps:
s51: acquiring a license plate number and parking time corresponding to a second abnormal vehicle corresponding to a second alarm signal in the early warning analysis set, marking the license plate number and the parking time as a monitoring license plate number and a monitoring parking time respectively, and acquiring a value to be paid according to the monitoring parking time and a preset parking charging unit price;
s52: searching payment records in the data according to the monitoring license plate number, if the payment records of the monitoring license plate number do not exist, judging that the parking vehicle corresponding to the monitoring license plate number escapes, setting the monitoring license plate number as a first blacklist vehicle, associating the value to be paid with the monitoring license plate number, and prompting the payment through the monitoring license plate number when the first blacklist vehicle enters the parking space next time;
s53: if the payment record of the monitoring license plate number exists but the payment value in the payment record is smaller than the value to be paid, determining that the parking vehicle corresponding to the monitoring license plate number is owed, setting the monitoring license plate number as a second blacklist vehicle, associating the difference between the payment value and the value to be paid with the monitoring license plate number, and prompting the value to be paid through the monitoring license plate number when the second blacklist vehicle enters the parking space next time.
The invention has the beneficial effects that:
according to the aspects disclosed by the invention, through the matched use of the data acquisition module, the data processing module, the data analysis module, the early warning prompt module and the monitoring evidence collection module, the aim of checking video recording accountability and evidence tracing without manual work during parking rubbing is fulfilled, and the evidence tracing efficiency is improved;
the method comprises the steps that a data acquisition module is used for acquiring a parking information set and a parking in-out information set in a parking space, wherein the parking information set comprises parking space coordinate information, parking space type information and parking space use information, and the parking in-out information set comprises parking vehicle section information, parking in-out information and parking out-of-out information; by collecting the parking information set and the parking warehousing and ex-warehousing information set in the parking space and analyzing and processing the parking information set, comprehensive analysis is performed on various factors, the accuracy of data analysis can be improved, and effective data support is provided for subsequent early warning and verification;
receiving the parking information set and the parking warehousing-out information set by using the data processing module and carrying out processing operation to obtain parking space coordinate processing information, parking vehicle type processing information, parking space use processing information, parking vehicle section processing information, parking warehousing-in processing information and parking warehousing-out processing information; the data in the parking information set and the parking warehousing-out information set are processed, so that the calculation and analysis of subsequent data are facilitated;
the data analysis module is used for analyzing the received data to obtain a data analysis set, and a plurality of ordered position matching values and vehicle matching values are obtained through calculation, so that the relation between the parking information set and a plurality of data in the parking in-out information set is established, and the efficiency and the accuracy of data processing are improved;
receiving a data analysis set by using an early warning prompt module and carrying out early warning analysis operation; the monitoring evidence collection module is used for photographing and collecting evidence of vehicles with abnormal parking in and out of the garage and vehicles with abnormal clearing in and out of the garage according to the early warning analysis set; whether the parking stall corresponding to the abnormal signal is scratched or not can be timely arranged for personnel to timely handle the accident and the vehicle with abnormal parking fee payment can be handled.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of a parking space monitoring system based on big data according to the present invention.
Fig. 2 is a schematic structural diagram of an electronic device of a parking space monitoring system based on big data according to the present invention.
Detailed Description
The technical method 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, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1-2, the present invention relates to a parking space monitoring system based on big data, which includes a data acquisition module, a data processing module, a data analysis module, an early warning prompt module and a monitoring evidence collection module;
the data acquisition module is used for acquiring a parking information set and a parking in-out information set in a parking space, wherein the parking information set comprises parking space coordinate information, parking space type information and parking space use information, the parking in-out information set comprises parking vehicle section information, parking in-out information and parking out-of-out information, and the parking information set and the parking in-out-of-out information set are sent to the data processing module together;
the data processing module is used for receiving the parking information set and the parking warehousing-out information set and carrying out processing operation to obtain parking space coordinate processing information, parking vehicle type processing information, parking space use processing information, parking vehicle section processing information, parking warehousing-in processing information and parking warehousing-out processing information; and send it to the data analysis module together; the data processing module is used for receiving the parking information set and the parking warehousing-out information set and performing processing operation, and comprises the following specific steps:
receiving a parking information set and a parking warehousing-out information set, and acquiring parking space coordinate information, parking space type information and parking space use information in the parking information set;
marking the coordinate of each parking space in the parking space coordinate information as TCZi, wherein i is 1,2.. n; establishing a coordinate system by taking the entrance as an original point, performing ascending arrangement according to the distance between the coordinates of the parking stalls and the original point, and combining the coordinates of the parking stalls to obtain coordinate processing information of the parking stalls;
setting the unparked parking spaces with both sides unparked in the parking space type information as a first parking space weight, and marking the unparked parking spaces as YTCi, i is 1,2.. n; setting an unpark position with one side being unparked in the parking position type information as a second parking position weight, and marking the unpark position as ETCi, wherein i is 1,2.. n; setting the unworked parking spaces with both sides parked in the parking space type information as a third parking space weight, and marking the third parking space weight as STCi, wherein i is 1,2.. n; combining the marked first parking space weight, the marked second parking space weight and the marked third parking space weight to obtain parking space type processing information;
marking the starting parking time in the parking space use information as KTSi, wherein i is 1,2.. n; marking the parking stopping time in the parking space use information as JTSi, wherein i is 1,2.. n; acquiring a parking time mark TSLi, wherein i is 1,2.. n; combining the marked starting parking time, ending parking time and parking duration to obtain parking space use processing information;
acquiring a parking in-out information set comprising parking vehicle section information, parking in-out information and parking out-of-out information;
marking a plurality of road sections in the parking vehicle road section information as TCLi, wherein i is 1,2.. n; setting different corresponding road section preset values when two sides of different road sections stop, matching a plurality of road sections in the road section information of the parking vehicle with all the road sections to obtain the corresponding road section preset values, and marking the road section preset values as LYi, wherein i is 1,2. Combining the marked road sections and corresponding road section preset values thereof to obtain parking vehicle road section processing information;
marking the parking license plate in the parking and warehousing information as RCBi, wherein i is 1,2.. n; marking the historical arrearage in the parking and warehousing information as LQFi, i is 1,2.. n; marking the parking space entering time length as TRSi, wherein i is 1,2.. n; combining the marked warehousing license plate, the historical arrearages and the parking space entering duration to obtain parking warehousing processing information;
marking the license plate of the fee evasion vehicle in the parking and ex-warehouse information as TCBi, wherein i is 1,2.. n; marking the vehicle fee corresponding to the license plate of the vehicle with the fee of fee evasion as TCFi, wherein i is 1,2.. n; marking the parking departure time length as TCSi, wherein i is 1,2.. n; combining the marked license plate of the fee evasion vehicle and the corresponding fee evasion vehicle and the parking space leaving time length to obtain parking and leaving processing information;
the data analysis module is used for analyzing the received data to obtain a data analysis set, the data analysis set comprises a plurality of ordered bit matching values and vehicle matching values, and the data analysis set is sent to the early warning prompt module; the specific steps of the data analysis module for analyzing the received data include:
receiving marked first parking space weight YTCi, second parking space weight ETci, third parking space weight STCi, starting parking time KTSi, ending parking time JTSi, parking time TSLi, a plurality of road sections TCLi, road section preset values LYi, warehousing license plates RCBi, historical arrearages LQFi, toll evasion TCFi, parking space entering time TRSi and parking space leaving time TCSi;
obtaining a position matching value of the parking space to be parked by using a formula, wherein the formula is as follows:
wherein Q iswpExpressed as a bit matching value, alpha is expressed as a preset bit matching correction factor, a1, a2, a3 and a4 are expressed as different proportionality coefficients, and a1+ a2+ a3-a4 is not zero;
performing descending order permutation and combination on a plurality of bit matching values;
the vehicle matching value of the parking space to be parked is obtained by using a formula, wherein the formula is as follows:
wherein Q iscpExpressed as the vehicle-matching value, mu is expressed as the preset vehicle-matching correction factor, b1 and b2 are expressed as differentThe proportionality coefficient of (a);
performing descending order arrangement and combination on the plurality of vehicle matching values;
the early warning prompt module is used for receiving a data analysis set and performing early warning analysis operation, and comprises the following specific steps:
the method comprises the following steps: receiving a plurality of ordered bit-match values Q in a data analysis setwpNumber of cars Qcp；
Step two: marking a preset standard position matching threshold value as Y1, marking a preset standard vehicle matching threshold value as Y2, and respectively comparing and judging the standard position matching threshold value and the standard vehicle matching threshold value with a position matching value and a vehicle matching value;
step three: if QwpIf the parking position is less than or equal to Y1, judging that the parking vehicle corresponding to the matching value is normally parked in the garage and generating a first normal signal; if Qwp>Y1, judging that the parking vehicle corresponding to the matching value enters and exits the garage and is abnormally parked, generating a first alarm signal, marking the parking vehicle corresponding to the matching value as a first abnormal vehicle, and marking the parking space corresponding to the first abnormal vehicle as a parking space to be analyzed;
if QcpIf the parking vehicle is not more than Y2, judging that the parking vehicle corresponding to the matching value is normal in ex-warehouse settlement and generating a second normal signal; if Qcp>Y2, judging that the parking vehicle corresponding to the matching value is abnormal in the warehouse-out settlement, generating a second alarm signal, and marking the parking vehicle corresponding to the matching value as a second abnormal vehicle;
step four: combining the marked first alarm signal, the marked first abnormal vehicle and the corresponding parking space to be analyzed, and the marked second alarm signal and the marked second abnormal vehicle to obtain an early warning analysis set, carrying out early warning prompt according to the early warning analysis set, and sending the early warning analysis set to a monitoring evidence collection module; the method comprises the following specific steps:
acquiring a first abnormal vehicle and a parking space to be analyzed corresponding to a first alarm signal in an early warning analysis set, acquiring time for generating the first alarm signal and marking the time as a monitoring time point, acquiring a starting time point of video backup to be performed according to preset monitoring time at the monitoring time point, marking the time point of leaving the first abnormal vehicle as an ending time point of the video backup to be performed, storing video of the first abnormal vehicle according to the starting time point and the ending time point, generating video evidence data and storing the video evidence data into a database;
the method comprises the steps of obtaining working posts, working coordinates and working states of workers in a parking space, setting different working posts to correspond to different post preset values, matching the working posts of the workers with all the working posts to obtain corresponding post preset values, and marking the corresponding post preset values as GYi, wherein i is 1,2. Obtaining a distance value between the working coordinate and the parking space to be analyzed and marking the distance value as a distance to be measured DJi, wherein i is 1,2.. n; setting different working states corresponding to different worker-shaped preset values, matching the working states of workers with all the working states to obtain corresponding worker-shaped preset values, and marking the worker-shaped preset values as GZ, wherein i is 1,2.. n;
normalizing the marked post preset value, the distance to be measured and the I-shaped preset value, and taking a value, and acquiring the I-shaped value of the first abnormal vehicle by using a formula, wherein the formula is as follows:
wherein Q isgpExpressing as a work piece value, expressing delta as a preset work piece correction factor, and expressing g1, g2 and g3 as different proportionality coefficients;
setting the staff corresponding to the maximum work matching value as the selected staff, and sending the coordinates of the parking space to be analyzed to the selected staff for checking according to the reserved mobile phone number;
the monitoring evidence collection module is used for analyzing and collecting evidence of vehicles with abnormal parking in the warehouse and vehicles with abnormal ex-warehouse settlement according to the early warning analysis set, and the monitoring evidence collection module comprises the following specific steps:
acquiring a license plate number and parking time corresponding to a second abnormal vehicle corresponding to a second alarm signal in the early warning analysis set, marking the license plate number and the parking time as a monitoring license plate number and a monitoring parking time respectively, and acquiring a value to be paid according to the monitoring parking time and a preset parking charging unit price;
searching payment records in the data according to the monitoring license plate number, if the payment records of the monitoring license plate number do not exist, judging that the parking vehicle corresponding to the monitoring license plate number escapes, setting the monitoring license plate number as a first blacklist vehicle, associating the value to be paid with the monitoring license plate number, and prompting the payment through the monitoring license plate number when the first blacklist vehicle enters the parking space next time;
if the payment record of the monitoring license plate number exists but the payment value in the payment record is smaller than the value to be paid, determining that the parking vehicle corresponding to the monitoring license plate number is owed, setting the monitoring license plate number as a second blacklist vehicle, associating the difference between the payment value and the value to be paid with the monitoring license plate number, and prompting the value to be paid through the monitoring license plate number when the second blacklist vehicle enters the parking space next time.
Example two
The data acquisition module acquires monitoring information, the monitoring information comprises temperature data, humidity data, voltage data and current data of parked vehicles, and the monitoring information is sent to the data processing module;
the data processing module receives the monitoring information and carries out processing operation to obtain temperature processing data, humidity processing data, voltage processing data and current processing data; the method comprises the following specific steps:
marking the in-vehicle temperature in the temperature data as CNwi, i being 1,2.. n; marking the outside temperature in the temperature data as CWW, i being 1,2.. n; combining the marked in-vehicle temperature and the marked out-vehicle temperature to obtain temperature processing data;
marking the in-vehicle humidity in the humidity data as CNSi, i ═ 1,2.. n; marking the humidity outside the vehicle in the humidity data as CWSI, wherein i is 1,2.. n; combining the marked humidity inside the vehicle and the marked humidity outside the vehicle to obtain humidity processing data;
marking the monitored voltage in the voltage data as JDYi, i ═ 1,2.. n; combining the marked monitoring voltages to obtain voltage processing data; marking the monitored current in the current data as JDLi, i ═ 1,2.. n; combining the marked monitoring currents to obtain current processing data;
calculating and obtaining a screening value of the parking state by using a formula, wherein the formula is as follows:
wherein Q isspExpressed as a screening value, b1, b2, b3 and b4 are expressed as preset different proportionality coefficients, D1 is expressed as a preset standard temperature difference value, D2 is expressed as a preset standard humidity difference value, D3 is expressed as a preset standard voltage, and D4 is expressed as a preset standard current;
comparing and judging the screening value with a preset standard screening threshold value;
if the screening value is not larger than the standard screening threshold value, judging that the internal state of the parking vehicle is normal and generating a first screening signal;
if the screening value is larger than the standard screening threshold value, judging that the internal state of the parking vehicle is abnormal and generating a second screening signal;
acquiring corresponding coordinates of the parking vehicles according to the second screening signals, controlling the camera to carry out real-time shooting on the parking vehicles, and informing parking space workers to check parking conditions according to the coordinates of the parking vehicles;
the working principle of the embodiment of the invention is as follows: through the matched use of the data acquisition module, the data processing module, the data analysis module, the early warning prompt module and the monitoring and evidence collection module, the aim of improving the verification efficiency by checking video recording responsibility and verifying during parking rubbing and bumping is fulfilled without manual work;
the method comprises the steps that a data acquisition module is used for acquiring a parking information set and a parking in-out information set in a parking space, wherein the parking information set comprises parking space coordinate information, parking space type information and parking space use information, and the parking in-out information set comprises parking vehicle section information, parking in-out information and parking out-of-out information; by collecting the parking information set and the parking warehousing and ex-warehousing information set in the parking space and analyzing and processing the parking information set, comprehensive analysis is performed on various factors, the accuracy of data analysis can be improved, and effective data support is provided for subsequent early warning and verification;
receiving the parking information set and the parking warehousing-out information set by using the data processing module and carrying out processing operation to obtain parking space coordinate processing information, parking vehicle type processing information, parking space use processing information, parking vehicle section processing information, parking warehousing-in processing information and parking warehousing-out processing information; the data in the parking information set and the parking warehousing-out information set are processed, so that the calculation and analysis of subsequent data are facilitated;
analyzing the received data by using a data analysis module to obtain a data analysis set, and using a formula
Acquiring a position matching value of a to-be-parked position; performing descending order permutation and combination on a plurality of bit matching values; using formulas
Acquiring a vehicle matching value of a to-be-parked position; performing descending order arrangement and combination on the plurality of vehicle matching values; a plurality of ordered position matching values and vehicle matching values are obtained through calculation, so that the relation is established between the parking information set and a plurality of data in the parking and warehousing information set, and the efficiency and the accuracy of data processing are improved;
receiving a data analysis set by using an early warning prompt module and carrying out early warning analysis operation; the monitoring evidence collection module is used for photographing and collecting evidence of vehicles with abnormal parking in and out of the garage and vehicles with abnormal clearing in and out of the garage according to the early warning analysis set; using formulas
Acquiring a work matching value of a first abnormal vehicle; setting the staff corresponding to the maximum work matching value as the selected staff, and sending the coordinates of the parking space to be analyzed to the selected staff for checking according to the reserved mobile phone number; whether the parking stall corresponding to the abnormal signal is scratched or not can be timely arranged for personnel to timely handle the accident and the vehicle with abnormal parking fee payment can be handled.
Fig. 2 is a schematic structural diagram of an electronic device for implementing a parking space monitoring system based on big data according to the present invention.
The electronic device may comprise a processor, a memory and a bus, and may further comprise a computer program stored in the memory and executable on the processor, such as a program of a big data based parking space monitoring system.
Wherein the memory comprises at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory may also be an external storage device of the electronic device in other embodiments, such as a plug-in removable hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the electronic device. The memory may also include both internal storage units and external storage devices of the electronic device. The memory may be used not only to store application software installed in the electronic device and various types of data, such as codes of a large data-based parking space monitoring system, etc., but also to temporarily store data that has been output or is to be output.
The processor may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor is a Control Unit of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules stored in the memory (for example, executing a big data-based parking space monitoring system, etc.) and calling data stored in the memory.
The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connected communication between the memory and at least one processor or the like.
Fig. 2 shows only an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 2 does not constitute a limitation of the electronic device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (e.g., a battery) for supplying power to the components, and the power supply may be logically connected to the at least one processor through a power management device, so as to implement functions such as charge management, discharge management, and power consumption management through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
The electronic device may further include a network interface, which may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices.
The electronic device may further comprise a user interface, which may be a Display (Display), an input unit, such as a Keyboard (Keyboard), or a standard wired, wireless interface. In some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, and the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The memory in the electronic device stores a program of a big data based parking space monitoring system that is a combination of instructions that, when executed in the processor, may implement the steps of fig. 1.
The specific implementation method of the processor for the instruction may refer to the description of the relevant steps in the embodiment corresponding to fig. 1, which is not described herein again.
The electronic device integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a non-volatile computer-readable storage medium. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of the embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above examples are only intended to illustrate the technical process of the present invention and not to limit the same, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical process of the present invention without departing from the spirit and scope of the technical process of the present invention.
Claims (5)
1. A parking space monitoring system based on big data is characterized by comprising a data acquisition module, a data processing module, a data analysis module, an early warning prompt module and a monitoring evidence collection module;
the data acquisition module is used for acquiring a parking information set and a parking in-out information set in a parking space, wherein the parking information set comprises parking space coordinate information, parking space type information and parking space use information, the parking in-out information set comprises parking vehicle section information, parking in-out information and parking out-of-out information, and the parking information set and the parking in-out-of-out information set are sent to the data processing module together;
the data processing module is used for receiving the parking information set and the parking warehousing-out information set and carrying out processing operation to obtain parking space coordinate processing information, parking vehicle type processing information, parking space use processing information, parking vehicle section processing information, parking warehousing-in processing information and parking warehousing-out processing information; and send it to the data analysis module together;
the data analysis module is used for analyzing the received data to obtain a data analysis set, the data analysis set comprises a plurality of ordered bit matching values and vehicle matching values, and the data analysis set is sent to the early warning prompt module;
the early warning prompt module is used for receiving a data analysis set and performing early warning analysis operation, and comprises the following specific steps:
the method comprises the following steps: receiving a plurality of ordered bit-match values Q in a data analysis setwpNumber of cars Qcp；
Step two: marking a preset standard position matching threshold value as Y1, marking a preset standard vehicle matching threshold value as Y2, and respectively comparing and judging the standard position matching threshold value and the standard vehicle matching threshold value with a position matching value and a vehicle matching value;
step three: if QwpIf the parking position is less than or equal to Y1, judging that the parking vehicle corresponding to the matching value is normally parked in the garage and generating a first normal signal; if Qwp>Y1, judging that the parking vehicle corresponding to the matching value enters and exits the garage and is abnormally parked, generating a first alarm signal, marking the parking vehicle corresponding to the matching value as a first abnormal vehicle, and marking the parking space corresponding to the first abnormal vehicle as a parking space to be analyzed;
if QcpIf the parking vehicle is not more than Y2, judging that the parking vehicle corresponding to the matching value is normal in ex-warehouse settlement and generating a second normal signal; if Qcp>Y2, judging that the parking vehicle corresponding to the matching value is abnormal in the warehouse-out settlement, generating a second alarm signal, and marking the parking vehicle corresponding to the matching value as a second abnormal vehicle;
step four: combining the marked first alarm signal, the marked first abnormal vehicle and the corresponding parking space to be analyzed, and the marked second alarm signal and the marked second abnormal vehicle to obtain an early warning analysis set, carrying out early warning prompt according to the early warning analysis set, and sending the early warning analysis set to a monitoring evidence collection module;
and the monitoring evidence collection module is used for analyzing and collecting evidence of vehicles with abnormal parking in the warehouse and vehicles with abnormal ex-warehouse settlement according to the early warning analysis set.
2. The big-data-based parking space monitoring system according to claim 1, wherein the specific steps of the data processing module for receiving the parking information set and the parking warehousing information set and performing the processing operation include:
s21: receiving a parking information set and a parking warehousing-out information set, and acquiring parking space coordinate information, parking space type information and parking space use information in the parking information set;
s22: marking the coordinate of each parking space in the parking space coordinate information as TCZi, wherein i is 1,2.. n; establishing a coordinate system by taking the entrance as an original point, performing ascending arrangement according to the distance between the coordinates of the parking stalls and the original point, and combining the coordinates of the parking stalls to obtain coordinate processing information of the parking stalls;
s23: setting the unparked parking spaces with both sides unparked in the parking space type information as a first parking space weight, and marking the unparked parking spaces as YTCi, i is 1,2.. n; setting an unpark position with one side being unparked in the parking position type information as a second parking position weight, and marking the unpark position as ETCi, wherein i is 1,2.. n; setting the unworked parking spaces with both sides parked in the parking space type information as a third parking space weight, and marking the third parking space weight as STCi, wherein i is 1,2.. n; combining the marked first parking space weight, the marked second parking space weight and the marked third parking space weight to obtain parking space type processing information;
s24: marking the starting parking time in the parking space use information as KTSi, wherein i is 1,2.. n; marking the parking stopping time in the parking space use information as JTSi, wherein i is 1,2.. n; acquiring a parking time mark TSLi, wherein i is 1,2.. n; combining the marked starting parking time, ending parking time and parking duration to obtain parking space use processing information;
s25: acquiring a parking in-out information set comprising parking vehicle section information, parking in-out information and parking out-of-out information;
s26: marking a plurality of road sections in the parking vehicle road section information as TCLi, wherein i is 1,2.. n; setting different corresponding road section preset values when two sides of different road sections stop, matching a plurality of road sections in the road section information of the parking vehicle with all the road sections to obtain the corresponding road section preset values, and marking the road section preset values as LYi, wherein i is 1,2. Combining the marked road sections and corresponding road section preset values thereof to obtain parking vehicle road section processing information;
s27: marking the parking license plate in the parking and warehousing information as RCBi, wherein i is 1,2.. n; marking the historical arrearage in the parking and warehousing information as LQFi, i is 1,2.. n; marking the parking space entering time length as TRSi, wherein i is 1,2.. n; combining the marked warehousing license plate, the historical arrearages and the parking space entering duration to obtain parking warehousing processing information;
s28: marking the license plate of the fee evasion vehicle in the parking and ex-warehouse information as TCBi, wherein i is 1,2.. n; marking the vehicle fee corresponding to the license plate of the vehicle with the fee of fee evasion as TCFi, wherein i is 1,2.. n; marking the parking departure time length as TCSi, wherein i is 1,2.. n; and combining the marked license plate of the fee evasion vehicle and the corresponding fee evasion vehicle and the parking space leaving time length to obtain parking and leaving warehouse processing information.
3. The big-data-based parking space monitoring system according to claim 1, wherein the specific steps of the data analysis module for performing analysis operation on the received data include:
s31: receiving marked first parking space weight YTCi, second parking space weight ETci, third parking space weight STCi, starting parking time KTSi, ending parking time JTSi, parking time TSLi, a plurality of road sections TCLi, road section preset values LYi, warehousing license plates RCBi, historical arrearages LQFi, toll evasion TCFi, parking space entering time TRSi and parking space leaving time TCSi;
s32: obtaining a position matching value of the parking space to be parked by using a formula, wherein the formula is as follows:
wherein Q iswpExpressed as a bit matching value, alpha is expressed as a preset bit matching correction factor, a1, a2, a3 and a4 are expressed as different proportionality coefficients, and a1+ a2+ a3-a4 is not zero;
s33: performing descending order permutation and combination on a plurality of bit matching values;
s34: the vehicle matching value of the parking space to be parked is obtained by using a formula, wherein the formula is as follows:
wherein Q iscpThe vehicle matching value is expressed, mu is a preset vehicle matching correction factor, and b1 and b2 are different proportionality coefficients;
s35: and carrying out descending order arrangement and combination on the plurality of vehicle matching values.
4. The big-data-based parking space monitoring system according to claim 1, wherein early warning prompting is performed according to an early warning analysis set, and the specific steps include:
s41: acquiring a first abnormal vehicle and a parking space to be analyzed corresponding to a first alarm signal in an early warning analysis set, acquiring time for generating the first alarm signal and marking the time as a monitoring time point, acquiring a starting time point of video backup to be performed according to preset monitoring time at the monitoring time point, marking the time point of leaving the first abnormal vehicle as an ending time point of the video backup to be performed, storing video of the first abnormal vehicle according to the starting time point and the ending time point, generating video evidence data and storing the video evidence data into a database;
s42: the method comprises the steps of obtaining working posts, working coordinates and working states of workers in a parking space, setting different working posts to correspond to different post preset values, matching the working posts of the workers with all the working posts to obtain corresponding post preset values, and marking the corresponding post preset values as GYi, wherein i is 1,2. Obtaining a distance value between the working coordinate and the parking space to be analyzed and marking the distance value as a distance to be measured DJi, wherein i is 1,2.. n; setting different working states corresponding to different worker-shaped preset values, matching the working states of workers with all the working states to obtain corresponding worker-shaped preset values, and marking the worker-shaped preset values as GZ, wherein i is 1,2.. n;
s43: normalizing the marked post preset value, the distance to be measured and the I-shaped preset value, and taking a value, and acquiring the I-shaped value of the first abnormal vehicle by using a formula, wherein the formula is as follows:
wherein Q isgpExpressing as a work piece value, expressing delta as a preset work piece correction factor, and expressing g1, g2 and g3 as different proportionality coefficients;
s44: and setting the staff corresponding to the maximum work matching value as the selected staff, and sending the coordinates of the parking space to be analyzed to the selected staff for checking according to the reserved mobile phone number.
5. The big-data-based parking space monitoring system according to claim 1, wherein the monitoring and evidence collection module is used for analyzing and collecting the vehicle with abnormal parking in and out and settlement according to the early warning analysis set, and comprises the following specific steps:
s51: acquiring a license plate number and parking time corresponding to a second abnormal vehicle corresponding to a second alarm signal in the early warning analysis set, marking the license plate number and the parking time as a monitoring license plate number and a monitoring parking time respectively, and acquiring a value to be paid according to the monitoring parking time and a preset parking charging unit price;
s52: searching payment records in the data according to the monitoring license plate number, if the payment records of the monitoring license plate number do not exist, judging that the parking vehicle corresponding to the monitoring license plate number escapes, setting the monitoring license plate number as a first blacklist vehicle, associating the value to be paid with the monitoring license plate number, and prompting the payment through the monitoring license plate number when the first blacklist vehicle enters the parking space next time;
s53: if the payment record of the monitoring license plate number exists but the payment value in the payment record is smaller than the value to be paid, determining that the parking vehicle corresponding to the monitoring license plate number is owed, setting the monitoring license plate number as a second blacklist vehicle, associating the difference between the payment value and the value to be paid with the monitoring license plate number, and prompting the value to be paid through the monitoring license plate number when the second blacklist vehicle enters the parking space next time.
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