CN116486578A - Data monitoring method based on big data - Google Patents

Data monitoring method based on big data Download PDF

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Publication number
CN116486578A
CN116486578A CN202310459891.6A CN202310459891A CN116486578A CN 116486578 A CN116486578 A CN 116486578A CN 202310459891 A CN202310459891 A CN 202310459891A CN 116486578 A CN116486578 A CN 116486578A
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China
Prior art keywords
parking
vehicle
information data
abnormal
monitoring
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CN202310459891.6A
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Chinese (zh)
Inventor
李进
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Hengyang Jiling Information Technology Co ltd
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Hengyang Jiling Information Technology Co ltd
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Priority to CN202310459891.6A priority Critical patent/CN116486578A/en
Publication of CN116486578A publication Critical patent/CN116486578A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Devices For Checking Fares Or Tickets At Control Points (AREA)

Abstract

The invention discloses a data monitoring method based on big data, and relates to the field of data monitoring; setting a region to be tested as a parking garage, collecting information data of vehicle entering and exiting in a parking space and vehicle parking, processing the collected information data to obtain processed information data, analyzing the processed information data, utilizing the processed information data to obtain a parking space matching value and a vehicle matching value, comparing the parking space matching value and a standard threshold value, generating an alarm signal, judging abnormal vehicles in the parking space, receiving the alarm signal to reduce a monitoring range, monitoring and evidence obtaining the abnormal vehicles, checking the abnormal vehicles, obtaining the information data of the abnormal vehicles, arranging personnel to check monitoring video and pursue responsibility and check, arranging personnel to process vehicles with abnormal parking fee, shortening the parking time of the vehicles with abnormal fee, and improving the efficiency of parking fee.

Description

Data monitoring method based on big data
Technical Field
The invention relates to the field of data monitoring, in particular to a data monitoring method based on big data.
Background
The existing parking space management system is a set of network system which is built by a computer, network equipment and parking space management equipment and is used for managing the vehicle entering and exiting of a parking space, guiding the vehicle flow in the field and collecting parking fees, and is a necessary tool for a professional parking management company;
in the prior art, a parking lot cannot find abnormal vehicles in time in the parking process, and a large amount of time is required to check the abnormal vehicles, so that manpower and material resources are wasted, and in order to solve the problem, a data monitoring method based on big data is provided.
Disclosure of Invention
The invention aims to provide a data monitoring method based on big data.
The aim of the invention can be achieved by the following technical scheme, namely a data monitoring method based on big data, which comprises the following steps:
step one: setting a region to be detected as a parking garage, and collecting information data of vehicle entering and exiting and parking in a parking space and vehicle parking;
step two: processing the collected information data;
step three: analyzing the processed information data, judging whether the vehicle in the parking space is an abnormal vehicle or not, and generating an alarm signal;
step four: and monitoring and evidence obtaining is carried out on the abnormal vehicle by receiving the alarm signal, and the abnormal vehicle is processed.
Further, the process of collecting information data of vehicle entering and exiting in a parking space and vehicle parking comprises the following steps:
the vehicle in-out warehouse information data comprises parking warehouse information data and parking warehouse information data, and the vehicle parking information data comprises parking stall coordinate information data, parking stall category information data and parking stall use information data;
the parking information data comprise license plates, historical arrearage records and parking time of parking places of vehicles;
the parking and leaving information data comprise license plates, parking fee escaping fees and vehicle leaving time;
the parking space use information data comprise a start parking time, an end parking time and a parking duration.
Further, the processing of the collected information data includes:
the collected information data of the vehicle entering and exiting warehouse and the vehicle parking are subjected to marking processing operation, so that processed information data are obtained;
according to whether two sides of the parking vehicle type information data used by a user are parked or not, the empty spaces which are not parked are set to be the first parking space weight, the empty spaces which are not parked are set to be the second parking space weight, and the parking spaces which are parked on two sides are set to be the third parking space weight.
Obtaining a parking space matching value L according to the parking space weight, the parking space entering time and the parking space exiting time 1 ；
Obtaining a parking space matching value by using a weight formula, wherein the formula is as follows:
wherein L is 1 The parking space matching value is expressed, alpha is expressed as a correction factor for preset parking space matching, a1, a2, a3 and a4 are expressed as different proportion coefficients, and a1+a2+a3-a4 is not equal to 0;
obtaining a vehicle matching value L according to the historical arrearage record and the processing data of the parking fee 2 ；
Obtaining a vehicle matching value of a parking space by using the formula:
further, the process of judging whether the parking vehicle goes out of the warehouse or not is abnormal according to the parking space matching value comprises the following steps:
setting a standard parking space matching threshold Y 1 Comparing the obtained parking space matching value with a standard parking space matching threshold value:
when L 1 ≤Y 1 Judging that the parking vehicle corresponding to the parking space matching value is normally parked in the warehouse and generating a first normal signal;
when L 1 ＞Y 1 And judging that the parking vehicle corresponding to the parking space matching value is abnormal in parking, generating a first alarm signal, and marking the corresponding vehicle as a first abnormal vehicle.
Further, the process of judging whether the parking vehicle delivery settlement is normal according to the vehicle matching value comprises the following steps:
setting a standard vehicle matching threshold Y 2 Comparing the obtained vehicle matching value with a standard vehicle matching threshold value:
when L 2 ≤Y 2 Judging that the vehicle delivery settlement corresponding to the vehicle matching value is normal;
when L 2 ＞Y 2 And judging that the vehicle delivery settlement corresponding to the vehicle matching value is abnormal, generating a second alarm signal, and marking the corresponding vehicle as a second abnormal vehicle.
Further, the process of monitoring and evidence obtaining for the first abnormal vehicle by receiving the first alarm signal comprises the following steps:
acquiring a time point of warehousing and a time point of ex-warehouse of a first abnormal vehicle in the monitoring video, storing the monitoring video of the first abnormal vehicle according to the time point, and generating an abnormal video;
and further judging whether the parking vehicle in-out warehouse is damaged to other parking vehicles or not according to the abnormal video, if so, informing the parking vehicle owners of the treatment problem.
Further, the process of monitoring and evidence obtaining for the second abnormal vehicle by receiving the second alarm signal comprises the following steps:
obtaining second abnormal vehicle information data corresponding to the second alarm signal according to the monitoring video;
the second abnormal vehicle information data comprise a monitoring license plate number and a monitoring parking time, and the amount to be paid is obtained according to the monitoring parking time and a preset parking charging unit price;
searching payment records according to the monitored license plate numbers, and further judging the escape behavior or the arrearage behavior of the parked vehicle:
if the payment record is not searched, judging that the parking vehicle corresponding to the monitoring license plate number is a fee escaping behavior;
if the payment record is searched but the payment amount is smaller than the amount to be paid, judging that the parking vehicle corresponding to the monitoring license plate number is in arrearage.
Compared with the prior art, the invention has the beneficial effects that: the data monitoring method based on big data can reduce the monitoring range, arrange personnel in time to check video recording and follow-up verification, improve the checking efficiency, arrange personnel in time to process vehicles with abnormal parking fee collection, shorten the parking time of the vehicles with abnormal fee collection, and improve the efficiency of vehicle lifting fee collection.
Drawings
FIG. 1 is a schematic diagram of the present invention;
Detailed Description
As shown in fig. 1, a data monitoring method based on big data includes the following steps:
step one: setting a region to be detected as a parking garage, and collecting information data of vehicle entering and exiting in a parking space and vehicle parking;
the vehicle in-out garage information data comprises parking vehicle road section information data, parking garage information data and parking garage information data, and the vehicle parking information data comprises parking space coordinate information data, parking space category information data and parking space use information data;
the parking space category information data are divided into a large parking space and a small parking space according to the size;
the road information data of the parked vehicles are two sections of road information entering and exiting the parking lot, cameras are installed, and the road cameras are used for obtaining license plates of the vehicles entering and exiting the parking lot;
the parking information data comprise license plates, historical arrearage records and parking time of parking places of vehicles;
the parking and leaving information data comprise license plates, parking fee escaping fees and vehicle leaving time.
Step two: processing the collected information data;
processing the acquired information data of the vehicle entering and exiting warehouse and the vehicle parking to obtain coordinate processing information data of the parking space, parking vehicle type processing information data and parking space use processing information data, wherein the specific process comprises the following steps:
marking the coordinates of the parking spaces, establishing a rectangular coordinate system by taking a parking entrance as an origin, and arranging the coordinates of the parking spaces in ascending order according to the distance between the coordinates of the parking spaces and the origin;
the parking space coordinate processing information data are formed by combining marked parking space coordinates;
setting a first parking space weight as a vacant space on two sides of the parking vehicle type information data needed by a user, and marking the vacant space as W i Setting a vacant parking space on one side of the parking vehicle type information data needed by the user as a second parking space weight, and marking the vacant parking space as E i Setting a third parking space weight as a parking space of the parking vehicle type information data which is needed by a user and is used by the user, and marking the third parking space weight as S i Wherein i is an integer of 1 or more;
the parking vehicle category processing information data is formed by combining marked first parking space weights, second parking space weights and third parking space weights;
it should be further noted that, in the specific implementation process, if one side of the parking space does not have a space where the other side of the parking space is not parked, the first parking space weight is 0, if one side of the parking space does not have a space where the other side of the parking space is parked, the second parking space weight is 0, and if both sides of the parking space are spaces, the third parking space weight is 0;
the starting parking time in the parking space use information data is marked as K i Will end the parking time and is marked as T i Obtaining the parking time according to the starting parking time and the ending parking time, and marking as J i Wherein i is an integer of 1 or more;
the parking space use processing information data are formed by combining marked starting parking time, parking ending time and parking duration;
marking two road segments in the parking vehicle road segment information data as D 1 And D 2 Marking the number of the warehouse-in license plate in the parking warehouse-in information data as H i Marking a historical arrearage record in parking information data as Q i Marking the parking space entering duration in the parking space entering information data as U i Wherein i is an integer of 1 or more;
the parking vehicle road section processing information data is formed by combining marked warehouse-in license plate numbers, historical arrearage records and parking time duration;
marking the license plate number of the escaping vehicle in the parking and delivering information data as G i Marking the escaping parking fee in the parking and leaving information data as V i Marking the vehicle parking space time length in the parking and leaving information data as N i Wherein i is an integer of 1 or more;
the parking and leaving processing information data are formed by combining the number of the marked license plate of the escaping fee vehicle, the escaping parking fee and the vehicle leaving time.
Step three: analyzing the processed information data, judging whether the vehicle in the parking space is an abnormal vehicle or not, and generating an alarm signal;
calculating and obtaining a parking space matching value of a to-be-parked space according to data obtained by data processing;
obtaining a parking space matching value by using a weight formula, wherein the formula is as follows:
wherein L is 1 The parking space matching value is expressed, alpha is expressed as a correction factor for preset parking space matching, a1, a2, a3 and a4 are expressed as different proportion coefficients, and a1+a2+a3-a4 is not equal to 0;
the obtained parking space matching values are arranged and combined in a descending order;
obtaining a vehicle matching value of a parking space by using the formula:
wherein L is 2 Expressed as a vehicle match value, beta is expressed as a correction factor for a preset vehicle match, b1 and b 2 Representing different ratio coefficients;
the obtained vehicle matching values are combined in a descending order;
setting a standard parking space matching threshold value as Y 1 Standard ofThe vehicle matching threshold is Y 2 ；
Respectively matching the obtained parking space matching value and the obtained vehicle matching value with a standard parking space matching threshold Y 1 Standard vehicle matching threshold Y 2 Matching is carried out, and whether the vehicle is an abnormal vehicle or not is judged;
when L 1 ≤Y 1 Judging that the parking vehicle corresponding to the parking space matching value is normally parked in the warehouse and generating a first normal signal;
when L 1 ＞Y 1 Judging that the parking vehicle corresponding to the parking space matching value is abnormal in entering and exiting, and generating a first alarm signal, so that the corresponding parking vehicle is marked as a first abnormal vehicle, and the parking space corresponding to the first abnormal vehicle is marked as a parking space to be detected;
when L 2 ≤Y 2 Judging that the vehicle delivery settlement corresponding to the vehicle matching value is normal, and generating a second normal signal;
when L 2 ＞Y 2 And judging that the vehicle delivery settlement corresponding to the vehicle matching value is abnormal, generating a second alarm signal, and marking the vehicle corresponding to the vehicle matching value as a second abnormal vehicle.
Step four: monitoring and evidence obtaining are carried out on the abnormal vehicles by receiving the alarm signals, and the abnormal vehicles are processed;
the alarm signal is received to monitor and evidence the abnormal vehicle, and the specific process comprises the following steps:
the method comprises the steps of performing first abnormal vehicle information data corresponding to a first alarm signal of a monitoring video and corresponding parking space information data to be detected, obtaining the time for generating the first alarm signal, and marking the time as a monitoring time point;
the starting time of the monitoring time point is a time point for acquiring a first abnormal vehicle to put in storage according to the monitoring video, the ending time point of the monitoring time point is a time point for acquiring a first abnormal vehicle to put out of storage according to the starting time point and the ending time point, the monitoring video of the first abnormal vehicle is stored, and abnormal video reserved evidence is generated and stored in a database;
the parking space information data to be detected comprises vehicle information of a parking space, wherein the vehicle information comprises personal information of a vehicle owner, a working position and coordinates of a parking space;
the personal information includes the name and telephone number of the owner;
judging whether the parking space to be detected corresponding to the abnormal vehicle is occupied by the abnormal vehicle or not according to the abnormal video and the vehicle information of the parking space:
if so, acquiring the license plate number of the abnormal vehicle, judging that the parking space to be detected is occupied by the abnormal vehicle according to the coordinates of the parking space, and informing the vehicle owner to move the vehicle and vacate the parking space;
if not, judging whether the adjacent vehicle is damaged during the warehouse-in and warehouse-out process according to the abnormal video, if so, informing the vehicle owner of solving the problem.
Performing monitoring video second abnormal vehicle information data corresponding to the second alarm signal;
the second abnormal vehicle information data comprises license plates and parking time, the corresponding license plates are marked as monitoring license plates and the corresponding parking time is marked as monitoring parking time, and the amount to be paid is obtained according to the monitoring parking time and the preset parking charging unit price;
searching a payment record in a database according to the license plate number;
if the payment record of the monitoring license plate number does not exist, judging that the parking vehicle corresponding to the monitoring license plate number is a fee evasion vehicle, setting the monitoring license plate number as a first blacklist parking vehicle, associating the amount to be paid with the monitoring license plate number, reminding a vehicle owner to pay through the monitoring license plate number when the first blacklist parking vehicle enters a parking space again, and if the vehicle owner cannot enter a parking garage to park;
if the payment record of the monitoring license plate number exists but the payment amount is smaller than the amount to be paid, judging the parking arrears corresponding to the monitoring license plate number, adding the parking arrears record to the historical arrears record of the vehicle, setting the monitoring license plate number as a second blacklist parking vehicle, associating the monitoring license plate number with the second blacklist parking vehicle, and when the second blacklist parking amount enters a parking space again, monitoring the monitoring license plate number and reminding the vehicle owner to pay, and if the parking amount does not pay, failing to enter a parking garage to park;
marking the blacklist parking vehicle as a belief-losing vehicle and storing the blacklist parking vehicle into a database;
it should be further noted that, in the specific implementation process, the parking duration marked as the belief-losing vehicle can be shortened according to the times of adding the blacklist, and other parking garages are entered, so that the staff can be reminded that the parked vehicle is the belief-losing vehicle, the fee escaping or arrearage behaviors of the parked vehicle are further avoided, and the belief-losing vehicle is warned to be in an faith parking state.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.

Claims (7)

1. A data monitoring method based on big data, the method comprising:
step one: setting a region to be detected as a parking garage, and collecting information data of vehicle entering and exiting in a parking space and information data of vehicle parking;
step two: processing the collected information data;
step three: analyzing the processed information data, judging whether the vehicle in the parking space is an abnormal vehicle or not, and generating an alarm signal;
step four: and monitoring and evidence obtaining is carried out on the abnormal vehicle by receiving the alarm signal, and the abnormal vehicle is processed.
2. The method for monitoring data based on big data according to claim 1, wherein the process of collecting information data of vehicle in-out and in-in and vehicle parking in the parking space comprises the steps of:
the vehicle in-out warehouse information data comprises parking warehouse information data and parking warehouse information data, and the vehicle parking information data comprises parking stall coordinate information data, parking stall category information data and parking stall use information data;
the parking information data comprise license plates, historical arrearage records and parking time of parking places of vehicles;
the parking and leaving information data comprise license plates, parking fee escaping fees and vehicle leaving time;
the parking space use information data comprise a start parking time, an end parking time and a parking duration.
3. The big data based data monitoring method of claim 2, wherein the processing of the collected information data comprises:
the collected information data of the vehicle entering and exiting warehouse and the vehicle parking are subjected to marking processing operation, so that processed information data are obtained;
according to whether two sides of the parking vehicle type information data used by a user are parked or not, the empty spaces which are not parked are set to be the first parking space weight, the empty spaces which are not parked are set to be the second parking space weight, and the parking spaces which are parked on two sides are set to be the third parking space weight.
Obtaining a parking space matching value L according to the parking space weight, the parking space entering time and the parking space exiting time 1 ；
Obtaining a vehicle matching value L according to the historical arrearage record and the processing data of the parking fee 2 。
4. The data monitoring method based on big data according to claim 3, wherein the process of judging whether the parking vehicle goes out and goes in to be abnormal according to the parking space matching value comprises the following steps:
setting a standard parking space matching threshold Y 1 Comparing the obtained parking space matching value with a standard parking space matching threshold value:
when L 1 ≤Y 1 Judging the matching value of the parking spaceThe corresponding parked vehicles go out and go in the warehouse to park normally, and a first normal signal is generated;
when L 1 ＞Y 1 And judging that the parking vehicle corresponding to the parking space matching value is abnormal in parking, generating a first alarm signal, and marking the corresponding vehicle as a first abnormal vehicle.
5. A data monitoring method based on big data according to claim 3, wherein the process of judging whether the parking vehicle delivery settlement is normal according to the vehicle matching value comprises:
setting a standard vehicle matching threshold Y 2 Comparing the obtained vehicle matching value with a standard vehicle matching threshold value:
when L 2 ≤Y 2 Judging that the vehicle delivery settlement corresponding to the vehicle matching value is normal;
when L 2 ＞Y 2 And judging that the vehicle delivery settlement corresponding to the vehicle matching value is abnormal, generating a second alarm signal, and marking the corresponding vehicle as a second abnormal vehicle.
6. The method for monitoring and controlling data based on big data as claimed in claim 4, wherein the process of monitoring and controlling the first abnormal vehicle for evidence by receiving the first alarm signal comprises:
acquiring a time point of warehousing and a time point of ex-warehouse of a first abnormal vehicle in the monitoring video, storing the monitoring video of the first abnormal vehicle according to the time point, and generating an abnormal video;
and further judging whether the parking vehicle in-out warehouse is damaged to other parking vehicles or not according to the abnormal video, if so, informing the parking vehicle owners of the treatment problem.
7. The method for monitoring and controlling data based on big data according to claim 5, wherein the process of monitoring and controlling the second abnormal vehicle for evidence by receiving the second alarm signal comprises:
obtaining second abnormal vehicle information data corresponding to the second alarm signal according to the monitoring video;
the second abnormal vehicle information data comprise a monitoring license plate number and a monitoring parking time, and the amount to be paid is obtained according to the monitoring parking time and a preset parking charging unit price;
searching payment records according to the monitored license plate numbers, and judging that the parked vehicle has a fee escaping behavior or a fee owed behavior:
if the payment record is not searched, judging that the parking vehicle corresponding to the monitoring license plate number is a fee escaping behavior;
if the payment record is searched but the payment amount is smaller than the amount to be paid, judging that the parking vehicle corresponding to the monitoring license plate number is in arrearage.
CN202310459891.6A 2023-04-26 2023-04-26 Data monitoring method based on big data Withdrawn CN116486578A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310459891.6A CN116486578A (en) 2023-04-26 2023-04-26 Data monitoring method based on big data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310459891.6A CN116486578A (en) 2023-04-26 2023-04-26 Data monitoring method based on big data

Publications (1)

Publication Number Publication Date
CN116486578A true CN116486578A (en) 2023-07-25

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CN202310459891.6A Withdrawn CN116486578A (en) 2023-04-26 2023-04-26 Data monitoring method based on big data

Country Status (1)

Country Link
CN (1) CN116486578A (en)

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