CN114022920A - Wisdom garden fortune dimension system based on thing networking - Google Patents
Wisdom garden fortune dimension system based on thing networking Download PDFInfo
- Publication number
- CN114022920A CN114022920A CN202111057660.XA CN202111057660A CN114022920A CN 114022920 A CN114022920 A CN 114022920A CN 202111057660 A CN202111057660 A CN 202111057660A CN 114022920 A CN114022920 A CN 114022920A
- Authority
- CN
- China
- Prior art keywords
- information
- vehicle
- video
- matching
- face
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000006855 networking Effects 0.000 title description 3
- 238000012423 maintenance Methods 0.000 claims abstract description 14
- 238000000034 method Methods 0.000 claims description 29
- 230000010365 information processing Effects 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 8
- 230000006399 behavior Effects 0.000 claims description 3
- 238000013135 deep learning Methods 0.000 claims description 3
- 238000009434 installation Methods 0.000 claims description 3
- 230000001537 neural effect Effects 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 2
- 238000007726 management method Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000007306 turnover Effects 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Biology (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Artificial Intelligence (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Evolutionary Computation (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses an intelligent park operation and maintenance system based on the Internet of things, which relates to the technical field of park management.
Description
Technical Field
The invention belongs to the technical field of park management, and particularly relates to an intelligent park operation and maintenance system based on the Internet of things.
Background
At present, with the rapid development of the internet technology, the internet and an intelligent integrated management mode are combined in more and more fields to obtain a plurality of intelligent products, a smart park is one of the smart parks, and the smart park is various characteristic industrial parks and comprehensive industrial parks which take a new generation of information technology as a means and support information application and realize park infrastructure optimization, development and management refinement, functional service specialization and industrial development intelligence.
In reality, the garden is because every day's flow of people and vehicle flow are all bigger usually, huge flow of people and vehicle flow make people and the car of garden business turn over all more in a jumble, be difficult to manage, under this condition, the personnel or the vehicle that some illegal entering garden threaten to the safety in the garden more easily, how to manage and control personnel and the vehicle of garden business turn over, can monitor the inside safety in garden simultaneously, be the problem that we need to solve urgently, for this reason, now provide a wisdom garden fortune dimension system based on the thing networking.
Disclosure of Invention
The invention aims to provide an intelligent park operation and maintenance system based on the Internet of things.
The purpose of the invention can be realized by the following technical scheme: an intelligent park operation and maintenance system based on the Internet of things comprises a cloud platform, a database, an information input module, an image acquisition module, an information matching module, an information processing module and a track tracking module;
the database is used for establishing an information matching library, and the information matching library comprises a personnel information sub-library and a vehicle information sub-library;
the image acquisition module is used for acquiring face video information and vehicle video information;
the information processing module is used for processing the face video and the vehicle video acquired by the image acquisition module;
the information matching module is used for matching the personnel information with the vehicle information according to the information obtained by the information processing module;
and the track tracking module is used for tracking the tracks of the personnel and the vehicles in the park.
Further, the process of establishing the personnel information sub-library comprises the following steps: the basic information of the personnel is input into the system through the information input module, and a personnel information subset is generated according to the basic information of the personnel; rasterizing the picture of the front face of the person, and marking feature points on the rasterized picture; and generating a human face reference picture by performing neural deep learning on the feature points in the picture of the front face of the human face.
Further, the building process of the vehicle information sub-library comprises the following steps: vehicle information is input into the system through an information input module, and a vehicle information subset is generated according to the vehicle information; binding the driver information with the vehicle information, rasterizing a picture of the front face of the driver, and marking a feature point on the rasterized picture; and generating a vehicle information subset according to the acquired data, and sending the vehicle information subset to a vehicle information sub-library.
Further, the process of acquiring the face video information and the vehicle video information by the image acquisition module comprises the following steps: arranging a plurality of high-definition cameras at the outlet of the garden, the inlet of the garden and proper positions in the garden; through the high definition digtal camera in the exit in garden, acquire personnel's face video and the vehicle video that will get into the garden.
Further, the processing procedure of the information processing module comprises: analyzing the acquired face video and the acquired vehicle video frame by frame; marking video frames with face information in each frame of video in the face video; and marking the video frame with the vehicle information in each frame of video in the vehicle video, and simultaneously acquiring the time corresponding to the video frame.
Further, the matching process of the personnel information comprises the following steps: rasterizing a video frame with the face information; carrying out face feature point marking on the video frame subjected to rasterization processing, and matching the video frame of the marked face information with a face reference picture; determining whether the person has the authority to enter and exit the park according to the matching result, if the matching is successful, indicating that the person has the authority to enter and exit the park, and if the matching is unsuccessful, indicating that the person does not have the authority to enter and exit the park; according to the installation position of the high-definition camera, the position of a person in the park is marked, and meanwhile, the shooting time is recorded.
Further, the matching process of the vehicle information includes the steps of: rasterizing a video frame with the vehicle information; extracting vehicle information from the video frame of the rasterized vehicle information; and matching the vehicle information with the vehicle information subsets in the vehicle information sub-library in the database, and outputting a matching result.
Further, the process of trajectory tracking includes: establishing a garden area plane layout model and generating a garden area plane model map; marking the position of a high-definition camera installed in a park plane map; when people or vehicles appear in the picture shot by the high-definition camera, obtaining the information of the people and the information of the vehicles through the information matching module; acquiring the position of the high-definition camera and recording shooting time; and sequencing the positions of the personnel or the vehicles according to the shooting time, marking position points on the park plane model map, and finally connecting the position points according to the time sequence to generate a behavior track.
The invention has the beneficial effects that: the intelligent park management system is characterized in that a personnel information sub-library and a vehicle information sub-library are established in a database, high-definition cameras are arranged at an inlet and an outlet of a park, so that personnel information and vehicle information entering and exiting the park are acquired, the personnel information sub-library and the vehicle information sub-library in the database are matched with the personnel information sub-library and the vehicle information sub-library in the park, so that whether the personnel information and the vehicle information sub-library have the authority to enter and exit the park is judged, meanwhile, a track tracking module is further arranged, and the high-definition cameras are arranged at proper positions in the park, so that tracks of the personnel and the vehicles in the park are tracked.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of an intelligent park operation and maintenance system based on the internet of things.
Detailed Description
As shown in fig. 1, an intelligent park operation and maintenance system based on the internet of things comprises a cloud platform, a database, an information input module, an image acquisition module, an information matching module, an information processing module and a trajectory tracking module;
an information matching library is established in the database and comprises a personnel information sub-library and a vehicle information sub-library;
the establishment process of the personnel information sub-base comprises the following steps:
step R1: the basic information of the personnel is input into the system through the information input module, and a personnel information subset is generated according to the basic information of the personnel; the basic information of the personnel comprises name, age, gender, mobile phone number of real-name authentication and a face photo;
step R2: rasterizing the picture of the front face of the person, and marking feature points on the rasterized picture;
step R3: generating a human face reference picture by means of neural deep learning on the feature points in the picture of the front face of the human face;
step R4: binding the human face reference picture with the basic information of the personnel;
in the actual use process, after the basic information of the personnel is input into the system, the personnel has the authority of accessing the park, otherwise, the basic information of the personnel is not input into the system, and the authority of the personnel not accessing the park is represented;
the building process of the vehicle information sub-library comprises the following steps:
step C1: vehicle information is input into the system through an information input module, and a vehicle information subset is generated according to the vehicle information; the vehicle information comprises vehicle types, license plate numbers and driver information;
step C2: binding driver information and vehicle information, wherein the driver information comprises a driver name, a driver license, a vehicle driving license, a mobile phone number of the real-name authentication of the driver and a face front photo of the driver;
step C3: rasterizing a picture of the front face of the driver, and marking a feature point on the rasterized picture;
step C4: and generating a vehicle information subset according to the data acquired in the steps C1-C3, and sending the vehicle information subset to a vehicle information sub-library.
In the actual use process, after the driver information is input into the system, the driver has the authority of entering and exiting the park in a limited time and limited area, otherwise, when the driver information is not input into the system, the driver has no authority of entering and exiting the park; the time limit and the limit area are respectively in a specified time period and a specified area.
The image acquisition module is used for acquiring face video information and vehicle video information, and the specific acquisition process comprises the following steps:
step T1: arranging a plurality of high-definition cameras at the outlet of the garden, the inlet of the garden and proper positions in the garden;
step T2: acquiring a human face video and a vehicle video of a person about to enter a park through a high-definition camera at an outlet of the park;
step T3: and sending the face video and the vehicle video to an information processing module.
The information processing module is used for processing the face video and the vehicle video acquired by the image acquisition module, and the specific analysis process comprises the following steps:
step X1: analyzing the acquired face video and the acquired vehicle video frame by frame;
step X2: identifying whether face information exists in each frame of video in the face video, and marking the video frames with the face information;
step X3: identifying whether vehicle information exists in each frame of video in the vehicle video, marking the video frames with the vehicle information, and acquiring time corresponding to the video frames;
step X4: and sending the video frames of the marked face information and the marked vehicle information to an information matching module.
The information matching module is used for matching the personnel information and the vehicle information according to the information obtained by the information processing module, and the specific matching process comprises the following steps:
the personnel information matching process comprises the following steps:
step P1: rasterizing a video frame with the face information;
step P2: carrying out face feature point marking on the video frame subjected to rasterization processing, and matching the video frame of the marked face information with a face reference picture;
step P3: determining whether the person has the authority to enter and exit the park according to the matching result, if the matching is successful, indicating that the person has the authority to enter and exit the park, and if the matching is unsuccessful, indicating that the person does not have the authority to enter and exit the park;
step P4: according to the installation position of the high-definition camera, marking the position of a person in the park, simultaneously recording the shooting time, and sending the shooting time to the track tracking module;
the matching process of the vehicle information comprises the following steps:
step L1: rasterizing a video frame with the vehicle information;
step L2: extracting vehicle information from a video frame of the rasterized vehicle information, wherein the vehicle information comprises a vehicle type, a license plate number and driver information;
step L3: matching the vehicle information with the vehicle information subsets in the vehicle information sub-library in the database, and outputting a matching result;
step L4: when the matching result is failure, the vehicle is not allowed to enter the park; when the matching result is successful, acquiring the face information of the driver, and matching the face information of the driver with the driver information in the corresponding vehicle information subset; if the matching is successful, allowing the vehicle to enter the park, and if the matching is failed, the vehicle cannot enter the park.
The track tracking module is used for tracking the track of people and vehicles in the park, and the specific process comprises the following steps:
step Z1: establishing a garden area plane layout model and generating a garden area plane model map;
step Z2: marking the position of a high-definition camera installed in a park plane map;
step Z3: when a person or a vehicle appears in a picture shot by a high-definition camera, acquiring the person information and the vehicle information through an information matching module;
step Z4: acquiring the position of the high-definition camera and recording shooting time;
step Z5: when the same person or the same vehicle appears in different high-definition cameras, the positions of the person or the vehicle are sequenced according to shooting time, position point marking is carried out on the park plane model map, and finally the position points are connected according to the time sequence, so that a behavior track is generated.
The foregoing is illustrative and explanatory of the structure of the invention, and various modifications, additions or substitutions in a similar manner to the specific embodiments described may be made by those skilled in the art without departing from the structure or scope of the invention as defined in the claims. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise. In the embodiments provided by 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 there may be other divisions when the actual implementation is performed; 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.
It will also 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 (8)
1. An intelligent park operation and maintenance system based on the Internet of things is characterized by comprising a cloud platform, a database, an information input module, an image acquisition module, an information matching module, an information processing module and a trajectory tracking module;
the database is used for establishing an information matching library, and the information matching library comprises a personnel information sub-library and a vehicle information sub-library;
the image acquisition module is used for acquiring face video information and vehicle video information;
the information processing module is used for processing the face video and the vehicle video acquired by the image acquisition module;
the information matching module is used for matching the personnel information with the vehicle information according to the information obtained by the information processing module;
and the track tracking module is used for tracking the tracks of the personnel and the vehicles in the park.
2. The intelligent park operation and maintenance system based on the internet of things as claimed in claim 1, wherein the establishment process of the personnel information sub-base comprises: the basic information of the personnel is input into the system through the information input module, and a personnel information subset is generated according to the basic information of the personnel; rasterizing the picture of the front face of the person, and marking feature points on the rasterized picture; and generating a human face reference picture by performing neural deep learning on the feature points in the picture of the front face of the human face.
3. The IOT-based intelligent campus operation and maintenance system as claimed in claim 2, wherein said building process of said vehicle information sub-library comprises: vehicle information is input into the system through an information input module, and a vehicle information subset is generated according to the vehicle information; binding the driver information with the vehicle information, rasterizing a picture of the front face of the driver, and marking a feature point on the rasterized picture; and generating a vehicle information subset according to the acquired data, and sending the vehicle information subset to a vehicle information sub-library.
4. The intelligent park operation and maintenance system based on the internet of things as claimed in claim 3, wherein the process of acquiring the human face video information and the vehicle video information by the image acquisition module comprises the following steps: arranging a plurality of high-definition cameras at the outlet of the garden, the inlet of the garden and proper positions in the garden; through the high definition digtal camera in the exit in garden, acquire personnel's face video and the vehicle video that will get into the garden.
5. The IOT-based intelligent campus operation and maintenance system as claimed in claim 3, wherein the processing procedure of the information processing module comprises: analyzing the acquired face video and the acquired vehicle video frame by frame; marking video frames with face information in each frame of video in the face video; and marking the video frame with the vehicle information in each frame of video in the vehicle video, and simultaneously acquiring the time corresponding to the video frame.
6. The IOT-based intelligent campus operation and maintenance system as claimed in claim 5, wherein the matching process of the personnel information comprises: rasterizing a video frame with the face information; carrying out face feature point marking on the video frame subjected to rasterization processing, and matching the video frame of the marked face information with a face reference picture; determining whether the person has the authority to enter and exit the park according to the matching result, if the matching is successful, indicating that the person has the authority to enter and exit the park, and if the matching is unsuccessful, indicating that the person does not have the authority to enter and exit the park; according to the installation position of the high-definition camera, the position of a person in the park is marked, and meanwhile, the shooting time is recorded.
7. The intelligent park operation and maintenance system based on the internet of things as claimed in claim 1, wherein the matching process of the vehicle information comprises the following steps: rasterizing a video frame with the vehicle information; extracting vehicle information from the video frame of the rasterized vehicle information; and matching the vehicle information with the vehicle information subsets in the vehicle information sub-library in the database, and outputting a matching result.
8. The IOT-based intelligent campus operation and maintenance system as claimed in claim 1, wherein the tracking process comprises: establishing a garden area plane layout model and generating a garden area plane model map; marking the position of a high-definition camera installed in a park plane map; when people or vehicles appear in the picture shot by the high-definition camera, obtaining the information of the people and the information of the vehicles through the information matching module; acquiring the position of the high-definition camera and recording shooting time; and sequencing the positions of the personnel or the vehicles according to the shooting time, marking position points on the park plane model map, and finally connecting the position points according to the time sequence to generate a behavior track.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111057660.XA CN114022920A (en) | 2021-09-09 | 2021-09-09 | Wisdom garden fortune dimension system based on thing networking |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111057660.XA CN114022920A (en) | 2021-09-09 | 2021-09-09 | Wisdom garden fortune dimension system based on thing networking |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114022920A true CN114022920A (en) | 2022-02-08 |
Family
ID=80054248
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111057660.XA Pending CN114022920A (en) | 2021-09-09 | 2021-09-09 | Wisdom garden fortune dimension system based on thing networking |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114022920A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040199785A1 (en) * | 2002-08-23 | 2004-10-07 | Pederson John C. | Intelligent observation and identification database system |
| KR20170078910A (en) * | 2015-12-29 | 2017-07-10 | 서울과학기술대학교 산학협력단 | The vehicle entrance and exit management and crime prevention system based on high definition images |
| CN110807888A (en) * | 2019-09-24 | 2020-02-18 | 北京畅景立达软件技术有限公司 | Intelligent security method, system and storage medium for park |
| CN111815841A (en) * | 2020-09-09 | 2020-10-23 | 杭州绿城信息技术有限公司 | Wisdom garden situation perception system based on thing networking |
| CN113269091A (en) * | 2021-05-26 | 2021-08-17 | 广州瀚信通信科技股份有限公司 | Personnel trajectory analysis method, equipment and medium for intelligent park |
-
2021
- 2021-09-09 CN CN202111057660.XA patent/CN114022920A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040199785A1 (en) * | 2002-08-23 | 2004-10-07 | Pederson John C. | Intelligent observation and identification database system |
| KR20170078910A (en) * | 2015-12-29 | 2017-07-10 | 서울과학기술대학교 산학협력단 | The vehicle entrance and exit management and crime prevention system based on high definition images |
| CN110807888A (en) * | 2019-09-24 | 2020-02-18 | 北京畅景立达软件技术有限公司 | Intelligent security method, system and storage medium for park |
| CN111815841A (en) * | 2020-09-09 | 2020-10-23 | 杭州绿城信息技术有限公司 | Wisdom garden situation perception system based on thing networking |
| CN113269091A (en) * | 2021-05-26 | 2021-08-17 | 广州瀚信通信科技股份有限公司 | Personnel trajectory analysis method, equipment and medium for intelligent park |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110390262B (en) | Video analysis method, device, server and storage medium | |
| CN109902575B (en) | Anti-walking method and device based on unmanned vehicle and related equipment | |
| CN110942524B (en) | Cloud edge end cooperative parking management timing charging system and method based on block chain | |
| US10949687B2 (en) | Method and apparatus for outputting information | |
| DE102017122170A1 (en) | SYSTEM AND METHOD FOR PLACING SUBJECTIVE MESSAGES ON A VEHICLE | |
| CN103177436B (en) | Method and system for tracking object | |
| CN109635857A (en) | People's wheel paths method for monitoring and analyzing, device, equipment and storage medium | |
| CN109584130A (en) | Wisdom prohibition of drug socialized service system system | |
| CN112016520A (en) | AI-based traffic violation voucher generation method, device, terminal and storage medium | |
| CN108230669B (en) | Road vehicle violation detection method and system based on big data and cloud analysis | |
| CN111222375A (en) | Vehicle driving track generation method, system and server | |
| CN112233428B (en) | Traffic flow prediction method, device, storage medium and equipment | |
| Kamruzzaman et al. | AI-based computer vision using deep learning in 6G wireless networks | |
| Sutjarittham et al. | Monetizing parking IoT data via demand prediction and optimal space sharing | |
| CN114022920A (en) | Wisdom garden fortune dimension system based on thing networking | |
| Mingrone et al. | Smart urban electric transport system: An innovative real model | |
| KR20200033514A (en) | Vehicle accident video sharing method and apparatus | |
| CN114463685A (en) | Behavior recognition method and device, electronic equipment and storage medium | |
| CN112529116B (en) | Scene element fusion processing method, device and equipment and computer storage medium | |
| CN115272924A (en) | Treatment system based on modularized video intelligent analysis engine | |
| CN112289026B (en) | Vehicle route restoration method, equipment and medium | |
| CN111738884A (en) | Student behavior diagnosis and management method based on intelligent campus student position information | |
| CN113128294A (en) | Road event evidence obtaining method and device, electronic equipment and storage medium | |
| CN112887532B (en) | Traffic sealing control method and system combining image processing and geographic information | |
| CN114663862B (en) | Vehicle identification method, device, system and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |