CN116781862A - Abnormal behavior detection system for automobile production line workers based on video monitoring - Google Patents
Abnormal behavior detection system for automobile production line workers based on video monitoring Download PDFInfo
- Publication number
- CN116781862A CN116781862A CN202310734543.5A CN202310734543A CN116781862A CN 116781862 A CN116781862 A CN 116781862A CN 202310734543 A CN202310734543 A CN 202310734543A CN 116781862 A CN116781862 A CN 116781862A
- Authority
- CN
- China
- Prior art keywords
- module
- sub
- staff
- video monitoring
- production line
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 71
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 48
- 206010000117 Abnormal behaviour Diseases 0.000 title claims abstract description 23
- 238000001514 detection method Methods 0.000 title claims abstract description 18
- 230000009471 action Effects 0.000 claims abstract description 81
- 238000003860 storage Methods 0.000 claims abstract description 30
- 230000002159 abnormal effect Effects 0.000 claims abstract description 25
- 238000012545 processing Methods 0.000 claims abstract description 20
- 238000013500 data storage Methods 0.000 claims abstract description 10
- 238000012790 confirmation Methods 0.000 claims description 12
- 238000005192 partition Methods 0.000 claims description 12
- 239000000523 sample Substances 0.000 claims description 10
- 239000003623 enhancer Substances 0.000 claims description 5
- 238000004220 aggregation Methods 0.000 claims description 4
- 230000002776 aggregation Effects 0.000 claims description 4
- 238000002372 labelling Methods 0.000 claims description 3
- 230000000903 blocking effect Effects 0.000 claims 1
- 238000005457 optimization Methods 0.000 abstract description 2
- 230000000875 corresponding effect Effects 0.000 description 9
- 230000006872 improvement Effects 0.000 description 7
- 230000006399 behavior Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 239000011248 coating agent Substances 0.000 description 3
- 238000000576 coating method Methods 0.000 description 3
- 238000000034 method Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000005507 spraying Methods 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 238000005520 cutting process Methods 0.000 description 2
- 238000011282 treatment Methods 0.000 description 2
- 238000003466 welding Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000001962 electrophoresis Methods 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003973 paint Substances 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 239000002966 varnish Substances 0.000 description 1
Landscapes
- General Factory Administration (AREA)
Abstract
The invention discloses an abnormal behavior detection system of an automobile production line worker based on video monitoring, which comprises an input storage system and a video monitoring system, wherein the input storage system comprises an action acquisition module, an information input module and a data storage module, and the video monitoring system comprises an image processing module, a comparison judging module, an intelligent switching module and an alarm timing module; according to the invention, through inputting the standard actions of staff operation of the production line, carrying out video monitoring and alarming reminding on the abnormal actions of staff in the daily production process based on the standard actions, the problem that batch products are unqualified or serious safety accidents caused by misoperation of the staff due to dozing at night is effectively avoided, the system safety is high, meanwhile, the production state of the production line can be monitored in real time according to the video monitoring, the product production process can be conveniently traced, the on-duty operation staff is automatically switched to monitor based on image recognition, and the standard actions of updating and recognition can be selected according to staff optimization adjustment, and the intelligent degree is high.
Description
Technical Field
The invention relates to the technical field of monitoring systems, in particular to an automobile production line worker abnormal behavior detection system based on video monitoring.
Background
The automobile production line comprises a stamping line, a welding line, a coating line, an assembly line and the like, wherein the stamping line is a first workshop of a main machine factory and is used for stamping materials such as iron plates and the like used by automobiles, and the equipment used is the most dangerous machinery of the production line; the welding line is the production line with the most complex process and highest automation degree in the whole automobile production line; the coating line comprises two workshops of electrophoresis and spraying, and three processing steps of intermediate coating, colored paint spraying and varnish spraying are carried out on the frame; assembling all parts of the automobile by an assembly line; and all the production lines are matched with each other to assemble the complete automobile.
Because the automobile production line can work at night, the staff of the production line can doze at night, the quality of the produced batch products is not up to standard if the staff is light, and serious production safety accidents are caused by the fact that the staff is injured by errors when heavy equipment is operated due to dozing, therefore, the invention provides an automobile production line staff abnormal behavior detection system based on video monitoring, and the system is used for solving the problems in the prior art.
Disclosure of Invention
Aiming at the problems, the invention aims to provide the automobile production line worker abnormal behavior detection system based on video monitoring, which is used for recording the standard actions of the operation of the production line workers, carrying out video monitoring and alarming reminding on the worker abnormal behaviors in the daily production process based on the standard actions, effectively avoiding unqualified or serious safety accidents of batch products caused by misoperation of workers due to doze at night, being high in system safety, simultaneously carrying out real-time monitoring on the production state of the production line according to the video monitoring, facilitating the tracing of the production process of the products, carrying out monitoring based on image identification and automatically switching on-duty operation workers, and also being high in intelligent degree according to the optimized adjustment of the workers to select the updated and identified standard actions.
In order to achieve the purpose of the invention, the invention is realized by the following technical scheme: the system comprises an input storage system and a video monitoring system, wherein the input storage system comprises an action acquisition module, an information input module and a data storage module, the action acquisition module is used for adjusting and acquiring an employee operation standard action based on a spherical multi-angle-adjustment monitoring probe, processing and recording the operation standard action, the operation standard action is monitored and observed and confirmed in the whole process of the production line length during acquisition, the information input module is used for inputting and storing basic information, operation gestures and scheduling information of the employee, the fluctuation threshold range is added to the outer ring of an image of the standard action gesture after the operation gestures are input so as to facilitate comparison and judgment of later monitoring images, and the data storage module is used for carrying out partition block storage and data real-time update on the input information, and the partition block storage is convenient for inquiring or rapid retrieval of corresponding information of the monitoring comparison system;
the video monitoring system comprises an image processing module, a comparison judging module, an intelligent switching module and an alarm timing module, wherein the image processing module is used for processing an obtained staff operation action image and a scene monitoring image on a post, cutting the scene monitoring image and intelligently identifying whether abnormal behaviors and abnormal behavior types exist or not, acquiring phenomenon audio data, the comparison judging module is used for comparing the processed image with standard actions which are acquired by a recording storage system and judging whether abnormal behaviors exist or not, the intelligent switching module is used for identifying and acquiring corresponding information for monitoring staff on a post, a monitoring probe is used for automatically identifying and identifying staff face information of the staff when the staff is on a post, and the alarm timing module is used for timely alarming when abnormal judgment information is given and timing notification and warning of offline rest staff and bundling aggregation phenomena.
The further improvement is that: the action acquisition module comprises an image acquisition sub-module, a quality detection sub-module and an authentication confirmation sub-module, wherein the image acquisition sub-module is used for acquiring images of a plurality of staff operation devices based on the automatic angle adjustment of a post monitoring probe, selecting proper images by staff and line length for confirmation, the quality detection sub-module is used for detecting and confirming whether the quality of the processed product is qualified or not when the images are acquired, carrying out quality detection and confirmation on the processed product when the images are acquired, marking the system on the corresponding action images for checking and selecting the line length, then carrying out noise removal and other treatments on the images, and the authentication confirmation sub-module is used for re-confirming the processed product by the line length and recording the qualified processed product as the staff operation standard action after authorized confirmation when the images are acquired.
The further improvement is that: the information input module comprises an information input sub-module, a staff table importing sub-module and a real-time updating sub-module, wherein the information input sub-module is used for inputting basic information of trained staff into the system, the basic information is data provided when the staff enters the staff, the staff table importing sub-module is used for importing staff tables into the system, the staff tables are imported into the system after being adjusted by a line length arrangement, the real-time updating sub-module is used for automatically updating staff table scheduling staff in real time according to later-stage or temporary adjustment, change information is input by the line length when staff shift adjustment occurs in the later-stage, the system is automatically replaced, and the monitoring probe is used for automatically identifying staff information to be replaced and automatically counting the staff information to the staff table in a post-stage period when staff is replaced, so that performance assessment is facilitated.
The further improvement is that: the data storage submodule comprises a partition storage submodule and a replacement update submodule, wherein the partition storage submodule is used for performing block division and classification storage on input and input employee basic information and working standard actions, the replacement update submodule is used for automatically selecting and inputting and updating own information and working labeling actions according to employees, updating the standard actions and automatically updating the employee basic information, and simultaneously sealing and newly-built file storage on files of employees who leave and are newly-entered.
The further improvement is that: the image processing module comprises an identification classification sub-module and a denoising enhancer sub-module, the identification classification sub-module is used for primarily identifying an acquired image and dividing the acquired image into an equipment operation action image and other images, the other images comprise production line dispute conflict phenomena, crowded pile phenomena, factory illegal behaviors and the like, and the denoising enhancer sub-module is used for identifying and confirming abnormal behavior types again for other images after denoising enhancement processing is carried out on the identified image.
The further improvement is that: the comparison judging module comprises a data calling sub-module, an action judging sub-module and a violation judging sub-module, wherein the data calling sub-module is used for calling standard action images recorded by corresponding staff from a recording storage system, the action judging sub-module is used for judging whether the action images obtained after the real-time acquisition are abnormal action or not after the comparison with the standard actions, alarming and reminding the abnormal actions in time, and the violation judging sub-module is used for judging whether the abnormal action actions of the violations exist or not after the identification of other processed pictures, if yes, warning and scattering are carried out, and a line length is checked according to the monitoring after the fact to confirm that the cause is punishment.
The further improvement is that: the intelligent switching module comprises a face recognition sub-module and a monitoring updating sub-module, wherein the face recognition sub-module is used for recognizing face information of workers of the workers when the workers are on duty and performing recognition switching of operation behaviors, and the detection updating sub-module is used for automatically calling operation standard actions of the workers to perform real-time monitoring after recognizing the face information of the workers.
The further improvement is that: the alarm timing module comprises an abnormal alarm sub-module, a timing monitoring sub-module, an off-duty timing sub-module and a remote reminding sub-module, wherein the abnormal alarm sub-module is used for carrying out alarm reminding when an on-duty operator is abnormal and has illegal actions due to dozing, timely informing that the on-duty operator is going to order, enabling staff to rest for a period of time by a line length arrangement, and then putting the staff into operation again, the timing monitoring sub-module is used for carrying out timing video on illegal actions, the off-duty timing sub-module is used for timing off-duty personnel rest time when the off-duty timing time is replaced, and the remote reminding sub-module is used for reminding and simultaneously carrying out remote notification on the line length of the production line to look over when the alarm reminding is carried out on the production line through a factory mobile phone APP according to the off-duty timing time.
The beneficial effects of the invention are as follows: according to the invention, through inputting the standard actions of staff operation of the production line, carrying out video monitoring and alarming reminding on the abnormal actions of staff in the daily production process based on the standard actions, the problem that batch products are unqualified or serious safety accidents caused by misoperation of the staff due to dozing at night is effectively avoided, the system safety is high, meanwhile, the production state of the production line can be monitored in real time according to the video monitoring, the product production process can be conveniently traced, the on-duty operation staff is automatically switched to monitor based on image recognition, and the standard actions of updating and recognition can be selected according to staff optimization adjustment, and the intelligent degree is high.
Drawings
FIG. 1 is a diagram of a system architecture of the present invention.
Detailed Description
The present invention will be further described in detail with reference to the following examples, which are only for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
According to the embodiment, as shown in fig. 1, the system for detecting abnormal behaviors of an automobile production line worker based on video monitoring comprises an input storage system and a video monitoring system, wherein the input storage system comprises an action acquisition module, an information input module and a data storage module, the action acquisition module is used for adjusting and acquiring the operation standard actions of workers based on a monitoring probe regulated by spherical multiple angles, processing and recording the actions, the whole process of the production line length is supervised and observed and confirmed during acquisition, the action acquisition module comprises an image acquisition sub-module, a quality detection sub-module and an authentication confirmation sub-module, the image acquisition sub-module is used for automatically adjusting angles based on the post monitoring probe, acquiring images of a plurality of workers operation equipment, selecting proper images by workers and line length to confirm, the quality detection sub-module is used for detecting and confirming whether the quality of the processed product is qualified or not when the images are acquired, carrying out quality detection and confirmation on the processed product when the images are acquired, the system marks the corresponding action images for line length checking and selecting, then carrying out denoising and other treatments on the images, and the authentication confirmation sub-module is used for inputting the operation standard actions again and confirming the processed product by the line length after the line length is qualified when the images are acquired;
the information input module is used for inputting and storing basic information of staff, operation gestures and scheduling information, the fluctuation threshold range is increased on the outer ring of an image of a standard action gesture after the operation gestures are input so as to facilitate comparison and judgment of later monitoring images, the information input module comprises an information input sub-module, a staff table importing sub-module and a real-time updating sub-module, the information input sub-module is used for inputting basic information of the trained staff into the system, the basic information is data provided by the staff when the staff enters the staff, the staff table importing sub-module is used for importing the staff table into the system, the staff table is imported into the system after the staff table is scheduled by a line length, the real-time updating sub-module is used for automatically updating staff scheduling staff in real time according to later or temporary adjustment, changing information is input by the line length when staff adjustment occurs in the later stage, the staff information is automatically identified by a monitoring probe when the staff takes the post-stage and the staff information is automatically counted on the staff table for the time period of taking the post-stage, and efficiency assessment is facilitated;
the data storage module is used for carrying out partition block storage and data real-time update on the input information, the partition block storage is convenient for a system to quickly acquire corresponding information during later inquiry or monitoring comparison, the data storage submodule comprises a partition storage submodule and a replacement update submodule, the partition storage submodule is used for carrying out partition block and classification storage on the input and input employee basic information and working standard actions, the replacement update submodule is used for automatically selecting and inputting and updating own information and working labeling actions according to the employee, and besides updating the standard actions, the basic information of the employee can be automatically updated, and meanwhile files of the employee who leaves and is newly input are sealed and newly built for file storage.
Specific staff enter standard actions of normal operation equipment of different staff as comparison images by a system after the staff are on duty for training, the corresponding staff's entered standard actions are called through inquiring staff shift time and compared with a series of actions when the staff operation equipment is produced on the current shift, whether the standard is judged, and then the standard actions are entered into the system for storage.
The video monitoring system comprises an image processing module, a comparison judging module, an intelligent switching module and an alarm timing module, wherein the image processing module is used for processing an acquired staff operation action image and a scene monitoring image on a post, cutting the scene monitoring image and intelligently identifying whether abnormal behaviors and abnormal behavior types exist or not, acquiring phenomenon audio data, the image processing module comprises an identification classifying sub-module and a denoising enhancer sub-module, the identification classifying sub-module is used for primarily identifying the acquired image and dividing the acquired image into an equipment operation action image and other images, the other images comprise a production line dispute conflict phenomenon, a crowded bundling phenomenon, factory illegal behaviors and the like, and the denoising enhancement sub-module is used for identifying the other images again after denoising enhancement processing is carried out on the identified images to confirm the abnormal behavior types;
the comparison judging module is used for comparing the processed image with the standard action which is acquired by the input storage system and giving a judgment to confirm whether the staff operation equipment has abnormal action, the comparison judging module comprises a data acquisition sub-module, an action judging sub-module and a violation judging sub-module, the data acquisition sub-module is used for acquiring the standard action image which is acquired by the corresponding staff from the input storage system, the action judging sub-module is used for comparing the processed action image with the standard action and judging whether the action is abnormal action or not, alarming and reminding the abnormal action in time and judging whether the abnormal action exists after identifying other processed pictures, and if yes, giving a warning and scattering to the abnormal action, and checking and confirming reason according to monitoring by a wire length after a matter;
when dozing, the action is greatly deviated, at the moment, the video monitoring and recognition is immediately carried out, the warning is carried out, the on-duty line length is timely notified through the APP, the on-duty line length is led to go to the order, and if necessary, the line length is used for arranging a top guard, so that staff can rest for 20 minutes and then put into work again.
Meanwhile, staff at all posts of the production line are monitored, so that the lazy phenomenon of the crowded pile is avoided, and the problem of collision among staff can be avoided.
The intelligent switching module is used for identifying the staff on duty and calling corresponding information to monitor, the monitoring probe automatically identifies the face information of the worker confirming the staff on duty, the intelligent switching module comprises a face identification sub-module and a monitoring updating sub-module, the face identification sub-module is used for identifying the face information of the worker on duty when the staff is on duty, the identification switching of operation behaviors is carried out, and the detection updating sub-module is used for automatically calling the operation standard action of the staff to monitor in real time after the face information of the worker on duty is identified;
the alarm timing module is used for timely alarming when abnormal judgment information is given and timing notification and warning are carried out on offline rest staff and the pile-up aggregation phenomenon, the alarm timing module comprises an abnormal alarm sub-module, a timing monitoring sub-module, an off-duty timing sub-module and a remote reminding sub-module, the abnormal alarm sub-module is used for alarming when abnormal operation actions occur and illegal actions occur due to doze of on-duty operators, timely notifying the on-duty staff to go to order, the staff is allowed to rest for a period of time by the line length arrangement, the timing monitoring sub-module is used for timing video of illegal actions, the off-duty timing sub-module is used for timing rest time of off-duty staff when the off-duty is replaced by the off-duty timing sub-module, and the remote reminding sub-module is used for reminding and simultaneously remotely notifying the line length of the production line to go to check when the alarm reminding occurs according to off-duty timing time through a factory mobile phone APP.
When the timing monitoring sub-module monitors through video monitoring, if three or more staff pile tying communication time exceeds 10 minutes, the staff pile tying communication time is judged to be pile tying aggregation, the system controls the abnormal alarm sub-module to carry out alarm reminding, meanwhile, the video monitoring stores image screenshot collected by pile tying staff and carries out face recognition to determine pile tying staff information, and finally, the images and the staff information are remotely sent to a remote communication device APP with the on-duty line length;
when the staff disputes or conflicts, the video monitoring is used for recording and monitoring and identifying the warning reminding, and when the drastic quarry or the overstress limb actions occur, the situation is also remotely sent to the remote communication equipment APP of the on-duty line length in time and is processed by the line length.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. An abnormal behavior detection system of an automobile production line worker based on video monitoring, which is characterized in that: the system comprises an input storage system and a video monitoring system, wherein the input storage system comprises an action acquisition module, an information input module and a data storage module, the action acquisition module is used for acquiring the operation standard action of staff based on the adjustment of a monitoring probe and processing and recording, the information input module is used for inputting and storing basic information, operation gesture and scheduling information of the staff, and the data storage module is used for carrying out partition block storage and data real-time update on the input information;
the video monitoring system comprises an image processing module, a comparison judging module, an intelligent switching module and an alarm timing module, wherein the image processing module is used for processing an obtained staff operation action image on a post and a scene monitoring image, the comparison judging module is used for comparing the processed image with a standard action called by a recording storage system and giving judgment, the intelligent switching module is used for identifying a post-replacing staff and calling corresponding information to monitor, and the alarm timing module is used for timely alarming and timing notification of offline rest staff and bundling aggregation phenomenon when abnormal judgment information is given.
2. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the action acquisition module comprises an image acquisition sub-module, a quality detection sub-module and an authentication confirmation sub-module, wherein the image acquisition sub-module is used for acquiring an image of staff operation equipment based on a post monitoring probe, the quality detection sub-module is used for detecting and confirming whether the quality of the processed product is qualified or not when the image is acquired, and the authentication confirmation sub-module is used for re-confirming the processed product by a line length and authorizing confirmation after the processed product is qualified when the image is acquired and inputting the qualified product into the staff operation standard action.
3. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the information input module comprises an information input sub-module, a table importing sub-module and a real-time updating sub-module, wherein the information input sub-module is used for inputting basic information of trained staff into the system, the table importing sub-module is used for importing staff tables into the system, and the real-time updating sub-module is used for automatically updating staff on the table according to later-stage or temporary adjustment.
4. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the data storage submodule comprises a partition storage submodule and a replacement update submodule, wherein the partition storage submodule is used for storing basic information of an employee which is input and standard actions of the work in a blocking and classifying mode, and the replacement update submodule is used for automatically selecting and inputting and updating own information and labeling actions of the work according to the employee.
5. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the image processing module comprises an identification classification sub-module and a denoising enhancer sub-module, wherein the identification classification sub-module is used for primarily identifying an acquired image and dividing the acquired image into an equipment operation action image and other images, and the denoising enhancer sub-module is used for carrying out denoising enhancement processing on the identified image and then carrying out identification confirmation on the other images.
6. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the comparison judging module comprises a data calling sub-module, an action judging sub-module and an offence judging sub-module, wherein the data calling sub-module is used for calling standard action images recorded by corresponding staff from a recording storage system, the action judging sub-module is used for judging whether abnormal action acts or not after comparing the action images obtained after real-time acquisition and the standard actions, and the offence judging sub-module is used for judging whether offence abnormal action acts or not after identifying other processed pictures.
7. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the intelligent switching module comprises a face recognition sub-module and a monitoring updating sub-module, wherein the face recognition sub-module is used for recognizing the face information of the workers when the workers are on the job, and the detection updating sub-module is used for automatically calling the operation standard action of the workers to conduct real-time monitoring after recognizing the face information of the workers.
8. The system for detecting abnormal behaviors of an automobile production line worker based on video monitoring according to claim 1, wherein the system comprises the following components: the alarm timing module comprises an abnormal alarm sub-module, a timing monitoring sub-module, an off-duty timing sub-module and a remote reminding sub-module, wherein the abnormal alarm sub-module is used for alarming and reminding on duty operators when abnormal operation actions occur and illegal actions occur due to doze, the timing monitoring sub-module is used for timing and video recording the illegal actions, the off-duty timing sub-module is used for timing rest time of off-duty personnel when the off-duty timing sub-module is used for reminding on the basis of off-duty timing time through a factory mobile phone APP and simultaneously checking the line length of a remote notification production line when the alarm reminding occurs on the production line.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310734543.5A CN116781862A (en) | 2023-06-20 | 2023-06-20 | Abnormal behavior detection system for automobile production line workers based on video monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310734543.5A CN116781862A (en) | 2023-06-20 | 2023-06-20 | Abnormal behavior detection system for automobile production line workers based on video monitoring |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116781862A true CN116781862A (en) | 2023-09-19 |
Family
ID=87989047
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310734543.5A Pending CN116781862A (en) | 2023-06-20 | 2023-06-20 | Abnormal behavior detection system for automobile production line workers based on video monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116781862A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117115755A (en) * | 2023-10-23 | 2023-11-24 | 科曼智能科技有限公司 | Power operation site violation monitoring alarm recognition system based on image recognition |
| CN117471033A (en) * | 2023-10-24 | 2024-01-30 | 济南趵突泉酿酒有限责任公司 | Brewing production monitoring method, system, terminal and computer readable storage medium |
-
2023
- 2023-06-20 CN CN202310734543.5A patent/CN116781862A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117115755A (en) * | 2023-10-23 | 2023-11-24 | 科曼智能科技有限公司 | Power operation site violation monitoring alarm recognition system based on image recognition |
| CN117115755B (en) * | 2023-10-23 | 2024-01-23 | 科曼智能科技有限公司 | Power operation site violation monitoring alarm recognition system based on image recognition |
| CN117471033A (en) * | 2023-10-24 | 2024-01-30 | 济南趵突泉酿酒有限责任公司 | Brewing production monitoring method, system, terminal and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116781862A (en) | Abnormal behavior detection system for automobile production line workers based on video monitoring | |
| KR102053619B1 (en) | Industrial Site Safety Management System | |
| CN111105047B (en) | Operation and maintenance monitoring method and device, electronic equipment and storage medium | |
| CN108833831A (en) | A kind of power construction intelligent safety monitor system | |
| CN100485558C (en) | Electrical power system safety operation intelligent monitoring device and monitoring method thereof | |
| JP2021517099A (en) | Methods and equipment for monitoring and managing the operation of loading docks and equipment | |
| CN109450098A (en) | Power regulation integral system warning information optimization method | |
| CN109996182B (en) | Positioning method, device and system based on combination of UWB positioning and monitoring | |
| CN111161541B (en) | Vehicle monitoring method, device and system and vehicle monitoring equipment | |
| CN112153345A (en) | On-site intelligent anti-violation management and control platform based on 5G application operation | |
| CN111325969A (en) | Vehicle safety supervision system based on big data analysis technology | |
| CN111061223A (en) | Intelligent management method for numerical control machine tool | |
| CN112651642A (en) | Hydraulic engineering field personnel safety management system based on multi-device perception | |
| CN115601905A (en) | Intelligent security alarm method and system for intelligent park | |
| CN110020791A (en) | A kind of product design method based on liability management | |
| CN112837456A (en) | Monitoring positioning and alarming system and method for chemical plant | |
| CN205427969U (en) | Wireless system of patrolling and examining | |
| CN117523799A (en) | Intelligent monitoring method and system for potential safety hazards | |
| CN112132990A (en) | Intelligent safety management and control system for risk workplace | |
| CN110988584A (en) | Intelligent monitoring and automatic control system for electric power system | |
| CN114815760A (en) | Safe production tracking and processing system and method | |
| CN113554834A (en) | Chemical industry park visual identification application system based on artificial intelligence technology | |
| CN113848861A (en) | Intelligent monitoring system and method based on Internet of things and electronic equipment | |
| CN112800896A (en) | Security emergency measure self-response method and system based on knowledge graph | |
| CN117576821A (en) | Electronic detonator factory workshop management system and method |
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 |