CN116311729A - AI-based power grid infrastructure site safety management system - Google Patents
AI-based power grid infrastructure site safety management system Download PDFInfo
- Publication number
- CN116311729A CN116311729A CN202211590698.8A CN202211590698A CN116311729A CN 116311729 A CN116311729 A CN 116311729A CN 202211590698 A CN202211590698 A CN 202211590698A CN 116311729 A CN116311729 A CN 116311729A
- Authority
- CN
- China
- Prior art keywords
- construction
- safety
- power grid
- site
- monitoring
- 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
Classifications
-
- 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
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
- G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention provides an AI-based power grid construction site safety management system, which is characterized in that safety helmets, construction clothes and safety belts of constructors are numbered by two-dimension codes, a power grid construction project working scene is used as a construction work photo to be input into a server, a power grid construction project safety civilization construction standard database is respectively established, two-dimension codes of the construction helmets, the construction clothes and the safety belts are input into the standard database, video monitoring equipment of a construction site takes pictures of real-time construction conditions and sends the pictures to the server, the server compares the received real-time field photo with the database in the power grid construction project safety civilization construction standard database, different areas are divided, data of the constructors are acquired through image acquisition equipment arranged on the construction site of the construction project, the identity information of the constructors is identified through the image acquisition equipment, and if at least one unsafe behavior exists, the intelligent safety management of the constructors is realized through sending an alarm to a management department.
Description
Technical Field
The invention relates to an AI-based power grid infrastructure site safety management system, and belongs to the field of power management.
Background
China is developing, the scale of the capital construction engineering is relatively large, but the safety management system is still lacking compared with the partially developed countries. The fact that the work of construction site constructors does not accord with safety regulations is a main factor causing construction safety problems, monitoring and management of engineering constructors are enhanced, recognition of environment abnormal changes is improved, and potential safety hazards are eliminated in an initial stage for guaranteeing the safety of the construction site. The artificial intelligence technology is applied to the building construction process to identify and monitor the environment, so that the bad behaviors of constructors can be found timely, the safety change condition of the construction site can be obtained, the task amount of the supervisory personnel can be reduced, and the supervision effect can be improved. Construction safety management personnel should try to improve engineering construction safety by using an artificial intelligent monitoring method, so that a management system needs to be designed for implementation.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide an AI-based power grid infrastructure site safety management system so as to solve the problems in the background art.
In order to achieve the above object, the present invention is realized by the following technical scheme: an AI-based power grid infrastructure site safety management system comprises the following steps:
s1: counting equipment, namely numbering two-dimensional codes on safety helmets, construction clothes and safety belts of constructors;
s2: the method comprises the steps of establishing a database, taking a power grid foundation engineering working scene as a foundation work photo to be input into a server, respectively establishing a power grid foundation engineering safety civilized construction standard database, and inputting two-dimension codes of a construction safety helmet, a construction suit and a safety belt into the standard database;
s3: the method comprises the steps of data acquisition, taking a picture of a real-time construction condition by video monitoring equipment of a construction site and sending the picture to a server, and comparing the received real-time field picture with a database in a power grid infrastructure engineering safety civilized construction standard library by the server to divide different areas;
s4: comparing the two-dimensional code obtained in the steps with the two-dimensional code in the real-time field photo, and judging whether the violation phenomenon exists according to the fact that whether the two-dimensional code is identical to the two-dimensional code in the real-time field photo.
Further, the two-dimensional code of the construction suit utilizes an artificial intelligence monitoring technology and a working suit recognition algorithm to recognize and monitor the wearing condition of the working suit, optimizes a working suit monitoring system, learns the normal wearing condition of the working suit under different conditions through deep learning of the artificial intelligence technology, and makes a corresponding model. In the subsequent monitoring and identifying process, monitoring staff, and finding out that staff wearing working clothes according to the standard does not carry out alarm prompt.
Further, in step S3, different areas need to be determined and forbidden areas, monitoring is performed in the area range where personnel are forbidden through the image acquisition equipment, the AI technology and the electronic perimeter recognition algorithm are used for inquiring, the AI technology can be used for automatically monitoring and recognizing a construction site, capturing pictures are recognized and stored in the AI technology, after the constructor is found to enter the area range illegally, the artificial intelligent system automatically pops out corresponding alarms, captures the pictures entered by the constructor, and uses the pictures as evidence to prove the system monitoring accuracy, and in the actual monitoring process, the engineering is monitored for different time and different objects according to different engineering requirements, so that the safety management effect of the construction site is improved.
Further, in step S4, the violation phenomenon includes fire, the smoke and fire condition existing in the field is identified by using AI technology, and when abnormal smoke or fire condition in the field is found, an alarm is given in time, and the management department is reported and an alarm is given.
Further, fire detection is improved through artificial intelligence technology and induction technology, AI system is adjusted, study and analysis of relevant contents such as smoke dynamic identification condition and flame development condition are enhanced, smoke conditions and the form of the initial stage of fire occurrence under different conditions are known, in the process of detecting the environment, the smoke conditions are compared with a database according to the actual conditions of smoke, once bad conditions are identified, accurate positioning and reporting processing are carried out in the construction community, and the smoke conditions are destroyed and processed at the initial stage of fire, so that the life safety of workers is ensured.
The invention has the beneficial effects that: according to the AI-based power grid infrastructure site safety management system, the image acquisition equipment arranged on the infrastructure construction site is used for acquiring the data of constructors, the image acquisition equipment is used for identifying the identity information of the constructors according to videos, and if at least one unsafe behavior exists, the management department is alerted to realize intelligent safety management of the constructors. The method can reduce the consumed manpower and material resources, thereby reducing the cost of safety management for constructors, improving the efficiency of safety management, avoiding the influence of human factors on the management process and improving the safety of management.
Detailed Description
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
The invention provides the technical scheme that: an AI-based power grid infrastructure site safety management system comprises the following steps:
s1: counting equipment, namely numbering two-dimensional codes on safety helmets, construction clothes and safety belts of constructors;
s2: the method comprises the steps of establishing a database, taking a power grid foundation engineering working scene as a foundation work photo to be input into a server, respectively establishing a power grid foundation engineering safety civilized construction standard database, and inputting two-dimension codes of a construction safety helmet, a construction suit and a safety belt into the standard database;
s3: the method comprises the steps of data acquisition, taking a picture of a real-time construction condition by video monitoring equipment of a construction site and sending the picture to a server, and comparing the received real-time field picture with a database in a power grid infrastructure engineering safety civilized construction standard library by the server to divide different areas;
s4: comparing the two-dimensional code obtained in the steps with the two-dimensional code in the real-time field photo, and judging whether the violation phenomenon exists according to the fact that whether the two-dimensional code is identical to the two-dimensional code in the real-time field photo.
The two-dimensional code of the construction suit utilizes an artificial intelligence monitoring technology and a working suit recognition algorithm to recognize and monitor the wearing condition of the working suit, optimizes a working suit monitoring system, learns the normal wearing condition of the working suit under different conditions through deep learning of the artificial intelligence technology, and makes a corresponding model. In the subsequent monitoring and identifying process, monitoring staff, and finding out that staff wearing working clothes according to the standard does not carry out alarm prompt.
In the step S3, different areas are required to be divided, forbidden areas are required to be determined, monitoring is carried out in the area range where personnel are forbidden through image acquisition equipment, an AI technology and an electronic perimeter recognition algorithm are used for inquiring, the AI technology can be used for automatically monitoring and recognizing a construction site, capturing pictures are recognized and stored in the AI technology, after the constructor is found to enter the area range illegally, an artificial intelligent system automatically pops out corresponding alarms, the pictures entered by the constructor are captured, the images are taken as evidence to prove the system monitoring accuracy, in the actual monitoring process, the engineering is monitored for different time and different objects according to different engineering requirements, and the safety management effect of the construction site is improved.
And S4, identifying smoke and fire conditions existing in the site by utilizing an AI technology, alarming in time when abnormal smoke or fire conditions appear in the site, and reporting to a management department and giving an alarm.
The fire detection is carried out through the promotion of artificial intelligence technique and sensing technique, adjusts AI system, strengthens the study and the analysis to smog dynamic identification condition and relevant content such as flame development condition, knows the condition of smog and the form in initial stage of fire occurrence under different circumstances, and in the in-process that detects the environment, compares it with the database according to the actual conditions of fireworks, in case discernment adverse condition, the building world carries out accurate location and reporting processing, breaks out and handles it in the conflagration initial stage, guarantee constructor life safety.
Examples: the method comprises the steps of carrying out two-dimension code numbering on a safety helmet, a construction suit and a safety belt of construction personnel, taking a work scene of a power grid foundation project as a foundation work photo and inputting the work scene of the power grid foundation project into a server, respectively establishing a construction standard database of the safety document of the power grid foundation project, inputting two-dimension codes of the construction safety helmet, the construction suit and the safety belt into the standard database, taking a picture of a real-time construction condition by video monitoring equipment of a construction site and sending the picture to the server, comparing the received real-time field photo with the database in the construction standard database of the safety document of the power grid foundation project, dividing different areas, determining forbidden areas by dividing the different areas, carrying out monitoring in a range of the forbidden personnel by using an image acquisition device, carrying out query by using an AI technology and an electronic perimeter recognition algorithm, carrying out automatic monitoring and recognition on the construction site, carrying out recognition and storage in the picture, automatically popping up a corresponding alarm after the fact that the constructor breaks down the construction personnel enter the range, carrying out the monitoring accuracy rate of the picture, carrying out two-dimension code recognition on the picture according to the fact that the field photo is corresponding to the project is detected, carrying out two-dimension code recognition on the situation in the field smoke and the fire disaster condition, and carrying out two-dimension code recognition on the fire disaster condition, and carrying out the two-dimensional smoke condition in real-time situation, and the fire condition is compared with the fire condition.
An intelligent safety monitoring system is constructed by utilizing an artificial intelligence technology, and the environment and people in the engineering construction site are monitored in an omnibearing manner without dead angles by utilizing a robot vision technology. And the intelligent identification is utilized to identify and control the monitoring content, so that unsafe behavior and environment existing in the construction process are found in time, and the prevention level of safety risks in the construction process is improved.
While the fundamental and principal features of the invention and advantages of the invention have been shown and described, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but may be embodied in other specific forms without departing from the spirit or essential characteristics 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.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (5)
1. The AI-based power grid infrastructure site safety management system is characterized by comprising the following steps:
s1: counting equipment, namely numbering two-dimensional codes on safety helmets, construction clothes and safety belts of constructors;
s2: the method comprises the steps of establishing a database, taking a power grid foundation engineering working scene as a foundation work photo to be input into a server, respectively establishing a power grid foundation engineering safety civilized construction standard database, and inputting two-dimension codes of a construction safety helmet, a construction suit and a safety belt into the standard database;
s3: the method comprises the steps of data acquisition, taking a picture of a real-time construction condition by video monitoring equipment of a construction site and sending the picture to a server, and comparing the received real-time field picture with a database in a power grid infrastructure engineering safety civilized construction standard library by the server to divide different areas;
s4: comparing the two-dimensional code obtained in the steps with the two-dimensional code in the real-time field photo, and judging whether the violation phenomenon exists according to the fact that whether the two-dimensional code is identical to the two-dimensional code in the real-time field photo.
2. The AI-based grid infrastructure site security management system of claim 1, wherein: the two-dimensional code of the construction suit utilizes an artificial intelligence monitoring technology and a working suit recognition algorithm to recognize and monitor the wearing condition of the working suit, a working suit monitoring system is optimized, the normal wearing condition of the working suit under different conditions is known through deep learning of the artificial intelligence technology, a corresponding model is manufactured, in the subsequent monitoring and recognition process, staff is monitored, and the staff wearing the working suit without the standard is found to carry out alarm prompt.
3. The AI-based power grid infrastructure site safety management system as claimed in claim 1, wherein in step S3, different areas are divided to determine forbidden areas, monitoring is performed in the area range where personnel are forbidden by using an image acquisition device, an AI technology and an electronic perimeter recognition algorithm are used for inquiring, the construction site can be automatically monitored and recognized by using the AI technology, pictures are captured and stored in the AI technology, after the constructor is found to enter the area range in a illegal way, the artificial intelligent system automatically pops out corresponding alarms, and captures the pictures entered by the constructor as evidence to prove the system monitoring accuracy, and in the actual monitoring process, different time and different objects are monitored for the engineering according to different engineering requirements, so that the safety management effect of the construction site is improved.
4. The AI-based power grid infrastructure site safety management system of claim 1, wherein the violation event in step S4 includes a fire, the smoke conditions existing in the site are identified by AI technology, and when abnormal smoke or fire conditions occur in the site are found, an alarm is given in time, and the management is reported and an alarm is given.
5. The AI-based grid infrastructure site security management system of claim 4, wherein: the fire detection is carried out through the promotion of artificial intelligence technique and sensing technique, adjusts AI system, strengthens the study and the analysis to smog dynamic identification condition and relevant content such as flame development condition, knows the condition of smog and the form in initial stage of fire occurrence under different circumstances, and in the in-process that detects the environment, compares it with the database according to the actual conditions of fireworks, in case discernment adverse condition, the building world carries out accurate location and reporting processing, breaks out and handles it in the conflagration initial stage, guarantee constructor life safety.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211590698.8A CN116311729A (en) | 2022-12-12 | 2022-12-12 | AI-based power grid infrastructure site safety management system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211590698.8A CN116311729A (en) | 2022-12-12 | 2022-12-12 | AI-based power grid infrastructure site safety management system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116311729A true CN116311729A (en) | 2023-06-23 |
Family
ID=86794831
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211590698.8A Pending CN116311729A (en) | 2022-12-12 | 2022-12-12 | AI-based power grid infrastructure site safety management system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116311729A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236691A (en) * | 2023-09-22 | 2023-12-15 | 思微科技(武汉)有限公司 | Edge side workstation for outdoor operation site management and control and application method thereof |
-
2022
- 2022-12-12 CN CN202211590698.8A patent/CN116311729A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236691A (en) * | 2023-09-22 | 2023-12-15 | 思微科技(武汉)有限公司 | Edge side workstation for outdoor operation site management and control and application method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113344326B (en) | System and method for identifying dynamic hidden danger and evaluating risk of special operation site | |
| CN111932709A (en) | Method for realizing violation safety supervision of inspection operation of gas station based on AI identification | |
| CN116311729A (en) | AI-based power grid infrastructure site safety management system | |
| CN112348731B (en) | Smart community real-time supervision system and method based on big data | |
| CN111506011A (en) | Construction safety monitoring method and device | |
| CN111652185A (en) | Safety construction method, system, device and storage medium based on violation behavior recognition | |
| CN109492548B (en) | Method for obtaining region mask picture based on video analysis | |
| CN113743256A (en) | Construction site safety intelligent early warning method and device | |
| CN113887445A (en) | Method and system for identifying standing and loitering behaviors in video | |
| CN115660297A (en) | Automatic AI early warning system and method for construction site safety | |
| CN114937237A (en) | Construction site safety monitoring method and system based on AI intelligent identification | |
| CN112381435A (en) | Gridding directional pushing management method for dynamic risk in hydropower station operation process | |
| CN107920224B (en) | Abnormity warning method, abnormity warning equipment and video monitoring system | |
| CN113378749B (en) | Visual inspection system based on big data analysis | |
| CN111274872B (en) | Video monitoring dynamic irregular multi-supervision area discrimination method based on template matching | |
| CN114092875A (en) | Operation site safety supervision method and device based on machine learning | |
| CN113506416A (en) | Engineering abnormity early warning method and system based on intelligent visual analysis | |
| CN116682162A (en) | Robot detection algorithm based on real-time video stream | |
| CN116246416A (en) | Intelligent analysis early warning platform and method for security protection | |
| CN115841730A (en) | Video monitoring system and abnormal event detection method | |
| CN115620192A (en) | Method and device for detecting wearing of safety rope in aerial work | |
| CN115019259A (en) | AI image recognition supervision method and system for intelligent mine | |
| CN114419475A (en) | Construction safety discrimination method and system based on video information behavior pattern recognition | |
| CN113191273A (en) | Oil field well site video target detection and identification method and system based on neural network | |
| CN112800896A (en) | Security emergency measure self-response method and system based on knowledge graph |
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 |