Intelligent safety helmet construction site mobile inspection method, system and device and medium

Abstract

The invention discloses an intelligent safety helmet construction site mobile inspection method, system and device and a medium, and the method comprises the steps: carrying out the inspection of a set route in an inspection task through a first object wearing device; according to the equipment, an acquisition device and a positioning device are arranged on a safety helmet, and an inspection task is obtained after identification and activation; acquiring real-time information through the acquisition device, and uploading the real-time information to a rear end; using AI identification to generate a check list, and pushing the check list to a third object; the second object can perform secondary auditing and modification on the checklist at the rear end; and the third object is used for uploading a rectification result to the first object aiming at the check list, and completing the closed loop of the check list after agreeing to rectify. More efficient and more accurate data acquisition is realized, personnel and data management are more efficient, early warning of potential safety hazards can be realized, the whole billing process is fully automatic by utilizing the AI technology, human errors are reduced, and the working efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction site supervision, and in particular to a method, system, device and medium for mobile inspection of construction sites using an intelligent safety helmet. Background Art

[0002] In the current field of construction site supervision, although technology has improved, supervisors have begun to use mobile devices to take photos on site and issue orders, and engineering units can also upload rectification status through mobile terminals, getting rid of the timeliness and other problems brought about by traditional paper-based ordering. Although the popularization of these technologies has improved work efficiency to a certain extent, it has also brought many new problems:

[0003] 1. There is a lot of subjectivity in the issuance of orders by supervisors, and it cannot be ensured that every supervisor can objectively issue rectification orders.

[0004] 2. Faced with complex scenarios, individuals are unable to make correct and complete analysis. There are large disagreements on some ambiguous points, which can easily lead to missed orders, and some materials are stacked unreasonably, making it impossible to make early warnings, which can lead to safety hazards later.

[0005] 3. It is impossible to fully grasp the track of supervisors, ensure that supervisors have visited every important point on the construction site, and prevent supervisors from being lazy. In addition, existing mobile devices cannot achieve accurate indoor positioning. Therefore, the exact track of supervisors cannot be seen.

[0006] In summary, it is particularly important to develop an AI-based smart helmet, which can automatically issue orders through image analysis using AI technology. At the same time, the device integrates indoor positioning functions, which can view the inspection trajectory of supervisors, thereby comprehensively improving the accuracy and efficiency of inspection and issuance of orders. Summary of the invention

[0007] In view of the above-mentioned problems, the present invention is proposed.

[0008] Therefore, the technical problems solved by the present invention are: the existing inspection methods are relatively objective; they cannot be comprehensively analyzed and are prone to omissions; and the inspection track cannot be checked.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for mobile inspection of construction sites using a smart safety helmet, comprising:

[0010] The first subject wears the device to perform inspection along a predetermined route in the inspection task; the device includes a collection device and a positioning device configured on a safety helmet, and obtains the inspection task after identification and activation;

[0011] Obtain real-time information through the acquisition device and upload it to the back end;

[0012] Using AI recognition, a checklist is generated and pushed to a third party; the second party can conduct a secondary review and modification of the checklist at the back end;

[0013] The third party uploads the rectification results of the inspection form to the first party, and completes the closed loop of the inspection form after agreeing to the rectification.

[0014] As a preferred solution of the mobile site inspection method for a smart safety helmet described in the present invention, the first object includes but is not limited to supervisors who perform inspection tasks.

[0015] As a preferred solution of the mobile site inspection method for a smart safety helmet described in the present invention, the second object includes but is not limited to a manager who inspects the first object in a back-end management system.

[0016] As a preferred solution of the method for mobile inspection of construction sites with a smart safety helmet described in the present invention, the third object includes but is not limited to the person actually in charge of the construction site supervised by the first object.

[0017] As a preferred solution of the method for mobile inspection of construction sites with a smart safety helmet according to the present invention, the safety helmet further comprises: the mobile terminal is connected to the safety helmet via Bluetooth, and after the connection is completed, the inspection task is activated after face recognition authentication;

[0018] The customized equipment is integrated into the safety helmet and connected to the AI ​​camera module, which can control the camera movement and adjust the shooting angle; at the same time, the inspection route of the supervisor is recorded through the positioning device.

[0019] As a preferred solution of the method for mobile inspection of construction sites using a smart safety helmet according to the present invention, a plurality of predetermined routes are stored in the mobile terminal, and a predetermined route for the current task is obtained by extraction.

[0020] As a preferred solution of the method for mobile inspection of construction sites with a smart safety helmet described in the present invention, the acquisition device is a high-definition camera and various sensors.

[0021] As a preferred solution of the method for mobile inspection of construction sites with a smart safety helmet described in the present invention, the real-time information includes real-time picture information and real-time data of various sensors.

[0022] As a preferred solution of the mobile inspection method for construction sites of intelligent safety helmets described in the present invention, the AI ​​recognition includes analyzing and making decisions from multiple dimensions of real-time data through AI;

[0023] At the same time, according to the path selection and the position of the construction location on the path, the swing angle of the screen in the wearable device of the first object is analyzed for abnormal behavior. AI recognizes the visual screen twice. The first time is to recognize whether there is an inspection object. If there is an inspection object, a second recognition is performed; if there is no inspection object, it is judged that the behavior of the first object is normal.

[0024] The second recognition includes recognizing a visual retention time on the inspection object image, and determining the first object according to the visual retention time.

[0025] As a preferred solution of the method for mobile inspection of construction sites using a smart safety helmet according to the present invention, the inspection sheet is a document recording detailed violations.

[0026] As a preferred solution of the mobile inspection method for construction sites of smart safety helmets of the present invention, the inspection form further includes that after the third object makes corrections to the inspection form, the third object uploads a photo of the corrections completed through the mobile terminal, and the backend sends a message to the first object;

[0027] If the first object agrees with the pushed content, the checklist closed loop is completed; if the first object rejects the pushed content, it returns to the third object and makes corrections again until it agrees.

[0028] On the other hand, an intelligent safety helmet construction site mobile inspection system is characterized by:

[0029] Data collection layer: Data collection is mainly done through smart helmets. The helmets have a built-in Android system and an integrated high-definition camera to capture inspection images and transmit them back to the platform layer in real time. At the same time, the smart helmets are integrated with various sensors for unified analysis and processing at the platform layer.

[0030] Platform layer: The smart helmet transmits the captured image data and various sensor data to the platform layer, which uses AI technology, sensor data and historical data for comprehensive analysis to automatically issue inspection records and train the AI ​​model. It also stores image data and other information at the platform layer.

[0031] Presentation layer: The front-end presentation layer has a dedicated mobile terminal and a back-end management system. Supervisors use the mobile terminal to activate their helmets and start inspections, as well as subsequent approvals to check rectification status. Managers can view inspection sheets for each construction site, supervisors’ work trajectories, and video playback data in the back-end management system. The site manager uses the mobile terminal to view sheets that need rectification at the construction site, and uploads them to supervisors for review after rectification is completed.

[0032] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0033] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0034] Beneficial effects of the present invention: The intelligent safety helmet mobile inspection method for construction sites provided by the present invention can not only collect high-definition video images through the intelligent safety helmet, but also collect more data information such as positioning, temperature, humidity, PM2.5 and other information through sensors, so that the platform layer can analyze the current construction site situation from multiple dimensions, and exclude human subjective factors through AI and big data algorithms, conduct more objective and accurate data analysis, and automatically issue inspection orders, which can reduce the risks and hidden dangers caused by insufficient supervision. The data collected by the intelligent safety helmet and personnel management are centrally managed and applied at the platform layer, and relevant data can be quickly obtained for comprehensive analysis during data analysis. In the event of some sudden emergencies, it is also convenient for administrators to quickly check information and make decisions. For the placement of some dangerous items, combined with some environmental data such as temperature and PM2.5 collected by the current sensors, early warning of hidden dangers can be issued in advance to reduce the occurrence of accidents. The entire order opening process is fully automated by using AI technology, which reduces human errors and improves work efficiency. A lot of current data of the construction site is also collected during the inspection process, making the construction site supervision more intelligent. From the construction site to the supervisors, further supervision has been received. The supervisors' facial recognition and inspection track viewing can show whether the supervisors are lazy at work. In addition, through AI automatic identification and issuance of orders, the construction site can be supervised more strictly without missing any safety blind spots.

[0035] To sum up, the present invention is a major change to the traditional way of issuing inspection orders on construction sites. It has significantly improved work efficiency, inspection order accuracy, objectivity, etc. It is a high-tech, high-efficiency, high-quality productivity, and will play a greater role in the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0037] Figure 1 An overall flow chart of a method for mobile inspection of construction sites of an intelligent safety helmet provided by the first embodiment of the present invention;

[0038] Figure 2 A flowchart of a closed-loop inspection in a mobile site inspection method for an intelligent safety helmet provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0040] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides a method for mobile inspection of a construction site using an intelligent safety helmet, comprising:

[0041] S1: The first subject wears the device and performs inspection along a predetermined route in the inspection task.

[0042] Furthermore, the device includes a collection device and a positioning device configured on the safety helmet, and obtains the inspection task after identification and activation.

[0043] In this embodiment, the first object is a supervisor who performs inspection tasks, and the device he wears is a helmet. In an optional solution, the first object can also be a non-supervisory inspector, a smart drone or a robot dog, etc. Similarly, the device he wears can also be smart glasses or other portable smart devices.

[0044] What we want to say is that AI high-definition cameras are integrated into safety helmets, and multiple cameras are integrated to increase the viewing angle. When users inspect the construction site, they automatically collect information and transmit it back to the cloud for real-time analysis of hidden dangers. Various data sensors: such as temperature, humidity, and PM2.5 sensors, after data collection, are transmitted back to the cloud for comprehensive analysis, helping AI to analyze from multiple dimensions. For example, some materials are at risk of ignition if left in high-temperature places for a long time, which can help AI make better decisions.

[0045] Integrate the customized Android device into the hard hat and connect it to the AI ​​camera module to control the camera movement and adjust the shooting angle. The Android device also has functions such as indoor positioning, which can record the inspection route of the supervisor. The supervisor can connect to the hard hat Android device through the mobile terminal to control and activate the use of the hard hat.

[0046] The supervisor first turns on the safety helmet, opens the mobile terminal and connects to the safety helmet via Bluetooth, then activates and starts the inspection task after facial recognition authentication on the mobile terminal, and inspects while wearing the safety helmet according to the established route.

[0047] S2: Obtain real-time information through the collection device and upload it to the back end.

[0048] Furthermore, the images captured by the AI ​​camera in the safety helmet and the data collected by various sensors will be transmitted back to the cloud server in real time. AI will analyze situations where risks and hidden dangers exist and automatically issue inspection records.

[0049] S3: Use AI recognition to generate a checklist and push it to the third party; the second party can perform a secondary review and modification on the checklist at the back end.

[0050] In this embodiment, the second object is the manager who checks the first object in the back-end management system; the third object is the person actually in charge of the construction site supervised by the first object.

[0051] At the same time, according to the path selection and the position of the construction location on the path, the swing angle of the screen in the wearable device of the first object is analyzed for abnormal behavior, and AI recognizes the visual screen twice. The first time is to recognize whether there is an inspection object. If there is an inspection object, a second recognition is performed; if there is no inspection object, it is judged whether the behavior of the first object is normal or abnormal. The second recognition includes recognizing the visual retention time on the inspection object image, and judging the first object according to the visual retention time.

[0052] It is important to know that at the time of the first recognition, there are conditional constraints. If the conditional constraints are not met, it will be judged as abnormal behavior and recorded on the inspection sheet. The conditional constraints include that the key positions on the path (when generating the path, the part of the path where the object to be inspected may be marked. This part of the function can be achieved through the matching mechanism of the database. The database matches the real-time engineering content according to the position on the map, and matches whether there are objects that need to be inspected according to the engineering content) must be fully collected. That is, the scope of visual acquisition is determined, and on the map, the visual scan area is analyzed according to the scope of the visual acquisition and the swing angle of the device worn at each position. If the key position is completely scanned, the constraint is met, otherwise it is not met.

[0053] It should also be said that through two recognitions, the degree of simplicity of the recognition algorithm can be simplified, and there is no need to directly generate recognition results, which can adapt to the adaptability of edge computing. The first recognition is used to determine whether there is an object that needs to be inspected. This recognition is very simple and can be completed through an extremely simple algorithm. The algorithm can be simplified without further recognition. Among them, the second recognition is a more complex recognition using AI. The algorithm can be simplified through simplified analysis logic "by only analyzing the retention time". This retention time is a variable variable. The time threshold is dynamically output by checking the number and importance of the object, where the output time threshold is proportional to the "number and importance of the object to be inspected".

[0054] The management backend can view the inspection records and rectification status of each construction site project, as well as the work status of supervisors, inspection routes, video playback and other data. Managers can see the route trajectory of supervisors in the backend, check whether the supervisors have done their job well and whether they are lazy, and view the playback of the shooting screen. At the same time, they can also view the inspection orders automatically issued by each construction site in the backend, and some orders with errors can be reviewed and modified for the second time.

[0055] Another thing to mention is that after the checklist is generated, a closed loop is formed between the supervisor and the person in charge. The management backend can view the playback during each inspection, which means that the management backend also supervises this closed loop process. In view of the above supervision, each time the next established path is generated, a constraint condition is added to the path selection: it must include the location of the checklist generated this time.

[0056] S4: The third party uploads the rectification results of the inspection form to the first party, and completes the closed loop of the inspection form after agreeing to the rectification.

[0057] After the inspection team issues an inspection form, it will be pushed to the person in charge of the construction site. The details of the inspection form can be viewed on the mobile terminal to see any non-compliant areas. After the rectification is completed, photos of the rectification can also be uploaded through the mobile terminal. After completion, the backend will send a message to the supervisor.

[0058] After receiving the push notification, the supervisor can check the rectification status of the construction site on the mobile phone and can agree or reject it. If he agrees, the checklist is closed. If he rejects, he will continue to repeat the rectification steps until he agrees.

[0059] The complete closed-loop process is as follows: Figure 2 As shown in the figure, take the rectification of the construction site as an example. After the supervisor wears the device, he starts the inspection and generates a checklist through AI. After passing through the management personnel, it is pushed to the person in charge of the construction site. After the person in charge completes the rectification, he submits it to the supervisor. If the supervisor agrees, the closed loop is completed. If not, it returns to the rectification.

[0060] Embodiment 2 is an embodiment of the present invention, which provides a smart safety helmet mobile site inspection system, which includes:

[0061] Data collection layer: Data collection is mainly carried out through smart helmets. The helmets have built-in Android systems and are integrated with hardware such as high-definition cameras. The high-definition cameras are used to capture inspection images and transmit them to the platform layer in real time. At the same time, the smart helmets are integrated with various sensors, such as precise indoor positioning, which can see a person's complete walking trajectory, and can also collect current temperature, PM2.5 and other conditions for unified analysis and processing at the platform layer.

[0062] Platform layer: The smart helmet transmits the captured image data and various sensor data to the platform layer. The platform layer uses AI technology, sensor data and historical data for comprehensive analysis to automatically issue inspection records. The AI ​​model is trained in this regard to continuously improve speed and accuracy. At the same time, the image data and other information are also stored at the platform layer for easy viewing and playback later.

[0063] Presentation layer: The front-end presentation layer mainly includes a dedicated mobile terminal and a back-end management system. Supervisors use the mobile terminal to activate their helmets and start inspections, as well as subsequent approvals to check rectification status. Managers can view inspection sheets for each construction site, as well as supervisors’ work trajectories, video playbacks and other data in the back-end management system. The site manager uses the mobile terminal to view sheets that need rectification at the construction site, and uploads them to supervisors for review after rectification is completed.

[0064] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0065] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0066] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0067] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0068] Example 3 is an embodiment of the present invention, which provides a method for mobile inspection of construction sites using an intelligent safety helmet. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0069] The experimental scene is a construction site, which is divided into four inspection areas, A, B, C, and D. Each area is configured with different environmental conditions to simulate the complex actual construction site environment. The experimental subjects include a supervisor (first subject), a back-end manager (second subject), and a construction site manager (third subject). The experiment verifies the superiority of the present invention by comparing the inspection efficiency, accuracy, and closed-loop feedback duration of the traditional manual inspection and the method of the present invention.

[0070] Experimental preparation:

[0071] Smart helmet configuration: Installed AI high-definition cameras (1 120° wide-angle camera, 2 180° fisheye cameras), integrated temperature and humidity sensors, PM2.5 sensors, and customized Android devices.

[0072] Experimental environment construction: Four typical safety hazards are set up in each inspection area:

[0073] Zone A: Too high temperature (simulating the risk of equipment overheating).

[0074] Area B: PM2.5 concentration exceeds the standard (simulating the risk of excessive dust).

[0075] Area C: Non-compliant stacking of materials (simulating the risk of items falling).

[0076] Area D: Inspection blind spots (examining the coverage capabilities of multiple cameras).

[0077] Data collection method: Compare traditional manual inspection records with smart helmet inspection records.

[0078] Evaluation Metrics: Risk and hidden danger identification rate (%) Average inspection time (minutes) Data upload and analysis time (seconds) Checklist generation accuracy (%) Closed-loop feedback completion time (hours) Experimental implementation process:

[0079] Traditional inspection: Two site supervisors will be divided into groups and carry record sheets to inspect each area, record any hidden dangers found, and pass the records to the back end to complete the generation and push of inspection sheets.

[0080] Smart helmet inspection: Supervisors wear smart helmets, turn on the helmets and connect to the mobile terminal via Bluetooth, activate the task, and inspect each area in turn along the designated route. During the inspection, AI cameras and sensors collect data in real time, upload it to the cloud for analysis via the 4G network, and the backend generates a checklist and pushes it to managers and site managers.

[0081] Rectification and closed loop: The site manager completes the rectification according to the inspection list, uploads the rectification results through the mobile terminal, and feedback is given to the supervisor after back-end review to complete the closed loop.

[0082] The hidden danger recognition rate of smart helmets reached over 90%, which is 22%-27% higher than that of traditional inspections. This is due to the multi-angle capture of AI cameras and the high sensitivity of sensors, which can detect hidden dangers that are missed by humans. The average duration of smart inspections has been reduced by about 40%. Traditional inspections require manual recording and analysis one by one, while smart devices realize real-time data collection and cloud analysis, greatly shortening the inspection time. The data upload time has been reduced from 5 minutes for traditional methods to within 30 seconds for smart inspections, indicating that the integration of customized Android devices has optimized communication efficiency. The accuracy of the checklists generated by the smart inspection solution has increased to 98%, effectively reducing the subjective errors and information omissions of manual analysis. The closed-loop duration of smart inspections is shortened by more than 60% compared with traditional methods, proving that the efficiency of information flow has been greatly improved during the rectification stage.

[0083] In summary, the experimental data fully demonstrates the advantages of the present invention in terms of efficiency, accuracy and overall closed-loop process optimization. The intelligent helmet inspection solution not only makes up for the shortcomings of traditional manual inspections, but also significantly improves the efficiency of hidden danger identification and rectification through AI multi-dimensional analysis, especially in complex scenarios, and has significant creativity and practicality.

[0084] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for mobile inspection of construction sites using a smart safety helmet, characterized in that: include: The first subject wears the device to perform inspection along a predetermined route in the inspection task; the device includes a collection device and a positioning device configured on a safety helmet, and obtains the inspection task after identification and activation; Obtain real-time information through the acquisition device and upload it to the back end; Using AI recognition, a checklist is generated and pushed to a third party; the second party can conduct a secondary review and modification of the checklist at the back end; The third party uploads the rectification results of the inspection form to the first party, and completes the closed loop of the inspection form after agreeing to the rectification.

2. The method for mobile inspection of a smart safety helmet on construction site according to claim 1, characterized in that: The first object includes, but is not limited to, supervisors who perform inspection tasks.

3. The method for mobile inspection of a construction site using an intelligent safety helmet as claimed in claim 1, characterized in that: The second object includes, but is not limited to, a manager who checks the first object in a back-end management system.

4. The method for mobile inspection of a smart safety helmet on construction site according to claim 1, characterized in that: The third object includes, but is not limited to, the person actually in charge of the construction site supervised by the first object.

5. The method for mobile inspection of a construction site using an intelligent safety helmet as claimed in claim 1 or 2, characterized in that: The helmet also includes a mobile terminal connected to the helmet via Bluetooth, and after the connection is completed, the inspection task is activated after face recognition authentication; The customized equipment is integrated into the safety helmet and connected to the AI ​​camera module, which can control the camera movement and adjust the shooting angle; at the same time, the inspection route of the supervisor is recorded through the positioning device.

6. The method for mobile inspection of a construction site using an intelligent safety helmet as claimed in claim 1, characterized in that: Multiple established routes are stored in the mobile terminal, and the established route for the current task is obtained by extraction.

7. The method for mobile inspection of a smart safety helmet on construction site according to any one of claims 1, 2, 3, 4 and 6, characterized in that: The acquisition device is a high-definition camera and various sensors.

8. The method for mobile inspection of a construction site using an intelligent safety helmet as claimed in claim 7, characterized in that: The real-time information includes real-time picture information and real-time data from various sensors.

9. The method for mobile inspection of a smart safety helmet on construction site according to any one of claims 1, 2, 3, 4, 6 and 8, characterized in that: The AI ​​recognition includes using AI to analyze and make decisions from multiple dimensions of real-time data; At the same time, according to the path selection and the position of the construction location on the path, the swing angle of the screen in the wearable device of the first object is analyzed for abnormal behavior. AI recognizes the visual screen twice. The first time is to recognize whether there is an inspection object. If there is an inspection object, a second recognition is performed; if there is no inspection object, it is judged that the behavior of the first object is normal. The second recognition includes recognizing a visual retention time on the inspection object image, and determining the first object according to the visual retention time.

10. The method for mobile inspection of a construction site using an intelligent safety helmet as claimed in claim 1, characterized in that: The inspection sheet is a document that records detailed violations.

11. The method for mobile inspection of a construction site of an intelligent safety helmet according to any one of claims 1, 2, 3, 4, 6, 8 and 10, characterized in that: The inspection form also includes that after the third subject makes corrections to the inspection form, the third subject uploads a photo of the corrections completed through the mobile terminal, and the backend sends a message to the first subject; If the first object agrees with the pushed content, the checklist closed loop is completed; if the first object rejects the pushed content, it returns to the third object and makes corrections again until it agrees.

12. An intelligent safety helmet mobile inspection system for construction sites, characterized by: Data collection layer: Data collection is mainly done through smart helmets. The helmets have a built-in Android system and an integrated high-definition camera to capture inspection images and transmit them back to the platform layer in real time. At the same time, the smart helmets are integrated with various sensors for unified analysis and processing at the platform layer. Platform layer: The smart helmet transmits the captured image data and various sensor data to the platform layer, which uses AI technology, sensor data and historical data for comprehensive analysis to automatically issue inspection records and train the AI ​​model. It also stores image data and other information at the platform layer. Presentation layer: The front-end presentation layer has a dedicated mobile terminal and a back-end management system. Supervisors use the mobile terminal to activate the helmet and start inspections, as well as review and approve the rectification status in the follow-up. Managers can view the inspection sheets for each construction site, the work trajectories of supervisors, and video playback data in the background management system; the construction site managers can view the sheets that need to be rectified on the construction site through the mobile terminal, and upload them to the supervisors for review after the rectification is completed.

13. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any method as claimed in claims 1-11 when executing the computer program.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

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