Construction site Internet of Things monitoring equipment group management tool based on AI

Abstract

The invention relates to the technical field of building construction site environment monitoring, in particular to an AI-based construction site Internet of Things monitoring equipment group management tool, which comprises an application layer, a platform layer, a network layer and an equipment layer, and is characterized in that the platform layer comprises a unified management platform, an AI analysis module and a data storage management module; the equipment layer comprises a movable camera, an unmanned aerial vehicle, a sensor module and personnel identification equipment; by integrating various AI technologies and IoT technologies, the functions of real-time monitoring, state detection, fault diagnosis, maintenance recording and the like of various monitoring devices are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of construction site environment monitoring, and in particular to an AI-based construction site Internet of Things monitoring equipment group management tool. Background Art

[0002] As the scale and complexity of modern construction continue to expand, the safety and management of construction sites have become an important concern. Traditional construction site management relies on manual inspections and fixed monitoring equipment, which cannot fully grasp the site dynamics in real time. This method is not only inefficient, but also prone to omissions and misjudgments. In order to improve management efficiency and safety, the Internet of Things (IoT) technology has been gradually introduced to construction sites to achieve intelligent monitoring and management through real-time perception and data transmission.

[0003] At present, when using construction site monitoring equipment, the existing monitoring system mainly relies on cameras and sensors in fixed positions, with a limited monitoring range and unable to flexibly respond to environmental changes. In addition, the alarm mechanism of the existing system is mostly based on simple threshold judgment, which is prone to false alarms or missed alarms and cannot accurately reflect the actual situation of the construction site. The existing monitoring system based on the Internet of Things also has defects in equipment management. There is a lack of a unified equipment management platform, and it is impossible to centrally manage and maintain monitoring equipment of various types and brands. Therefore, an AI-based construction site IoT monitoring equipment group management tool is proposed to facilitate the integration of multiple AI technologies and IoT technologies to achieve real-time monitoring, status detection, fault diagnosis and maintenance records of various monitoring equipment. Summary of the invention

[0004] In response to the problems in the prior art, the present invention provides an AI-based construction site IoT monitoring equipment group management tool, so as to realize functions such as real-time monitoring, status detection, fault diagnosis and maintenance recording of various monitoring equipment by integrating multiple AI technologies and IoT technologies.

[0005] The technical solution adopted by the present invention to solve its technical problem is an AI-based construction site IoT monitoring equipment group management tool, including an application layer, a platform layer, a network layer and a device layer, wherein the platform layer includes a unified management platform, an AI analysis module and a data storage management module;

[0006] The device layer includes movable cameras, drones, sensor modules and personnel recognition devices.

[0007] By adopting the above technical solutions, a real-time monitoring interface, an equipment management interface and an alarm information interface can be provided to realize centralized management and real-time monitoring. It can also perform intelligent analysis on video and sensor data, automatically identify abnormal behaviors and environmental changes, and movable cameras can monitor the construction site in real time and capture high-quality videos and images. Drones can regularly cruise the construction site and provide videos and data from a high-altitude perspective.

[0008] Specifically, the application layer includes an intelligent alarm system, an equipment detection and maintenance module, and a user interface module.

[0009] By adopting the above technical solutions, it is possible to comprehensively analyze multiple sensor data, take environmental factors and worker behavior into consideration, improve alarm accuracy, reduce false alarms and missed alarms, identify and solve potential problems in advance, reduce equipment downtime, and increase equipment service life.

[0010] Specifically, the sensor module includes a temperature sensor, a humidity sensor, a noise sensor and a vibration sensor.

[0011] By adopting the above technical solution, it is convenient to monitor the temperature changes at the construction site, the humidity conditions at the construction site, and the noise level at the construction site. Vibration sensors are installed at key structural parts to monitor the vibration conditions during the construction process.

[0012] Specifically, the personnel identification device includes an RFID tag and a wearable device.

[0013] By adopting the above technical solution, the location and status of construction workers can be tracked in real time to ensure their safety.

[0014] Specifically, the network layer includes a LoRaWAN network module, an edge computing node module and a data transmission management module.

[0015] By adopting the above technical solution, sensor data can be transmitted to the edge computing node module and the unified management platform, and preliminary processing and analysis of the data can be performed, reducing data transmission delays and improving response speed.

[0016] Beneficial effects of the present invention:

[0017] The AI-based construction site IoT monitoring equipment group management tool described in the present invention integrates multiple AI technologies and IoT technologies to achieve functions such as real-time monitoring, status detection, fault diagnosis and maintenance records of various monitoring equipment; for example, through deep learning algorithms, the system can automatically identify abnormal status of equipment and issue early warnings, which significantly improves the accuracy and timeliness of fault diagnosis. In addition, the system also has an adaptive learning function, which can continuously optimize monitoring strategies according to historical data and changes in the on-site environment, thereby improving the accuracy and reliability of monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0019] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0020] Figure 2 It is a schematic diagram of the application layer structure of the present invention;

[0021] Figure 3 It is a schematic diagram of the platform layer structure of the present invention;

[0022] Figure 4 It is a schematic diagram of the network layer structure of the present invention;

[0023] Figure 5 It is a schematic diagram of the device layer structure of the present invention;

[0024] Figure 6 It is a schematic diagram of the structure of the sensor module of the present invention;

[0025] Figure 7 It is a schematic diagram of the structure of the personnel identification device of the present invention;

[0026] In the figure: 1. Application layer; 101. Intelligent alarm system; 102. Equipment detection and maintenance module; 103. User interface module; 2. Platform layer; 201. Unified management platform; 202. AI analysis module; 203. Data storage management module; 3. Network layer; 301. LoRaWAN network module; 302. Edge computing node module; 303. Data transmission management module; 4. Device layer; 401. Movable camera; 402. Drone; 403. Sensor module; 4031. Temperature sensor; 4032. Humidity sensor; 4033. Noise sensor; 4034. Vibration sensor; 404. Personnel identification device; 4041. RFID tag; 4042. Wearable device. DETAILED DESCRIPTION

[0027] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0028] In order to facilitate the integration of multiple AI technologies and IoT technologies to achieve real-time monitoring, status detection, fault diagnosis and maintenance records of various monitoring equipment, such as Figure 1-5 As shown, the AI-based construction site IoT monitoring equipment group management tool described in the present invention includes an application layer 1, a platform layer 2, a network layer 3 and a device layer 4, wherein the platform layer 2 includes a unified management platform 201, an AI analysis module 202 and a data storage management module 203;

[0029] The device layer 4 includes a movable camera 401 , a drone 402 , a sensor module 403 and a personnel identification device 404 .

[0030] When in use, the unified management platform 201 can provide a real-time monitoring interface, a device management interface and an alarm information interface to achieve centralized management and real-time monitoring. The AI ​​analysis module 202 can intelligently analyze video and sensor data and automatically identify abnormal behaviors and environmental changes. The movable camera 401 of the equipment layer 4 can monitor the construction site in real time and capture high-quality video and images. The drone 402 can regularly cruise the construction site to provide video and data from a high-altitude perspective.

[0031] The unified management platform 201 is a data management platform that integrates all monitoring devices.

[0032] The movable camera 401 is a camera that can be moved around the construction site and is installed on a bracket whose position can be adjusted.

[0033] UAV 402 is a UAV equipped with a high-definition camera and multiple sensors.

[0034] For example, Figure 1 , Figure 2 As shown, the present invention also includes that the application layer 1 includes an intelligent alarm system 101, a device detection and maintenance module 102 and a user interface module 103.

[0035] When in use, the intelligent alarm system 101 can comprehensively analyze various sensor data, consider environmental factors and worker behavior, improve alarm accuracy, and reduce false alarms and missed alarms. The equipment detection and maintenance module 102 can identify and solve potential problems in advance, reduce equipment downtime, and increase equipment service life.

[0036] For example, Figure 6 As shown, the present invention also includes that the sensor module 403 includes a temperature sensor 4031 , a humidity sensor 4032 , a noise sensor 4033 and a vibration sensor 4034 .

[0037] When in use, the temperature sensor 4031 is used to monitor the temperature changes at the construction site, the humidity sensor 4032 is used to monitor the humidity conditions at the construction site, the noise sensor 4033 is used to monitor the noise level at the construction site, and the vibration sensor 4034 is installed at key structural locations to monitor the vibration conditions during the construction process.

[0038] For example, Figure 7As shown, the present invention also includes that the personnel identification device 404 includes an RFID tag 4041 and a wearable device 4042 .

[0039] When in use, the location and status of construction workers can be tracked in real time through RFID tags 4041 or wearable devices 4042 such as smart bracelets to ensure their safety.

[0040] For example, Figure 4 As shown, the present invention also includes that the network layer 3 includes a LoRaWAN network module 301, an edge computing node module 302 and a data transmission management module 303.

[0041] When in use, the sensor data can be transmitted to the edge computing node module 302 and the unified management platform 201 through the LoRaWAN network module 301. The edge computing node module 302 can perform preliminary processing and analysis of the data, reduce data transmission delays, and improve response speed.

[0042] When the present invention is used:

[0043] 1. Data collection:

[0044] The movable camera 401 and the drone 402 collect video data regularly, the sensor module 403 collects environmental parameter data in real time, and the personnel identification device 404 collects worker location data in real time;

[0045] 2. Edge computing and preliminary processing:

[0046] The data is transmitted to the edge computing node module 302 for preliminary processing and analysis, filtering useless data and extracting key information;

[0047] 3. Data transmission and integration:

[0048] The preliminarily processed data is transmitted to the unified management platform 201 through the LoRaWAN network module 301 to perform multi-source data fusion to form a comprehensive monitoring view;

[0049] 4. Intelligent analysis and alarm:

[0050] The AI ​​analysis module 202 performs deep learning and machine learning analysis on the fused data, automatically identifies abnormal behaviors and environmental changes, and triggers the intelligent alarm system 101 to perform intelligent alarms;

[0051] 5. Equipment management and maintenance:

[0052] The unified management platform 201 centrally manages all monitoring devices, monitors the health of the devices, updates firmware, performs fault diagnosis and maintenance records;

[0053] Predictive maintenance models analyze sensor data to predict equipment failures, perform maintenance in advance, and reduce equipment downtime.

[0054] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of the present invention is defined by the attached claims and their equivalents.

Claims

1. An AI-based construction site IoT monitoring equipment group management tool, characterized in that: The system comprises an application layer (1), a platform layer (2), a network layer (3) and a device layer (4), wherein the platform layer (2) comprises a unified management platform (201), an AI analysis module (202) and a data storage management module (203); The device layer (4) includes a movable camera (401), a drone (402), a sensor module (403) and a personnel identification device (404).

2. According to claim 1, an AI-based construction site IoT monitoring equipment group management tool is characterized in that: The application layer (1) comprises an intelligent alarm system (101), an equipment detection and maintenance module (102) and a user interface module (103).

3. According to claim 1, an AI-based construction site IoT monitoring equipment group management tool is characterized in that: The sensor module (403) includes a temperature sensor (4031), a humidity sensor (4032), a noise sensor (4033) and a vibration sensor (4034).

4. The AI-based construction site IoT monitoring equipment group management tool according to claim 1, characterized in that: The personnel identification device (404) includes an RFID tag (4041) and a wearable device (4042).

5. The AI-based construction site IoT monitoring equipment group management tool according to claim 1, characterized in that: The network layer (3) includes a LoRaWAN network module (301), an edge computing node module (302) and a data transmission management module (303).

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