A remote real-time monitoring system for on-site construction scenes

Abstract

The present invention relates to the field of real-time monitoring, and discloses a remote real-time monitoring system for on-site construction scenes, including a video monitoring module, a sensor and environment monitoring module, an intelligent safety early warning module, an equipment monitoring module and a personnel positioning module; the video monitoring module collects image data of the construction site in real time through a high-definition camera and intelligent monitoring equipment; the sensor and environment monitoring module is used to deploy temperature and humidity, wind speed, air pressure, noise, and vibration environment monitoring sensors to collect environmental data of the construction site in real time; the intelligent safety early warning module combines artificial intelligence and machine learning technology to analyze the video and sensor data of the construction site in real time and automatically identify potential safety hazards; the equipment monitoring module monitors the operating status of construction machinery and equipment through the Internet of Things technology; the personnel positioning module tracks the location and behavior of construction personnel in real time through wearable devices, positioning sensors or RFID tags. The present invention has the advantage of improving construction management efficiency.

Description

Technical Field

[0001] The present invention relates to the field of real-time monitoring, and in particular to a remote real-time monitoring system for on-site construction scenes. Background Art

[0002] As the construction industry's requirements for construction management continue to increase, traditional construction site monitoring methods are facing more and more challenges. The construction site is a dynamic and complex environment involving a large number of personnel, equipment and materials, and there are many interdependent links that need to be coordinated. In the process of ensuring construction progress, quality and safety, real-time, comprehensive monitoring and data feedback become essential. Traditional construction site management methods usually rely on manual inspections and fixed camera monitoring, which has great limitations in many cases, especially in modern large-scale, multi-location parallel construction.

[0003] Traditional manual inspections mainly rely on regular inspections and on-site feedback from on-site managers, but due to the limitations of the number of personnel and working hours, it is difficult to achieve comprehensive coverage of each construction link. Especially in the case of multi-location and multi-type construction, manual inspections often cannot achieve full coverage, resulting in managers' inaccurate control of the construction process and prone to monitoring blind spots and dead ends. For example, in high-rise building projects, construction workers need to perform high-altitude operations, and manual inspections usually make it difficult to monitor every detail of high-altitude operations in real time. On-site managers are under great work pressure, and the frequency and coverage of inspections are limited, which may miss some key safety hazards or construction progress issues. Therefore, it is necessary to design a remote real-time monitoring system for on-site construction scenes to improve construction management efficiency. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a remote real-time monitoring system for on-site construction scenes, which has the advantage of improving construction management efficiency and solves the problems in the above-mentioned background technology.

[0006] (II) Technical solution

[0007] In order to achieve the above-mentioned purpose of improving construction management efficiency, the present invention provides the following technical solutions: a remote real-time monitoring system for on-site construction scenes, including a video monitoring module, a sensor and environment monitoring module, an intelligent safety warning module, an equipment monitoring module and a personnel positioning module;

[0008] The video monitoring module collects image data of the construction site in real time through high-definition cameras and intelligent monitoring equipment;

[0009] Preferably, the video surveillance module further includes a camera that collects on-site image data in real time and transmits it to a central monitoring platform via a wireless network or a wired network, deploys smart cameras or fixed cameras equipped with a pan / tilt head, and uses intelligent tracking technology to automatically adjust the camera's angle, focal length and position according to the dynamic situation of the construction site, so as to always track and clearly record the target.

[0010] The sensor and environment monitoring module is used to deploy temperature and humidity, wind speed, air pressure, noise, and vibration environment monitoring sensors to collect environmental data of the construction site in real time;

[0011] Preferably, the sensor and environmental monitoring module further includes deploying a variety of environmental sensors at the construction site, including temperature and humidity sensors, wind speed sensors, air pressure sensors, noise sensors, and vibration sensors, and using data analysis algorithms to perform real-time analysis of environmental data to identify abnormal environmental factors that affect construction safety, quality or progress.

[0012] The intelligent safety warning module combines artificial intelligence and machine learning technologies to analyze video and sensor data from the construction site in real time and automatically identify potential safety hazards;

[0013] Preferably, the intelligent safety warning module further includes image processing and target recognition of real-time video streams, using computer vision technology to identify people and equipment at the construction site, as well as important behaviors during the construction process, using image segmentation, motion detection and abnormal behavior recognition technology to determine whether construction personnel comply with safety regulations, and inputting video surveillance and sensor data analysis results into a trained deep learning model to automatically identify and classify safety hazards through the model.

[0014] The equipment monitoring module monitors the operating status of construction machinery and equipment through the Internet of Things technology, obtains equipment health status data in real time, and prevents equipment failure;

[0015] Preferably, the equipment monitoring module further includes using a machine learning model to analyze the equipment data after cleaning, evaluate the current health status of the equipment, combine historical data with real-time data, predict the future failure risk of the equipment, and automatically determine whether there is an equipment failure or abnormality based on the equipment health status assessment results combined with preset failure thresholds and risk levels.

[0016] The personnel positioning module tracks the location and behavior of construction personnel in real time through wearable devices, positioning sensors or RFID tags.

[0017] Preferably, the personnel positioning module further includes equipping the construction workers' work clothes or safety helmets with wearable devices, or using RFID tags in combination with positioning sensors for positioning, configuring a unique identification code for each device, regularly synchronizing and updating the collected positioning data, using timestamps and calibration algorithms to eliminate the impact of equipment errors or signal loss on positioning accuracy, and analyzing the construction workers' behavior patterns based on the real-time collected location information.

[0018] (III) Beneficial effects

[0019] Compared with the prior art, the present invention provides a remote real-time monitoring system for on-site construction scenes, which has the following beneficial effects:

[0020] The present invention combines artificial intelligence and machine learning technology through an intelligent safety early warning module to analyze the video and sensor data of the construction site in real time and automatically identify potential safety hazards; the equipment monitoring module monitors the operating status of construction machinery and equipment through the Internet of Things technology, obtains equipment health status data in real time, and prevents equipment failure; the personnel positioning module tracks the location and behavior of construction personnel in real time through wearable devices, positioning sensors or RFID tags. It has the advantage of improving construction management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Example 1

[0024] The present invention provides a technical solution: a remote real-time monitoring system for on-site construction scenes, including a video monitoring module, a sensor and environment monitoring module, an intelligent safety warning module, an equipment monitoring module and a personnel positioning module;

[0025] The video monitoring module collects image data of the construction site in real time through high-definition cameras and intelligent monitoring equipment;

[0026] The camera collects on-site image data in real time and transmits it to the central monitoring platform through a wireless or wired network. The system supports the transmission of high-definition video streams to ensure clear image quality and has anti-interference capabilities to adapt to harsh construction environments. It achieves high-definition and smooth video transmission to ensure that real-time image data at the construction site can be uploaded to the cloud platform or local monitoring system in a timely and stable manner for remote management personnel to view and analyze.

[0027] Deploy smart cameras or fixed cameras equipped with pan / tilt cameras, and use intelligent tracking technology to automatically adjust the camera's angle, focal length, and position according to the dynamic situation of the construction site, always tracking and clearly recording key targets. For example, when an abnormal situation occurs in a certain area, the camera will automatically zoom in and track the area in real time to ensure that the key images are fully recorded. Ensure that the key links of the construction site are always within the monitoring range, especially when it is necessary to track certain specific operations or emergencies. Intelligent tracking can quickly adjust the viewing angle to ensure efficient monitoring.

[0028] The sensor and environment monitoring module is used to deploy temperature and humidity, wind speed, air pressure, noise, and vibration environment monitoring sensors to collect environmental data of the construction site in real time;

[0029] Deploy a variety of environmental sensors at key locations on the construction site, such as high-altitude work areas, equipment operation areas, and dangerous areas, including temperature and humidity sensors, wind speed sensors, air pressure sensors, noise sensors, vibration sensors, etc., to ensure that each sensor is debugged and configured according to the actual situation on site, and that its sensitivity and measurement range meet the environmental change requirements of the construction site. Achieve comprehensive monitoring of various environmental factors on the construction site, provide real-time environmental data for construction management personnel, and promptly identify environmental changes that may affect construction progress and personnel safety.

[0030] Use data analysis algorithms to analyze environmental data in real time and identify abnormal environmental factors that affect construction safety, quality or progress. For example, excessive wind speed, extreme temperature and humidity changes, high noise levels or abnormal vibrations. The system performs real-time comparisons based on preset safety thresholds to determine whether there are abnormal conditions and generates alarm notifications. Automatic detection and early warning of environmental anomalies are achieved to identify potential construction risks in a timely manner. For example, high temperatures or strong winds may cause danger to construction workers working at heights, and abnormal noise or vibrations may affect equipment operation or construction quality.

[0031] The intelligent safety warning module combines artificial intelligence and machine learning technologies to analyze video and sensor data from the construction site in real time and automatically identify potential safety hazards;

[0032] Perform image processing and target recognition on real-time video streams, use computer vision technology to identify people and equipment on the construction site, as well as important behaviors during the construction process, and use image segmentation, motion detection, and abnormal behavior recognition technology to determine whether construction workers follow safety regulations, such as whether they wear safety helmets, whether they enter dangerous areas, and whether they perform irregular operations. Provide comprehensive video monitoring and intelligent analysis of construction sites, automatically detect and identify potential safety hazards, and reduce human omissions and delays. Be able to warn construction workers of unsafe behaviors in real time, such as not wearing safety equipment or working in an improper position.

[0033] The results of video surveillance and sensor data analysis are input into the trained deep learning model, and the model is used to automatically identify and classify safety hazards. For example, possible risks of high-altitude operations, electrical fire risks, mechanical injuries, etc. are identified. The system gives priority classification according to different types of safety hazards and automatically assesses the severity of the hazards. Accurately identify and classify safety hazards to help managers deal with different types of hazards in a targeted manner. Priority classification ensures that the most serious risks are dealt with first.

[0034] The equipment monitoring module monitors the operating status of construction machinery and equipment through the Internet of Things technology, obtains equipment health status data in real time, and prevents equipment failure;

[0035] Use machine learning models to analyze the data of cleaned equipment, evaluate the current health status of the equipment, and combine historical data with real-time data to predict the future failure risk of the equipment. For example, through parameters such as equipment temperature and vibration, evaluate whether the equipment may have problems such as overheating, wear, and failure. Intelligent evaluation of equipment can accurately determine whether the equipment has potential failure risks, predict the remaining life of the equipment, and take maintenance or replacement measures in advance to avoid equipment downtime or major failures.

[0036] The system automatically determines whether there is equipment failure or abnormality based on the equipment health status assessment results, combined with the preset fault threshold and risk level. Once the system detects abnormal data or failure risk, it immediately triggers an alarm notification, which includes SMS, email, APP push, on-site voice alarm, etc. It can achieve rapid detection and early warning of equipment failures, inform management personnel of potential equipment failures in a timely manner, and reduce construction delays or downtime caused by equipment failures.

[0037] The system presents the equipment's operating data and health status information to construction managers through a visual interface. The data display forms include real-time charts, trend curves, equipment health scores, etc., automatically generates equipment health reports, and provides daily, weekly or monthly equipment operation status summaries to help managers fully understand the equipment status. Providing intuitive and easy-to-understand equipment health information enables managers to quickly identify equipment anomalies, evaluate the current status of the equipment, and provide data support for decision-making.

[0038] The personnel positioning module tracks the location and behavior of construction personnel in real time through wearable devices, positioning sensors or RFID tags.

[0039] Equip the construction workers' work clothes or helmets with wearable devices, or use RFID tags combined with positioning sensors for positioning, and configure each device with a unique identification code so that the system can accurately identify and track the location of each construction worker. Accurately identify and locate each construction worker, ensuring real-time tracking of each worker on the construction site. By binding with the system, the device can accurately transmit positioning data to avoid loss or misidentification of personnel.

[0040] The collected positioning data is updated synchronously on a regular basis to ensure that all position data remains consistent. Timestamps and calibration algorithms are used to eliminate the impact of device errors or signal loss on positioning accuracy. The system uses filtering algorithms to smooth position data and reduce fluctuations caused by sensor errors, signal fluctuations, and other factors. This improves data accuracy and stability, avoids position deviations caused by sensor failures or signal interference, and ensures that the system can provide continuous and reliable positioning information.

[0041] The system analyzes the behavior patterns of construction workers based on the real-time location information collected. For example, it identifies the range of activities, duration of stay, and distribution of work areas of workers at the construction site. It combines the location of workers and sensor data to analyze whether the construction workers are in the designated area, whether they have entered a dangerous area, or whether they have stayed in a location that they should not stay in for a long time. By analyzing the behavior of construction workers in real time, it provides a comprehensive understanding of their activities. It automatically identifies irregular behaviors and issues warnings or takes corresponding measures in a timely manner.

[0042] The system supports deployment and adaptation in a variety of construction environments, including indoor, outdoor, underground and other different construction scenes. It selects appropriate positioning technology for deployment. The system is compatible with other construction management platforms and equipment, and supports joint application with video monitoring, equipment monitoring, environmental monitoring and other modules. It realizes seamless integration and multi-device collaboration in different construction environments, ensuring comprehensive coverage of personnel positioning and behavior monitoring at the construction site, and avoiding data loss or positioning errors in different environments.

[0043] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0044] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote real-time monitoring system for on-site construction scenes, characterized in that: It includes video monitoring module, sensor and environment monitoring module, intelligent safety warning module, equipment monitoring module and personnel positioning module; The video monitoring module collects image data of the construction site in real time through high-definition cameras and intelligent monitoring equipment; The sensor and environment monitoring module is used to deploy temperature and humidity, wind speed, air pressure, noise, and vibration environment monitoring sensors to collect environmental data of the construction site in real time; The intelligent safety warning module combines artificial intelligence and machine learning technologies to analyze video and sensor data from the construction site in real time and automatically identify potential safety hazards; The equipment monitoring module monitors the operating status of construction machinery and equipment through the Internet of Things technology, obtains equipment health status data in real time, and prevents equipment failure; The personnel positioning module tracks the location and behavior of construction personnel in real time through wearable devices, positioning sensors or RFID tags.

2. A remote real-time monitoring system for on-site construction scenes according to claim 1, characterized in that: The video surveillance module further includes a camera that collects on-site image data in real time and transmits it to a central monitoring platform via a wireless network or a wired network, deploys smart cameras or fixed cameras equipped with a pan / tilt head, and uses intelligent tracking technology to automatically adjust the camera's angle, focal length and position according to the dynamic situation of the construction site, so as to always track and clearly record the target.

3. A remote real-time monitoring system for on-site construction scenes according to claim 1, characterized in that: The sensor and environmental monitoring module further includes deploying a variety of environmental sensors at the construction site, including temperature and humidity sensors, wind speed sensors, air pressure sensors, noise sensors, and vibration sensors, and using data analysis algorithms to perform real-time analysis of environmental data to identify abnormal environmental factors that affect construction safety, quality or progress.

4. A remote real-time monitoring system for on-site construction scenes according to claim 1, characterized in that: The intelligent safety warning module further includes image processing and target recognition of real-time video streams, using computer vision technology to identify people and equipment at the construction site, as well as important behaviors during the construction process, using image segmentation, motion detection and abnormal behavior recognition technology to determine whether construction personnel comply with safety regulations, and inputting video surveillance and sensor data analysis results into a trained deep learning model to automatically identify and classify safety hazards through the model.

5. A remote real-time monitoring system for on-site construction scenes according to claim 1, characterized in that: The equipment monitoring module further includes using a machine learning model to analyze the equipment data after cleaning, evaluate the current health status of the equipment, combine historical data with real-time data, predict the future failure risk of the equipment, and automatically determine whether there is an equipment failure or abnormality based on the equipment health status assessment results, combined with preset failure thresholds and risk levels.

6. A remote real-time monitoring system for on-site construction scenes according to claim 1, characterized in that: The personnel positioning module further includes equipping the construction workers' work clothes or safety helmets with wearable devices, or using RFID tags in combination with positioning sensors for positioning, configuring a unique identification code for each device, regularly synchronizing and updating the collected positioning data, using timestamps and calibration algorithms to eliminate the impact of equipment errors or signal loss on positioning accuracy, and analyzing the construction workers' behavior patterns based on the real-time collected location information.

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