Construction engineering site safety monitoring and early warning system

Abstract

The invention discloses a construction engineering site safety monitoring and early warning system, which comprises a high-precision sensor network, an intelligent video monitoring system, a data processing and analysis center, an early warning and decision support platform, an early warning and decision support platform, a mobile terminal application, a satellite positioning and geographic information system GIS integration and an internet of things gateway and edge computing device, the high-precision sensor network is composed of various sensors deployed at key parts of a building structure, construction equipment, a temporary support system and the like, and is used for monitoring the stress state and the deformation condition of a structure body and the operation parameters and the environment information of the equipment in real time; the data is transmitted to a data processing center through a low-power-consumption and long-distance wireless communication technology; according to the invention, a high-precision sensor network is constructed, real-time and accurate monitoring of information in multiple aspects such as key parts, construction equipment and environment of a building structure is realized, the condition of a construction site is comprehensively and accurately mastered, and monitoring dead angles and information omission are effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of building construction safety monitoring, and more specifically, to a building construction site safety monitoring and early warning system. Background Art

[0002] In the field of construction engineering, the safety of construction sites has always been a focus of attention. With the continuous expansion of the scale of construction projects, the increasing complexity of construction technology and the variability of the construction environment, traditional safety monitoring methods can no longer meet the high requirements of modern construction for safety management.

[0003] In the past, safety monitoring at construction sites mainly relied on manual inspections and simple equipment monitoring. Manual inspections are inefficient, have limited coverage, are prone to omissions, and cannot achieve real-time and continuous monitoring. Traditional equipment monitoring, such as single-type sensors, can often only obtain local and specific types of data, making it difficult to fully reflect the real situation of the construction site.

[0004] At the same time, there is a lack of effective means to monitor the behavior of construction workers. It is difficult to detect and correct behaviors such as improper wearing of safety helmets, improper use of safety belts, and illegal operations in a timely manner. In terms of the management of construction equipment, the prediction and maintenance of equipment failures often rely on regular inspections, and early warning and timely processing are impossible, increasing the risk of safety accidents caused by equipment failures.

[0005] In addition, in terms of data processing and analysis, traditional methods lack depth and comprehensiveness. It is impossible to effectively integrate and correlate multi-source heterogeneous data, such as sensor data, video data, construction plans, and engineering drawings, and it is difficult to discover potential safety risk patterns and patterns.

[0006] In terms of early warning mechanisms, traditional early warning methods are single and untimely, and cannot provide accurate and personalized early warning information according to different risk situations, resulting in low efficiency of emergency response. Moreover, there are hidden dangers in the security and credibility of data. Data is easily tampered or lost during collection, transmission and storage, affecting the accuracy and reliability of security assessments.

[0007] To sum up, in order to effectively respond to the increasingly complex safety challenges at construction sites, there is an urgent need for an innovative, integrated, and intelligent safety monitoring and early warning system that can achieve comprehensive, real-time, and accurate monitoring and early warning, and improve the safety of construction projects. Summary of the invention

[0008] 1. Technical issues to be solved

[0009] The purpose of the present invention is to provide a construction engineering site safety monitoring and early warning system to solve the problems raised in the above background technology.

[0010] 2. Technical solution

[0011] A construction site safety monitoring and early warning system, including a high-precision sensor network, an intelligent video monitoring system, a data processing and analysis center, an early warning and decision support platform, a mobile terminal application, satellite positioning and geographic information system GIS integration, and an Internet of Things gateway and edge computing equipment:

[0012] High-precision sensor network, composed of multiple sensors deployed at key parts of building structures, construction equipment, temporary support systems, etc., to monitor the stress state and deformation of the structure, as well as the operating parameters and environmental information of the equipment in real time, and transmit the data to the data processing center through low-power, long-distance wireless communication technology;

[0013] The intelligent video surveillance system, which is a combination of a high-definition panoramic camera and a high-definition zoom camera, is equipped with a deep learning-based intelligent video analysis module and a thermal imaging camera to achieve full coverage of the construction site, capture details of key areas, identify human behavior and objects, and monitor electrical equipment overheating and fire hazards;

[0014] The data processing and analysis center, based on cloud computing architecture, uses big data analysis technology and machine learning algorithms to deeply integrate and mine sensor data and video data, and establish a variety of security risk assessment models;

[0015] Early warning and decision support platform: when monitoring data exceeds the preset threshold or the risk assessment model determines that there is a high security risk, early warning information is issued in a timely manner through various means, and emergency decision support based on virtual reality VR and augmented reality AR technology is provided;

[0016] Mobile terminal applications make it convenient for relevant personnel to access the system through mobile devices anytime and anywhere to view real-time monitoring data, warning information, safety reports, etc.;

[0017] Satellite positioning is integrated with the Geographic Information System (GIS), and construction personnel and equipment are equipped with satellite positioning devices to combine positioning information with the GIS map of the construction site;

[0018] The IoT gateway and edge computing devices are responsible for data transmission and protocol conversion between the sensor network and the data processing center, and perform preliminary data processing and analysis on the side close to the data source.

[0019] Preferably, the sensors in the high-precision sensor network include pressure sensors, strain sensors, displacement sensors, acceleration sensors, inclination sensors, temperature sensors, humidity sensors, wind speed sensors and dust concentration sensors.

[0020] Preferably, the intelligent video analysis module in the intelligent video monitoring system can identify in real time the construction workers' helmet wearing, safety belt usage, illegal operating behaviors, crowd density and intrusion into dangerous areas.

[0021] Preferably, the safety risk assessment model established by the data processing and analysis center includes a structural stability analysis model, a construction equipment failure prediction model and a personnel behavior risk assessment model.

[0022] Preferably, the warning methods of the early warning and decision support platform include sound and light alarms, SMS notifications, mobile phone application push and on-site broadcasting.

[0023] Preferably, the mobile terminal application supports voice interaction and gesture operation.

[0024] Preferably, it also includes multimodal data fusion and correlation analysis technology, which comprehensively utilizes multi-source heterogeneous data such as sensor data, video data, positioning data, construction schedules, engineering drawings, etc. to explore potential safety risk laws and patterns.

[0025] Preferably, it also includes real-time prediction and early warning technology based on artificial intelligence, which uses deep learning and reinforcement learning algorithms to build a real-time safety risk prediction model, predict possible safety accidents in advance according to current monitoring data and construction status, and issue early warnings in a timely manner.

[0026] Preferably, it also includes personalized safety risk portraits and customized early warning technologies, establishing personalized safety risk portraits for each construction worker, construction equipment and construction area, and formulating customized safety thresholds and early warning strategies.

[0027] Preferably, blockchain technology is also included to encrypt and distribute the collection, transmission, storage and analysis processes of sensor data and video data to ensure the integrity, non-tamperability and traceability of the data.

[0028] Beneficial Effects

[0029] Compared with the prior art, the advantages of the present invention are:

[0030] By constructing a high-precision sensor network, the present invention realizes real-time and accurate monitoring of multiple aspects of information such as key parts of the building structure, construction equipment and environment, comprehensively and accurately grasps the conditions of the construction site, and effectively avoids monitoring blind spots and information omissions.

[0031] The present invention is equipped with an intelligent video surveillance system and combined with deep learning technology to identify various safety behaviors of construction personnel and abnormal conditions of equipment in real time, greatly improving the efficiency and accuracy of safety monitoring.

[0032] The present invention uses a data processing and analysis center based on a cloud computing architecture, big data analysis and machine learning algorithms, deep integration and mining of sensor data and video data, and establishes a variety of accurate security risk assessment models, providing strong support for accurately judging security risks.

[0033] Through the early warning and decision support platform, the present invention can issue early warning information in a variety of ways in a timely manner when the monitoring data exceeds the preset threshold or there is a high risk, and provide emergency decision support based on virtual reality (VR) and augmented reality (AR) technology to ensure that relevant personnel can respond quickly and make scientific decisions.

[0034] The present invention facilitates relevant personnel to access the system anytime and anywhere through mobile terminal applications, and timely obtain real-time monitoring data, early warning information and safety reports, etc., which greatly improves the convenience and flexibility of safety management.

[0035] The present invention integrates satellite positioning with the Geographic Information System (GIS), equips construction personnel and equipment with positioning devices and combines them with the GIS map of the construction site, thereby achieving accurate tracking and management of personnel and equipment and optimizing resource allocation.

[0036] The present invention ensures stable and efficient data transmission between the sensor network and the data processing center through the Internet of Things gateway and edge computing equipment, and performs preliminary processing and analysis near the data source, reducing the central processing burden and improving the real-time performance of the system.

[0037] The present invention uses multimodal data fusion and correlation analysis technology to comprehensively utilize multi-source heterogeneous data, explore potential security risk laws and patterns, and enhance the ability to predict and prevent security risks.

[0038] The present invention uses real-time prediction and early warning technology based on artificial intelligence, deep learning and reinforcement learning algorithms to build a real-time safety risk prediction model, predict possible safety accidents in advance, and change passive response to active prevention.

[0039] The present invention uses personalized safety risk profiling and customized early warning technology to tailor safety strategies for each construction worker, equipment and area, significantly improving the pertinence and effectiveness of early warnings.

[0040] The present invention introduces blockchain technology to encrypt and distribute the data collection, transmission, storage and analysis processes, ensuring the integrity, non-tamperability and traceability of the data, and enhancing the credibility and security of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic block diagram of the on-site safety monitoring and early warning system for a base construction project of the present invention. DETAILED DESCRIPTION

[0042] Example: See Figure 1 , a construction site safety monitoring and early warning system with rich and diverse components, covering high-precision sensor networks, intelligent video surveillance systems, data processing and analysis centers, early warning and decision support platforms, mobile terminal applications, satellite positioning and geographic information system GIS integration, as well as Internet of Things gateways and edge computing devices.

[0043] The high-precision sensor network consists of a variety of high-precision sensors carefully deployed in key locations such as key parts of the building structure, construction equipment, and temporary support systems. These sensors perform their respective duties, aiming to monitor the stress state of the structure in real time and accurately, and to capture even the slightest deformation; at the same time, they closely monitor the operating parameters of the construction equipment, such as power, speed, and energy consumption, and perceive the environmental information of the construction site, including temperature, humidity, wind speed, and dust concentration, in real time. In addition, with the help of low-power, long-distance advanced wireless communication technology, the massive data collected can be stably and efficiently transmitted to the data processing center to ensure the timeliness and integrity of the data.

[0044] The rules for high-precision sensor networks are:

[0045] A. Sensors should be deployed in key locations to ensure that important information can be fully monitored.

[0046] B. Different types of sensors should accurately monitor corresponding parameters according to their functions.

[0047] The algorithm used is:

[0048] The timeliness of data transmission can be compared with the preset maximum allowed time by the transmission time, for example: transmission time T<maximum allowed time T_max.

[0049] Data integrity can be measured by the ratio of the amount of successfully transmitted data to the total amount of collected data, for example: the amount of successfully transmitted data D_successful / the total amount of collected data D_total>integrity threshold P_min.

[0050] The intelligent video surveillance system, which perfectly combines high-definition panoramic cameras with high-definition zoom cameras, not only achieves all-round coverage of the construction site without blind spots, but also can capture clear details of key areas. In addition, the system is equipped with an intelligent video analysis module based on deep learning and a thermal imaging camera, which has powerful functions. It can identify the wearing of safety helmets by construction workers in real time to ensure that the construction workers' head protection is in place; accurately judge whether the use of safety belts is in compliance with regulations to ensure the life safety of workers working at heights; keenly detect the illegal operation of construction workers and correct them in time to avoid accidents; accurately monitor the density of personnel gathering to prevent safety hazards caused by excessive concentration of personnel; effectively identify intrusions in dangerous areas, issue alarms in time, and prevent dangerous behaviors.

[0051] The data processing and analysis center is built on a powerful cloud computing architecture, making full use of big data analysis technology and advanced machine learning algorithms to deeply integrate and mine the massive data from sensors and video surveillance systems. Through complex calculations and analysis, a variety of accurate safety risk assessment models are established, such as the structural stability analysis model, which can accurately assess the stability of the building structure during the construction process; the construction equipment failure prediction model, which predicts possible equipment failures in advance so that maintenance and repairs can be carried out in a timely manner; the personnel behavior risk assessment model, which conducts risk assessment on the operating behavior of construction personnel, and provides a scientific basis for safety management.

[0052] The early warning and decision support platform will promptly issue early warning information through multiple channels when the monitoring data exceeds the pre-set threshold or when the risk assessment model determines that there is a high safety risk. There are various early warning methods, including eye-catching sound and light alarms to ensure that on-site personnel can immediately detect; accurate SMS notifications to allow relevant persons in charge to obtain information in a timely manner; convenient mobile application push notifications to facilitate the grasp of the situation anytime and anywhere; and wide-coverage on-site broadcasts to ensure that every corner of the construction site can receive early warning signals. At the same time, the platform also provides emergency decision support based on virtual reality VR and augmented reality AR technology, allowing relevant personnel to understand the accident scene as if they were there, so as to make scientific and efficient emergency decisions.

[0053] Mobile terminal applications have brought great convenience to relevant personnel, enabling them to easily access the system through mobile devices anytime and anywhere. Whether it is real-time monitoring data, the latest warning information, detailed safety reports, etc., they can all be clearly presented on mobile terminals, realizing the mobility and real-time nature of security management.

[0054] Satellite positioning is integrated with the geographic information system GIS, and construction personnel and equipment are equipped with high-precision satellite positioning devices, which closely combine the acquired positioning information with the detailed GIS map of the construction site. In this way, real-time and accurate tracking and positioning management of construction personnel and equipment are achieved, and their activity trajectories and distribution can be clearly grasped, so as to carry out resource allocation and safety management more scientifically.

[0055] IoT gateways and edge computing devices are responsible for data transmission and protocol conversion between sensor networks and data processing centers. They not only ensure stable and efficient data transmission, but also perform preliminary data processing and analysis close to the data source. The preliminary screening and processing of data greatly reduces the burden on the data processing center and improves the response speed and real-time performance of the entire system.

[0056] In the present invention, in the high-precision sensor network, the types of sensors included are rich and varied, including pressure sensors that can accurately sense pressure changes, strain sensors that sensitively detect structural strain, displacement sensors that accurately measure displacement, acceleration sensors that quickly capture acceleration changes, inclination sensors that accurately measure tilt angles, temperature sensors that monitor temperature in real time, humidity sensors that dynamically sense humidity, wind speed sensors that effectively measure wind speed, and dust concentration sensors that accurately detect dust concentration.

[0057] In the present invention, the intelligent video analysis module in the intelligent video monitoring system has powerful real-time recognition capabilities, can accurately identify the wearing of safety helmets by construction workers, ensure that each construction worker wears a safety helmet correctly during work, and provide head safety protection; accurately judge whether the use of safety belts complies with the specifications, and ensure the life safety of workers working at heights; promptly discover illegal operations of construction workers, such as illegal use of electricity, illegal use of fire, etc., and quickly issue an alarm to correct the illegal behavior in time; accurately monitor the density of personnel gathering, and when the density of personnel gathering exceeds the safety threshold, immediately issue an early warning to prevent safety accidents such as trampling that may be caused by excessive concentration of personnel; efficiently identify intrusions into dangerous areas, and once unauthorized personnel or objects enter the dangerous area, immediately issue a warning to prevent the occurrence of dangerous behaviors.

[0058] In the present invention, the safety risk assessment model established by the data processing and analysis center is comprehensive and accurate. The structural stability analysis model can accurately assess the stability of the building structure during the construction process and discover potential structural safety hazards in advance by conducting in-depth analysis of the stress, deformation and other data of the structure. The construction equipment failure prediction model uses advanced machine learning algorithms based on the equipment's operating parameters, historical failure data and other information to predict possible equipment failures in advance, providing a scientific basis for timely maintenance and repairs, and effectively avoiding construction delays and safety accidents caused by equipment failures. The personnel behavior risk assessment model comprehensively considers factors such as the construction personnel's operating habits, working environment, and skill level, conducts a comprehensive risk assessment of the construction personnel's operating behavior, and provides accurate decision-making support for safety management.

[0059] In the present invention, the early warning methods of the early warning and decision support platform are rich and practical. The sound and light alarm can cause high alertness of personnel at the construction site through strong visual and auditory stimulation; SMS notification can accurately send early warning information to the mobile phone of the relevant person in charge, ensuring that he obtains important information in time; mobile application push is convenient for relevant personnel to receive early warning information on mobile devices anytime and anywhere, without being restricted by time and place; on-site broadcasting can quickly transmit early warning information to every corner of the construction site, ensuring that all personnel can receive the alarm.

[0060] In the present invention, the mobile terminal application supports convenient voice interaction and intuitive gesture operation, making it more convenient and quick for relevant personnel to operate the mobile terminal. Through voice commands, required information can be quickly queried to improve work efficiency; gesture operation provides a more intuitive and natural interaction method, allowing users to browse and operate the application interface more easily.

[0061] In addition, the present invention also includes multimodal data fusion and correlation analysis technology, which can comprehensively utilize multi-source heterogeneous data from sensors, video surveillance, satellite positioning, construction schedules, engineering drawings, etc. Through the deep fusion and correlation analysis of these data, potential safety risk laws and patterns can be excavated to provide more comprehensive and in-depth information support for safety monitoring and early warning.

[0062] The present invention also includes real-time prediction and early warning technology based on artificial intelligence, using deep learning and reinforcement learning algorithms to build a highly sensitive real-time safety risk prediction model. The model can accurately predict possible safety accidents in advance based on the real-time data and construction status currently monitored, and issue early warnings in a timely manner to prevent safety risks before they occur.

[0063] The present invention also includes personalized safety risk portraits and customized early warning technology, which establish unique personalized safety risk portraits for each construction worker, each construction equipment, and each construction area. Based on these portraits, customized safety thresholds and precise early warning strategies are formulated to ensure the pertinence and effectiveness of early warning information and minimize safety risks.

[0064] The present invention also includes blockchain technology, which strictly encrypts and distributes the entire process of sensor data and video data from collection, transmission, storage to analysis. In this way, the integrity, immutability and traceability of the data are ensured, providing highly reliable data protection for security monitoring and early warning.

[0065] 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 by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit 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 protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A construction site safety monitoring and early warning system, characterized in that: It includes high-precision sensor networks, intelligent video surveillance systems, data processing and analysis centers, early warning and decision support platforms, early warning and decision support platforms, mobile terminal applications, satellite positioning and geographic information system GIS integration, and Internet of Things gateways and edge computing devices. It features: High-precision sensor network, composed of multiple sensors deployed at key parts of building structures, construction equipment, temporary support systems, etc., to monitor the stress state and deformation of the structure, as well as the operating parameters and environmental information of the equipment in real time, and transmit the data to the data processing center through low-power, long-distance wireless communication technology; The intelligent video surveillance system, which is a combination of a high-definition panoramic camera and a high-definition zoom camera, is equipped with a deep learning-based intelligent video analysis module and a thermal imaging camera to achieve full coverage of the construction site, capture details of key areas, identify human behavior and objects, and monitor electrical equipment overheating and fire hazards; The data processing and analysis center, based on cloud computing architecture, uses big data analysis technology and machine learning algorithms to deeply integrate and mine sensor data and video data, and establishes a variety of security risk assessment models; Early warning and decision support platform: when monitoring data exceeds the preset threshold or the risk assessment model determines that there is a high security risk, early warning information is issued in a timely manner through various means, and emergency decision support based on virtual reality VR and augmented reality AR technology is provided; Mobile terminal applications make it convenient for relevant personnel to access the system through mobile devices anytime and anywhere to view real-time monitoring data, warning information, safety reports, etc.; Satellite positioning is integrated with the Geographic Information System (GIS), and construction personnel and equipment are equipped with satellite positioning devices to combine positioning information with the GIS map of the construction site; The IoT gateway and edge computing devices are responsible for data transmission and protocol conversion between the sensor network and the data processing center, and perform preliminary data processing and analysis on the side close to the data source.

2. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: The sensors in the high-precision sensor network include pressure sensors, strain sensors, displacement sensors, acceleration sensors, inclination sensors, temperature sensors, humidity sensors, wind speed sensors and dust concentration sensors.

3. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: The intelligent video analysis module in the intelligent video monitoring system can identify in real time the construction workers' helmet wearing, safety belt usage, illegal operation behaviors, crowd density and intrusion into dangerous areas.

4. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: The safety risk assessment model established by the data processing and analysis center includes a structural stability analysis model, a construction equipment failure prediction model and a personnel behavior risk assessment model.

5. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: The warning methods of the early warning and decision support platform include sound and light alarms, SMS notifications, mobile phone application push and on-site broadcasting.

6. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: The mobile terminal application supports voice interaction and gesture operation.

7. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: It also includes multimodal data fusion and correlation analysis technology, which comprehensively utilizes multi-source heterogeneous data such as sensor data, video data, positioning data, construction schedules, engineering drawings, etc. to explore potential safety risk laws and patterns.

8. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: It also includes real-time prediction and early warning technology based on artificial intelligence, which uses deep learning and reinforcement learning algorithms to build a real-time safety risk prediction model, predict possible safety accidents in advance based on current monitoring data and construction status, and issue early warnings.

9. The construction engineering site safety monitoring and early warning system according to claim 1 is characterized in that: It also includes personalized safety risk portraits and customized early warning technologies, establishing personalized safety risk portraits for each construction worker, construction equipment and construction area, and formulating customized safety thresholds and early warning strategies.

10. The construction engineering site safety monitoring and early warning system according to claim 1, characterized in that: It also includes blockchain technology, which encrypts and distributes the collection, transmission, storage and analysis processes of sensor data and video data to ensure the integrity, non-tamperability and traceability of the data.

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