(33a) Strategic Framework for Establishing Industrial Safety Technology and Management Methodologies from Dual Perspectives of the Internet and Big Data

Through the integrated application of the Internet, industrial safety technologies and management methods have undergone transformations from static to dynamic, post-event to pre-event, and single-point to holistic, thereby enhancing the intrinsic safety level of industrial production. The Internet has provided advanced technological means for work safety, supporting the digitalization, networking, and intelligent transformation of the manufacturing industry, and shaping a new mode of industrial production, manufacturing, and safety management. In industries such as petrochemicals, steel, mining, and electricity, the combination of the Internet and work safety has resulted in several pilot cases, demonstrating its practical effects in elevating safety management standards.

To deeply explore the innovations and practical applications of industrial safety technologies and management methods in the context of Internet and big data technologies, this paper constructs a comprehensive and systematic framework for Internet-based safety production technologies and management methods. This framework not only clarifies the application scenarios of the technologies but also details the technical architecture diagrams supporting these scenarios, providing an intuitive reference for understanding how the Internet and big data empower industrial safety. Starting from the instrumental realization of data acquisition and preprocessing technologies, this paper exhaustively introduces how to utilize advanced intelligent sensing technologies (such as sensor networks and IoT devices) to capture subtle changes in industrial environments and establish reliable data transmission channels through efficient network infrastructures, ensuring that raw data can be quickly and accurately transmitted to data centers for further processing. This step serves as the foundation of the entire data-driven safety management system, directly impacting the quality and effectiveness of subsequent data analysis. This paper delves into a series of key technical modules, including but not limited to deep data analysis and knowledge mining mechanisms. Specifically, it discusses predictive maintenance technologies for equipment failures, which, through deep learning and pattern recognition of historical data on equipment operating states, can predict potential equipment failures in advance, allowing for preventive measures to avoid unexpected shutdowns; monitoring and early warning technologies for major hazard sources, which continuously monitor changes in environmental parameters in high-risk areas and promptly issue alerts to remind relevant personnel to take necessary actions; feature recognition technologies based on machine vision, which can accurately identify specific targets or abnormal situations in complex working environments, improving operational efficiency while ensuring personnel safety; and production safety accident and incident investigation and analysis technologies based on industrial large models, which utilize large-scale datasets to train models for a deeper understanding of the root causes of accidents, providing a scientific basis for formulating effective preventive measures.

This paper also specifically elaborates on the construction scheme for intelligent decision support and risk early warning systems. This system integrates various functions such as automatic control, intelligent analysis and early warning, and auxiliary decision-making, aiming to rapidly assess potential safety risks by conducting real-time analysis of massive data generated during industrial production processes and propose corresponding countermeasures. Through this approach, not only can early detection and timely handling of safety risks be achieved, but the overall management level and emergency response capabilities of enterprises can also be significantly enhanced, laying a solid foundation for constructing a safer and more efficient industrial production environment.

This paper aims to deeply analyze the current application status and future development trends of Internet and big data technologies in the field of industrial safety technologies and management methods. Firstly, this paper reviews and evaluates the key paths for the intelligent transformation of existing industrial safety technologies and management methods, emphasizing the role played by Internet technology as the core force driving this transformation. Specifically, the development of Internet technology has significantly enhanced the sensing capabilities, data acquisition capabilities, and computing processing capabilities of various production equipment and systems, thereby prompting the transformation of industrial safety management from traditional static data analysis modes to more flexible and efficient dynamic perception modes, realizing the transition from passive post-event emergency management to proactive pre-event risk prevention strategies, and facilitating the evolution from single-node safety protection measures to comprehensive prevention and control systems covering the entire production network. This transformation has significantly improved the intrinsic safety of industrial production and reduced potential safety hazards. Furthermore, this paper discusses in detail the new generation of industrial safety technologies and management methods that are currently under research and development or in preliminary stages of application. These innovative achievements have not only broadened the research boundaries in the field of industrial safety but also brought revolutionary changes to its practical operations. For example, in terms of emergency resource allocation and coordinated disposal technologies, by constructing highly integrated information platforms, rapid response and effective management of emergencies can be achieved, ensuring optimal resource allocation within the shortest time and minimizing the impact of accidents. Additionally, human error early warning models based on big data analysis collect and analyze large amounts of historical data to identify operational patterns or environmental factors that may lead to human errors, taking intervention measures in advance to reduce accident rates and providing a more scientific and reliable safeguard mechanism for industrial safety.

This paper systematically summarizes the practical applications and case studies of Internet technology in the field of work safety, aiming to provide valuable references for industrial enterprises globally. Firstly, from a global perspective, it outlines the current status of Internet technology applications in safety in multiple industries such as petrochemicals, steel, mining, and electricity, demonstrating how Internet technology, through the construction of intelligent management systems, achieves comprehensive perception, monitoring, and early warning of production units, equipment status, personnel safety, and other aspects. These applications have not only significantly elevated the management level of work safety in various industries but also provided powerful technical support for preventing and reducing the occurrence of safety accidents.

For the Internet safety applications in specific industries, this paper conducts an in-depth analysis. Taking the petrochemical industry as an example, the application of Internet technology is mainly reflected in the real-time monitoring and data acquisition of oil and gas field exploration, refinery chemical processing, and other links through the deployment of advanced sensing devices and wireless communication networks, followed by the use of big data analysis technology to accurately predict and effectively manage potential safety risks. In the steel industry, Internet technology is widely used in production process optimization, equipment health status monitoring, and other aspects, establishing virtual simulation models to simulate various possible scenarios in the production process and identify and resolve potential issues in advance. The mining industry leverages Internet technology to achieve comprehensive perception of the mine environment and remote monitoring of mining machinery operating states, significantly reducing operational risks. The power industry utilizes Internet technology to strengthen real-time monitoring of grid operating states, improving fault diagnosis speed and accuracy, and ensuring the safe and stable supply of electricity. To further promote the development of industrial safety technologies and management methods based on the Internet and big data, this paper proposes several strategies and recommendations. Firstly, strengthen collaborative efforts to build cross-departmental and cross-industry information sharing and cooperation mechanisms, forming a joint force to address complex safety challenges. Secondly, adhere to a problem-oriented approach, focusing on prominent issues and weak links in current work safety, and conduct targeted technology research and development and application promotion. Thirdly, deepen supply capabilities by encouraging and supporting enterprises to increase research and development investments, continuously enhancing technological innovation capabilities and product quality. Additionally, integrate standard systems to promote the establishment of unified "Internet + Work Safety" technical standards, facilitating interoperability between different systems. Finally, strengthen experience dissemination through the sharing of typical cases, technical exchanges, and other means, accelerating the dissemination and application of advanced technologies and successful experiences, and improving the safety management level of the entire industry. In summary, through a comprehensive review and in-depth analysis of the applications of Internet technology in the field of work safety, this paper provides important theoretical support and practical guidance for relevant industrial enterprises to carry out Internet-based digital management of work safety, which is of great significance for promoting advancements in industrial work safety technology in China and even globally.