Businesses across Hebei are zeroing in on high-risk sectors to strengthen safety monitoring and early warning systems, actively adopting a regulatory model that fuses internet connectivity with artificial intelligence to prevent major accidents. On September 5th, at the smart operations hub of Hebei Weiyuan Biochemical Co., Ltd., a massive display showcased real-time data streams, including workforce heat maps, equipment vibration spectrums, and carbon emission curves. The system's AI-driven features, such as one-click task dispatch and automated error correction, responded instantly to operational changes.
"Safety is the lifeline for a company's high-quality growth. By getting data moving, we make safety oversight more penetrating, identifying and resolving hidden dangers early and thoroughly," stated Xu Yiwei, General Manager of Hebei Weiyuan Biochemical Co., Ltd. The company has deepened its internet-plus-safety production framework, upgrading its intelligent safety platform and deploying personnel positioning systems to enhance emergency response capabilities and mitigate risks at the source.
In the coal mining sector, a key energy production base, safety remains a top public concern. The Dongpang Mine of Jizhong Energy Group has prioritized intelligent upgrades across core areas like underground excavation, electromechanical transport, and ventilation systems. "Intelligent construction is akin to installing a 'cloud brain' for the mine, empowering smart safety supervision," noted Xing Yu, the mine's safety director. The operation has rolled out a comprehensive AI video monitoring platform with smart sensors at critical underground points that can automatically identify risky behaviors, delivering second-level alerts and full video recording for traceability. An upgraded four-network integrated monitoring system now links real-time data on gas, dust, roof conditions, and hydrology, enabling automatic anomaly alerts and shifting safety management from post-incident accountability to proactive prediction and prevention. Xing Yu added that the mine will continue to refine its intelligent oversight system, expand AI applications, break down data silos, and integrate smart monitoring with robust safety control mechanisms to elevate overall governance.
Steel, a pillar industry of Hebei, is also undergoing a safety transformation driven by data. On September 6th, at HBIS Group Shisteel Company, a risk monitoring and early warning system acted like a vigilant "all-seeing eye," tracking equipment operations around the clock. The platform integrates real-time alerts for 52 critical parameters, including major hazard sources and metal smelting, ensuring full coverage of key equipment and zones. "Using the internet-plus-AI technology platform, we've built a robust risk monitoring system that provides round-the-clock online surveillance for major safety risks like water leakage in water-cooled components of electric arc furnaces and refining furnaces," explained Cao Xiuhai, Safety Director of HBIS Group Shisteel Company. The company plans to leverage digital big-model tech and vast datasets to deepen trend analysis, conduct predictive assessments, and identify potential risks ahead of time, transitioning from reactive handling to proactive prevention.
Meanwhile, the construction industry, plagued by challenges like frequent high-altitude and cross operations, is turning to smart solutions to eliminate blind spots in traditional oversight. Dayuan Construction Group Co., Ltd. has advanced its "smart site" initiative by establishing a management platform that connects high-risk elements such as tower cranes, deep foundation pits, and large formwork systems to real-time monitoring. The firm is piloting inspection robots, AI recognition with voice alert systems, and operational robots. Wang Yanfeng, the company's Chief Safety Officer, said they are actively exploring intelligent regulatory models, leveraging the Internet of Things and smart helmets to track personnel location, health status, and working conditions in real-time. By applying big data to create precise project profiles, they aim to shift safety decisions from intuition-based to data-driven, ensuring safer construction environments.
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