Recently, the Ministry of Industry and Information Technology (MIIT) officially announced the list of typical cases of industrial internet “chain-network collaboration” for 2025. Recommended jointly by the Beijing Municipal Bureau of Economy and Information Technology and the Beijing Communications Administration, the application “Intelligent Monitoring of Chemical Hazard Sources and Chain-Network Collaborative Early Warning Based on Industrial Internet” submitted by Beijing Bangandi Information Technology Co., Ltd. (hereinafter referred to as “Bangandi”) stood out among numerous competing cases nationwide and was successfully selected, thanks to its innovative technical architecture, remarkable cost-reduction and efficiency-improvement results, and high scalability for large-scale replication. This national-level honor marks the company’s innovative leadership in the field of industrial safety digitalization as recognized by national authorities, and also provides a replicable benchmark model for the digital and green transformation of high-risk industries such as the chemical industry.
1. Tackling Industry Pain Points and Creating a Lightweight “New Model”
Addressing the core pain points commonly faced by hazardous chemical enterprises—fragmented monitoring methods, lagging early warning responses, high deployment costs of safety systems, and a lack of standardized lightweight applications—Bangandi has innovatively developed the “Industrial Internet-Based Intelligent Monitoring of Hazard Sources and Chain-Network Collaborative Early Warning Application.” With core goals of lightweight deployment, low-cost access, intelligent early warning, and networked collaboration, the solution deeply integrates IoT, edge computing, and AI analysis technologies to build a hazard source monitoring and early warning platform covering the entire chain of “perception—analysis—early warning—linkage.” Using a self-developed low-power IoT gateway, plug-and-play for mainstream protocols is achieved, reducing single-point retrofit costs by over 60% compared to traditional solutions. The lightweight AI model deployed at the edge improves early warning response speed to the second level while reducing false alarm rates by more than 40%, truly realizing the leap from “passive emergency response” to “active prevention.”
2. Deepening Chain-Network Collaboration and Building a Three-Tier Prevention and Control Network
The core value of this case lies not only in internal safety management and control of enterprises but also in its powerful “chain-network collaboration” capability. Through industrial internet identification resolution and API interfaces, the platform enables cross-device, cross-system, and cross-enterprise connectivity of hazard source data. Upstream, when abnormal liquid levels in raw material storage tanks or fluctuations in feed pressure occur, the system automatically pushes warnings to suppliers, prompting them to inspect transmission pipelines or adjust delivery schedules, thereby avoiding production stoppages due to raw material interruption. Downstream, during hazardous chemical loading operations, the platform shares real-time information on tank truck positions and tank status with logistics carrier platforms, improving dispatch efficiency and reducing average loading waiting time by 22%. At the same time, warning events are automatically synchronized to the smart emergency platform of the chemical industrial park and the provincial-level whole-chain supervision system for hazardous chemicals, building an integrated linkage mechanism of “enterprise alert, park response, government supervision,” effectively enhancing the overall safety resilience of the industrial chain.
3. Significant Results Driving Scalable Replication
Currently, this case has been stably operating at Cangzhou Xuyang Chemical Co., Ltd. for over three years, achieving remarkable economic and social benefits. In terms of safety, the effective early warning recognition rate reaches 92%, and the closed-loop handling rate for accident hazards is 98.5%. By preventing potential leaks and overpressure events through early warnings, unplanned shutdown losses are reduced by approximately 3.2 million RMB annually. In terms of cost reduction, the full deployment cost for a single enterprise is controlled between 250,000 and 350,000 RMB, only one-third to one-half of traditional customized systems, with average annual operation and maintenance savings of 180,000 RMB per enterprise. In terms of green and low-carbon benefits, by monitoring abnormal operating conditions, steam and electricity waste is reduced by approximately 120,000 kWh, equivalent to a carbon emission reduction of 96 tons of CO₂, while also avoiding the risk of environmental penalties. Leveraging its notable characteristics of “small, lightweight, fast, and precise” (small investment, fast deployment, lightweight, precise early warning), the solution has formed a mature replication model of “standard product + local service + ecological collaboration.” As of December 2025, it has been successfully promoted and applied in dozens of enterprises such as Xuyang Group, Hubei Jianghan, and Hainan Yisheng, as well as dozens of chemical industrial parks including Weifang Binhai and Jilin Chemical, and government regulatory platforms.
4. Looking Ahead: Continuously Empowering Industrial Safety
This selection as a typical case of industrial internet “chain-network collaboration” 2025 by MIIT is authoritative recognition of Bangandi’s deep commitment to the field of industrial safety digitalization and its drive for collaborative innovation across the industrial chain. In the future, Bangandi will continue to use the industrial internet as a link, technological innovation as an engine, and chain leader empowerment as a lever, continuously upgrading its products in directions such as AI large models, digital twins, and safety-environmental protection-energy efficiency synergy. It will also deepen efficient collaboration between upstream and downstream players in the industrial chain, accelerate the integration and innovation of digital technology with industrial safety scenarios, contribute more wisdom and solutions to industry transformation and upgrading as well as new industrialization construction, and inject solid momentum into the construction of Digital China.
