Waste incineration for power generation, as a new type of waste treatment method, converts waste into electrical energy, achieving resource reuse and becoming one of the important ways to achieve energy saving and environmental protection. To effectively implement its Environmental, Health, Safety, and Social Responsibility (EHSS) management system, Everbright Environment Energy, a renowned waste-to-energy investment operator, is committed to extensively leveraging technology to enhance the operational efficiency of all its plant systems. Following multi-stage discussions and project pilots, multiple project companies under Everbright Environment Energy have reached a deep cooperation with Xinmai, jointly exploring new directions for AI-driven intelligent management in waste-to-energy plants.

Everbright Environment Energy

Establishes the 'Halo Cloud Guardian' Smart Security System Management Platform

After multiple on-site inspections and demand assessments, a set of 'Halo Cloud Guardian' Smart Security System Management Platform was successfully built for Everbright Environment Energy. It is equipped with nearly 30 types of safety control series AI vision algorithms to intelligently identify personnel operational risks and environmental safety hazards, etc., in each waste-to-energy plant, and display the recognition results in real-time on the headquarters platform.

△ 'Halo Cloud Guardian' Smart Security System Management Platform

The platform also supports photo upload and organization functions via a mobile 'snap-and-shoot' WeChat mini-program. It offers analytical functions such as plant personnel control analysis, safety production risk control, and scoring. Bidding farewell to traditional manual inspections, it achieves intelligent personnel management and intelligent environmental analysis, creating a truly intelligent comprehensive security management system for plants, significantly improving operational efficiency.

Deep Dive into Real-World Demand Scenarios of Waste-to-Energy Plants

Developing Nearly 30 'Safety Control Series AI Vision Algorithms'

The nearly 30 'Safety Control Series AI Vision Algorithms' can perform real-time intelligent recognition across various plant scenarios for dimensions such as personnel protective equipment (PPE) wearing, personnel behavior, hot work operations, compliant unloading platform operations, equipment status, and environmental hazards, effectively preventing various types of safety accidents.

Personnel PPE Wearing and Behavior: Hard hat recognition, safety rope recognition, reflective vest recognition, smoking recognition, fall detection, fence climbing recognition, leaving post recognition, personnel count recognition, recognition of special PPE wearing in confined spaces, etc.;

Compliant Hot Work Operations: Recognition of special operation personnel and supervisor check-in, recognition of PPE for hot work, oxygen and acetylene cylinder placement recognition, fire extinguisher placement recognition, etc.;

Compliant Unloading Platform Operations: Recognition of vehicle anchoring and release of ground anchor safety locks on the unloading platform, recognition of personnel entering restricted areas on the unloading platform, recognition of personnel wearing safety ropes on the unloading platform, recognition of drivers not exiting vehicles on the unloading platform, etc.;

Equipment Status and Environmental Hazards: Scaffolding acceptance tag recognition, material leakage/clogging recognition, ash accumulation recognition, belt conveyor anomaly recognition; open flame recognition, smoke recognition, water accumulation recognition, small animal (rat) recognition, vehicle littering/spillage recognition, etc.

△ Application effects of some safety control series algorithms

Results Recognized by Users, Deployed Across Multiple Plants

Waste-to-Energy Plant Security Achieves Comprehensive Intelligent Upgrade

In March 2022, the security project at Everbright Environment Energy's Haiyan plant commenced construction and has gained user recognition. Currently, this platform has been deployed in Everbright Haiyan, Hangzhou, Shengzhou, Zhangjiajie, Xiong'an, Donghai, and other plants, with more plants to follow.

Long Shijie, Everbright Project Manager, stated: “Everbright Environment Energy has a very strict set of operational standards, with different requirements for different scenarios. This presented a significant challenge for the customized design of AI algorithms. Secondly, during project delivery, we faced extensive debugging and optimization work, requiring both human operators and algorithms to have a deep understanding of the business. Facing the complexity and high difficulty of the project, our professional team conducted multiple on-site inspections, dedicated themselves to research, and ultimately developed high-precision algorithms with excellent adaptability, enabling rapid promotion and deployment across different Everbright Environment Energy plant projects, ultimately achieving cost reduction and efficiency improvement for the client.”

In the future, we will join hands with Everbright Environment Energy to jointly explore more possibilities in the field of smart security, striving for the comprehensive intelligent transformation of the waste-to-energy industry, continuously pioneering innovation, deeply cultivating industry scenarios, and creating technological experiences with AI.