Systematic application and research of artificial intelligence technology in smart supervision of elevators

Purpose The study aims to explore the transformation mechanism of artificial intelligence on elevator safety supervision and provide a theoretically cutting-edge and practically guiding governance plan for Ningbo and similar cities. Design/methodology/approach Based on the actual needs of Ningbo Municipal Market Supervision Bureau, this paper constructs a research system through literature review and case analysis, identifies key problems and proposes a four-dimensional AI supervision framework with technical application models and platform construction plans. Findings Four major supervision problems (“human-machine conflict”, “regulatory lag”, “early warning deficiency”, “data island”) are identified. A four-dimensional theoretical framework and technical application models for four scenarios (PHM, behavior recognition, voice emergency disposal, credit evaluation) are developed, with a three-stage platform construction plan and implementation solutions. Originality/value This study systematically constructs an AI-enabled closed-loop system for urban-level elevator lifecycle governance for the first time. We organically integrate independent technologies such as PHM, CV and NLP into a unified regulatory framework through the core carrier of “Digital Twin” and the computing paradigm of “Cloud-Edge Collaboration”, solving the key transition problem from “single-point intelligence” to “system intelligence”.