Artificial Intelligence in Elevator Fault Diagnosis: A Process Optimization Perspective
Abstract
A contingency framework indicates that AI diagnosis will achieve its best results when combined with real-time sensor data and provided to
technicians in an understandable way rather than as a black-box prediction. Therefore, AI-powered fault diagnosis will not only be used to
replace the old mode of maintenance but also fundamentally change how elevator failure detection, location identification and response are
carried out by maintenance staff.
Keywords
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DOI: http://dx.doi.org/10.70711/aitr.v4i4.10151
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