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Non-invasive Method for Elevator's Movement Monitoring Based on MEMS Sensor and Kalman Filter

Abstract

Elevator has been indispensable in modern cities, yet a great number of elevator-related accidents have caused considerable harm to people’s welfare. In response to the situation, this paper proposes a non-invasive method for elevator’s movement monitoring using MEMS sensor and Kalman filter. Specifically, the method could automatically determine elevator’s status and use Kalman filter to yield accurate estimation of elevator’s displacement, especially short range displacement, without intervening elevator’s operation. The method could potentially be used in a considerable range of scenarios, such as automatic mechanical anomaly detection and monitoring of daily or weekly usage pattern for power conservation and information services.

Publication
14th IEEE International Conference on Signal Processing
Date