An internet of things-based lift predictive maintenance system

Publication Type

Journal Article

Publication Date

1-2021

Abstract

Lift (or elevator) breakdowns cause huge inconveniences to city dwellers and affect more than 80% of Singapore's residents who live in high-rise apartments. Unfortunately, lift maintenance today is either preventive (e.g., follows a fixed cycle based on statistics) or reactive (the faults are fixed after they happen). In this article, we describe a lift-model-agnostic and nation wide predictive maintenance system for lifts in high-rise apartments in Singapore. Based on real sensor and operational data collected over a 14-month period from more than 100 lifts, our prediction model is able to forecast a breakdown better than random guesses despite a highly imbalanced data set.

Keywords

Electric breakdown, Urban areas, Internet, Predictive maintenance

Discipline

Electrical and Computer Engineering

Publication

IEEE Potentials

Volume

40

Issue

1

First Page

17

Last Page

23

ISSN

0278-6648

Identifier

10.1109/MPOT.2020.2973697

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/MPOT.2020.2973697

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