An Artificial Intelligence Empowered Cyber Physical Ecosystem for Energy Efficiency and Occupation Health and Safety

Petros Koutroumpinas, Yu Zhang, Steve Wallis and Elizabeth Chang
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Petros Koutroumpinas: Faculty of Engineering, Monash University, Melbourne, VIC 3800, Australia
Yu Zhang: School of Business, University of New South Wales, Canberra, ACT 2612, Australia
Steve Wallis: Fleetwood Corporation Limited, Perth, WA 6004, Australia
Elizabeth Chang: School of Business, University of New South Wales, Canberra, ACT 2612, Australia

Energies, 2021, vol. 14, issue 14, 1-14

Abstract: Reducing energy waste is one of the primary concerns facing Remote Industrial Plants (RIP) and, in particular, the accommodations and operational plants located in remote areas. With the COVID-19 pandemic continuing to attack the health of workforce, managing the balance between energy efficiency and Occupation Health and Safety (OHS) in the workplace becomes another great challenge for the RIP. Maintaining this balance is difficult mainly because a full awareness of the OHS will generally consume more energy while reducing the energy cost may lead to a less effective OHS, and the existing literature has not seen a system that is designed for the RIPs to conserve energy usage and improve workforce OHS simultaneously. To bridge this gap, in this paper, we propose an AI Empowered Cyber Physical Ecosystem (AECPE) solution for the RIPs, which integrates Cyber-Physical Systems (CPS), artificial intelligence, and mobile networks. The preliminary results of lab experiments and field tests proved that the AECPE was able to help industries reduce the corporate annual energy cost that is worth millions of dollars, optimise the environmental conditions, and improve OHS for all workers and stakeholders. The implementation of the AECPE can result in efficient energy usage, reduced wastage and emissions, environment-friendly operations, and improved social reputation of the industries.

Keywords: cyber-physical system; ecosystem; remote industries; OHS; energy efficiency; smart meter; artificial intelligence; COVID-19 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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