Intelligent energy management of compressed air systems

Mohamad Thabet, David Sanders, Victor Becerra, Giles Tewkesbury, Malik Haddad, Tom Barker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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This work considers the use of real time sensing and AI (machine learning) to increase Compressed Air Systems (CAS) efficiency. Algorithms that automate the detection of energy inefficiencies and make decisions regarding suitable troubleshooting procedure will be created. Systems using compressed air are often inefficient and expensive to operate. Less than one unit of energy is turned into useful compressed air for every ten provided. Intelligent systems will be used to reduce energy consumption in compressors by considering real-time circumstances and the predicted needs. Sensor data will deliver information about the real time performance. AI will interpret the data and then act automatically. New intelligent techniques will be applied to save energy. This paper presents a review of the recent literature covering the topic of CAS energy efficiency. Some gaps in research were identified in the area of developing technologies and methods to detect and treat energy inefficiencies in CAS.
Original languageEnglish
Title of host publication2020 IEEE 10th International Conference on Intelligent Systems (IS)
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-7281-5456-5
ISBN (Print)978-1-7281-5457-2
Publication statusPublished - 18 Sept 2020
Event2020 IEEE 10th International Conference on Intelligent Systems - Varna, Bulgaria
Duration: 28 Aug 202030 Aug 2020

Publication series

NameIEEE IS Proceedings Series
ISSN (Print)1541-1672


Conference2020 IEEE 10th International Conference on Intelligent Systems


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