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Making Decisions About Saving Energy in Compressed Air Systems Using Ambient Intelligence and Artificial Intelligence

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Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 869))

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Abstract

Compressed air systems are often the most expensive and inefficient industrial systems. For every 10 units of energy, less than 1 unit turns into useful compressed air. Air compressors tend to be kept fully on even if they are not (all) needed. The research proposed in this short paper will combine real time ambient sensing with Artificial Intelligence and Knowledge Management to automatically improve efficiency in energy intensive manufacturing. The research will minimise energy use for air compressors based on real-time manufacturing conditions (and anticipated future requirements). Ambient data will provide detailed information on performance. Artificial Intelligence will make sense of that data and automatically act. Knowledge Management will facilitate the processing of information to advise human operators on actions to reduce energy use and maintain productivity. The aim is to create new intelligent techniques to save energy in compressed air systems.

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Author information

Authors and Affiliations

  1. School of Engineering, University of Portsmouth, Portsmouth, PO1 3DJ, UK

    David Adrian Sanders, Mohamed Hassan, Malik Haddad & Nadia Ahmed

  2. Cutting Tools Ltd, Castle Park Industrial Estate, Oldham, OL1 3LN, UK

    David Charles Robinson

  3. School of Computing, University of Portsmouth, Portsmouth, PO1 3HE, UK

    Alexander Gegov

Authors
  1. David Adrian Sanders
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  2. David Charles Robinson
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  3. Mohamed Hassan
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  4. Malik Haddad
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  5. Alexander Gegov
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  6. Nadia Ahmed
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Corresponding author

Correspondence to David Adrian Sanders .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

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Sanders, D.A., Robinson, D.C., Hassan, M., Haddad, M., Gegov, A., Ahmed, N. (2019). Making Decisions About Saving Energy in Compressed Air Systems Using Ambient Intelligence and Artificial Intelligence. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_92

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