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Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence

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

Standard

Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence. / Sanders, David; Robinson, David Charles; Hassan Sayed, Mohamed; Haddad, Malik Jamal Musa; Gegov, Alexander; Ahmed, Nadia.

Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2. ed. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Springer, 2019. p. 1229-1236 (Advances in Intelligent Systems and Computing; Vol. 869).

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

Harvard

Sanders, D, Robinson, DC, Hassan Sayed, M, Haddad, MJM, Gegov, A & Ahmed, N 2019, Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence. in K Arai, S Kapoor & R Bhatia (eds), Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2. Advances in Intelligent Systems and Computing, vol. 869, Springer, pp. 1229-1236, IntelliSys 2018, London, United Kingdom, 6/09/18. https://doi.org/10.1007/978-3-030-01057-7_92

APA

Sanders, D., Robinson, D. C., Hassan Sayed, M., Haddad, M. J. M., Gegov, A., & Ahmed, N. (2019). Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence. In K. Arai, S. Kapoor, & R. Bhatia (Eds.), Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2 (pp. 1229-1236). (Advances in Intelligent Systems and Computing; Vol. 869). Springer. https://doi.org/10.1007/978-3-030-01057-7_92

Vancouver

Sanders D, Robinson DC, Hassan Sayed M, Haddad MJM, Gegov A, Ahmed N. Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence. In Arai K, Kapoor S, Bhatia R, editors, Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2. Springer. 2019. p. 1229-1236. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-01057-7_92

Author

Sanders, David ; Robinson, David Charles ; Hassan Sayed, Mohamed ; Haddad, Malik Jamal Musa ; Gegov, Alexander ; Ahmed, Nadia. / Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence. Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2. editor / Kohei Arai ; Supriya Kapoor ; Rahul Bhatia. Springer, 2019. pp. 1229-1236 (Advances in Intelligent Systems and Computing).

Bibtex

@inproceedings{90b423add54341058a6ca4d98d94a099,
title = "Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence",
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 combinereal time ambient sensing with Artificial Intelligence andKnowledge 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 datawill 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.",
author = "David Sanders and Robinson, {David Charles} and {Hassan Sayed}, Mohamed and Haddad, {Malik Jamal Musa} and Alexander Gegov and Nadia Ahmed",
note = "expected pp, 1313-1316",
year = "2019",
month = "1",
doi = "10.1007/978-3-030-01057-7_92",
language = "English",
isbn = "978-3-030-01056-0",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "1229--1236",
editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",
booktitle = "Intelligent Systems and Applications",

}

RIS

TY - GEN

T1 - Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence

AU - Sanders, David

AU - Robinson, David Charles

AU - Hassan Sayed, Mohamed

AU - Haddad, Malik Jamal Musa

AU - Gegov, Alexander

AU - Ahmed, Nadia

N1 - expected pp, 1313-1316

PY - 2019/1

Y1 - 2019/1

N2 - 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 combinereal time ambient sensing with Artificial Intelligence andKnowledge 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 datawill 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.

AB - 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 combinereal time ambient sensing with Artificial Intelligence andKnowledge 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 datawill 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.

UR - https://www.springer.com/gb/book/9783030010539

UR - https://www.springer.com/gb/book/9783030010560

U2 - 10.1007/978-3-030-01057-7_92

DO - 10.1007/978-3-030-01057-7_92

M3 - Conference contribution

SN - 978-3-030-01056-0

T3 - Advances in Intelligent Systems and Computing

SP - 1229

EP - 1236

BT - Intelligent Systems and Applications

A2 - Arai, Kohei

A2 - Kapoor, Supriya

A2 - Bhatia, Rahul

PB - Springer

ER -

ID: 8746618