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

David Sanders; David Charles Robinson; Mohamed Hassan Sayed; Malik Jamal Musa Haddad; Alexander Gegov; Nadia Ahmed

doi:10.1007/978-3-030-01057-7_92

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

David Sanders, David Charles Robinson, Mohamed Hassan Sayed, Malik Jamal Musa Haddad, Alexander Gegov, Nadia Ahmed

School of Computing

Cutting Tools Ltd

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

425 Downloads (Pure)

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.

Original language	English
Title of host publication	Intelligent Systems and Applications
Subtitle of host publication	Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2
Editors	Kohei Arai, Supriya Kapoor, Rahul Bhatia
Publisher	Springer
Pages	1229-1236
ISBN (Electronic)	978-3-030-01057-7
ISBN (Print)	978-3-030-01056-0
DOIs	https://doi.org/10.1007/978-3-030-01057-7_92
Publication status	Published - Jan 2019
Event	IntelliSys 2018 - London, United Kingdom Duration: 6 Sept 2018 → 7 Sept 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	869
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	IntelliSys 2018
Country/Territory	United Kingdom
City	London
Period	6/09/18 → 7/09/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

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

Final_paper_IntelliSys_2018_making_decisions_about_energy
The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-01057-7_92.
Accepted author manuscript (Post-print), 363 KBLicence: Unspecified

http://saiconference.com/Conferences/IntelliSys2018

Management and Business Decision Making
Haddad, M. (CoI) & Sanders, D. (PI)
26/09/16 → 29/04/22
Project: Research
Using artificial intelligence and sensor systems for energy applications
Sanders, D. (PI), Robinson, D. (CoI), Gegov, A. (CoI) & Mazharsolook, E. (CoI)
21/06/14 → 3/04/17
Project: Research

Cite this

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

Sanders, David ; Robinson, David Charles ; Hassan Sayed, Mohamed et al. / 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).

@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; IntelliSys 2018 ; Conference date: 06-09-2018 Through 07-09-2018",

year = "2019",

month = jan,

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",

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booktitle = "Intelligent Systems and Applications",

}

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

Making decisions about saving energy in compressed air systems using Ambient Intelligence and Artificial Intelligence. / Sanders, David; Robinson, David Charles; Hassan Sayed, Mohamed et al.
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 proceeding › Conference contribution

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

T2 - IntelliSys 2018

Y2 - 6 September 2018 through 7 September 2018

ER -

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). Epub 2018 Nov 8. doi: 10.1007/978-3-030-01057-7_92

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

Abstract

Publication series

Conference

UN SDGs

Access to Document

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Projects

Management and Business Decision Making

Using artificial intelligence and sensor systems for energy applications

Cite this