Ambient intelligence based energy consumption monitoring and optimization for energy efficiency

Juhani Heilala, Krzysztof Klobut, Tapio Salonen, Reino Ruusu, Ljubisa Urosevic, Philip Reimer, Alberto Armijo, Mikel Sorli, Tomaz Fatur, Ziga Gantar

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

Abstract

Energy efficiency improvement refers to using less energy for producing the equivalent amount of services or useful output. The first step towards reduction of energy consumption is to track it along operational processes and production areas and to show data to production managers. The question is how much energy was used (input) and what was the output or activity (production quantity, operation hours or service provided) and what were the related energy use context data. Improvements are enabled if energy consumption data and other context are shown with sufficient detail to production manager or operators. The European research project AmI-MoSES is focused on developing such energy enhancement service solutions for SME manufacturing companies The AmI-MoSES service concept is based on the Industrial Ambient Intelligence (AmI) Reference Architecture. Energy use parameters and indicators are derived from monitored energy consumption data, other measured data and related energy use context data. This collected information is combined with the process and with ambient related measurement data for the purpose of creating knowledge-based context-aware services to support energy efficiency optimization.
Original languageEnglish
Title of host publicationAutomaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland
Place of PublicationHelsinki
Number of pages6
Publication statusPublished - 2011
MoE publication typeB3 Non-refereed article in conference proceedings

Publication series

NameSAS julkaisusarja
PublisherFinnish Society of Automation
Volume41
ISSN (Print)1455-6502

Fingerprint

Energy efficiency
Energy utilization
Monitoring
Managers
Ambient intelligence
Industry

Keywords

  • energy efficiency optimization
  • manufacturing process
  • asset management and monitoring

Cite this

Heilala, J., Klobut, K., Salonen, T., Ruusu, R., Urosevic, L., Reimer, P., ... Gantar, Z. (2011). Ambient intelligence based energy consumption monitoring and optimization for energy efficiency. In Automaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland Helsinki. Suomen automaatioseura. Julkaisusarja, Vol.. 41
Heilala, Juhani ; Klobut, Krzysztof ; Salonen, Tapio ; Ruusu, Reino ; Urosevic, Ljubisa ; Reimer, Philip ; Armijo, Alberto ; Sorli, Mikel ; Fatur, Tomaz ; Gantar, Ziga. / Ambient intelligence based energy consumption monitoring and optimization for energy efficiency. Automaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland. Helsinki, 2011. (Suomen automaatioseura. Julkaisusarja, Vol. 41).
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abstract = "Energy efficiency improvement refers to using less energy for producing the equivalent amount of services or useful output. The first step towards reduction of energy consumption is to track it along operational processes and production areas and to show data to production managers. The question is how much energy was used (input) and what was the output or activity (production quantity, operation hours or service provided) and what were the related energy use context data. Improvements are enabled if energy consumption data and other context are shown with sufficient detail to production manager or operators. The European research project AmI-MoSES is focused on developing such energy enhancement service solutions for SME manufacturing companies The AmI-MoSES service concept is based on the Industrial Ambient Intelligence (AmI) Reference Architecture. Energy use parameters and indicators are derived from monitored energy consumption data, other measured data and related energy use context data. This collected information is combined with the process and with ambient related measurement data for the purpose of creating knowledge-based context-aware services to support energy efficiency optimization.",
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Heilala, J, Klobut, K, Salonen, T, Ruusu, R, Urosevic, L, Reimer, P, Armijo, A, Sorli, M, Fatur, T & Gantar, Z 2011, Ambient intelligence based energy consumption monitoring and optimization for energy efficiency. in Automaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland. Helsinki, Suomen automaatioseura. Julkaisusarja, vol. 41.

Ambient intelligence based energy consumption monitoring and optimization for energy efficiency. / Heilala, Juhani; Klobut, Krzysztof; Salonen, Tapio; Ruusu, Reino; Urosevic, Ljubisa; Reimer, Philip; Armijo, Alberto; Sorli, Mikel; Fatur, Tomaz; Gantar, Ziga.

Automaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland. Helsinki, 2011. (Suomen automaatioseura. Julkaisusarja, Vol. 41).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

TY - GEN

T1 - Ambient intelligence based energy consumption monitoring and optimization for energy efficiency

AU - Heilala, Juhani

AU - Klobut, Krzysztof

AU - Salonen, Tapio

AU - Ruusu, Reino

AU - Urosevic, Ljubisa

AU - Reimer, Philip

AU - Armijo, Alberto

AU - Sorli, Mikel

AU - Fatur, Tomaz

AU - Gantar, Ziga

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N2 - Energy efficiency improvement refers to using less energy for producing the equivalent amount of services or useful output. The first step towards reduction of energy consumption is to track it along operational processes and production areas and to show data to production managers. The question is how much energy was used (input) and what was the output or activity (production quantity, operation hours or service provided) and what were the related energy use context data. Improvements are enabled if energy consumption data and other context are shown with sufficient detail to production manager or operators. The European research project AmI-MoSES is focused on developing such energy enhancement service solutions for SME manufacturing companies The AmI-MoSES service concept is based on the Industrial Ambient Intelligence (AmI) Reference Architecture. Energy use parameters and indicators are derived from monitored energy consumption data, other measured data and related energy use context data. This collected information is combined with the process and with ambient related measurement data for the purpose of creating knowledge-based context-aware services to support energy efficiency optimization.

AB - Energy efficiency improvement refers to using less energy for producing the equivalent amount of services or useful output. The first step towards reduction of energy consumption is to track it along operational processes and production areas and to show data to production managers. The question is how much energy was used (input) and what was the output or activity (production quantity, operation hours or service provided) and what were the related energy use context data. Improvements are enabled if energy consumption data and other context are shown with sufficient detail to production manager or operators. The European research project AmI-MoSES is focused on developing such energy enhancement service solutions for SME manufacturing companies The AmI-MoSES service concept is based on the Industrial Ambient Intelligence (AmI) Reference Architecture. Energy use parameters and indicators are derived from monitored energy consumption data, other measured data and related energy use context data. This collected information is combined with the process and with ambient related measurement data for the purpose of creating knowledge-based context-aware services to support energy efficiency optimization.

KW - energy efficiency optimization

KW - manufacturing process

KW - asset management and monitoring

M3 - Conference article in proceedings

SN - 978-952-5183-43-6

T3 - SAS julkaisusarja

BT - Automaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland

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Heilala J, Klobut K, Salonen T, Ruusu R, Urosevic L, Reimer P et al. Ambient intelligence based energy consumption monitoring and optimization for energy efficiency. In Automaatio XIX Seminar 2011, 15-16.3.2011, Helsinki, Finland. Helsinki. 2011. (Suomen automaatioseura. Julkaisusarja, Vol. 41).