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

    SeriesSuomen automaatioseura. Julkaisusarja
    Volume41
    ISSN1455-6502

    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).
    @inproceedings{5ac9c8a8705b4aaa8b5fa18de9ed6386,
    title = "Ambient intelligence based energy consumption monitoring and optimization for energy efficiency",
    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.",
    keywords = "energy efficiency optimization, manufacturing process, asset management and monitoring",
    author = "Juhani Heilala and Krzysztof Klobut and Tapio Salonen and Reino Ruusu and Ljubisa Urosevic and Philip Reimer and Alberto Armijo and Mikel Sorli and Tomaz Fatur and Ziga Gantar",
    note = "Project: 23620",
    year = "2011",
    language = "English",
    isbn = "978-952-5183-43-6",
    series = "Suomen automaatioseura. Julkaisusarja",
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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

    N1 - Project: 23620

    PY - 2011

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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 - Suomen automaatioseura. 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).