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


    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
    PublisherSuomen automaatioseura
    Number of pages6
    ISBN (Print)978-952-5183-43-6
    Publication statusPublished - 2011
    MoE publication typeB3 Non-refereed article in conference proceedings

    Publication series

    SeriesSuomen automaatioseura. Julkaisusarja


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


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