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IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach

Author

Listed:
  • Luis Gomes

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic Institute of Porto (IPP), P-4200-465 Porto, Portugal)

  • Carlos Ramos

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic Institute of Porto (IPP), P-4200-465 Porto, Portugal)

  • Aria Jozi

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic Institute of Porto (IPP), P-4200-465 Porto, Portugal)

  • Bruno Serra

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic Institute of Porto (IPP), P-4200-465 Porto, Portugal)

  • Lucas Paiva

    (IFSC—Instituto Federal de Santa Catarina (Campus Florianópolis Centro), 88020-300 Florianópolis, Santa Catarina, Brazil)

  • Zita Vale

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic Institute of Porto (IPP), P-4200-465 Porto, Portugal)

Abstract

This paper presents IoH (Intelligence of Home), a platform developed to test some basic intelligent behaviors in Home context. Internet of Things, ambient intelligence and context awareness approaches motivated the development of IoH. The platform involves six layers, responsible by connectivity, persistency, unification, Internet of Things integration, subsystems integration and user interface. The integrated subsystems involve intelligent systems for light control, television brightness control, desk light control, persons counting and air conditioner control. The IoH platform is then tested for a real building, and results and conclusions are obtained. Different intelligent methods and technologies are used, form the use of a diversity of sensors, actuators, and controllers and processing units to a set of artificial intelligence approaches varying from machine learning and optimization algorithms to the use of sensor fusion and computer vision. The use of IoH day-by-day demonstrated an intelligent performance for the real building occupants.

Suggested Citation

  • Luis Gomes & Carlos Ramos & Aria Jozi & Bruno Serra & Lucas Paiva & Zita Vale, 2019. "IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach," Future Internet, MDPI, vol. 11(3), pages 1-21, March.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:3:p:58-:d:210478
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    References listed on IDEAS

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    1. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
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    Cited by:

    1. Guoying Lin & Yuyao Yang & Feng Pan & Sijian Zhang & Fen Wang & Shuai Fan, 2019. "An Optimal Energy-Saving Strategy for Home Energy Management Systems with Bounded Customer Rationality," Future Internet, MDPI, vol. 11(4), pages 1-16, April.

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