• DocumentCode
    2737583
  • Title

    Designing an adaptive lighting control system for smart buildings and homes

  • Author

    Yuan Wang ; Dasgupta, Partha

  • Author_Institution
    Arizona State Univ., Tempe, AZ, USA
  • fYear
    2015
  • fDate
    9-11 April 2015
  • Firstpage
    450
  • Lastpage
    455
  • Abstract
    Lighting control in smart buildings and homes can be automated by having computer controlled lights and blinds along with illumination sensors that are distributed in the building. However, programming a large building light switches and blind settings can be time consuming and expensive. We present an approach that algorithmically sets up the control system that can automate any building without custom programming. This is achieved by making the system self calibrating and self learning. This paper described how the problem is NP hard but can be resolved by heuristics. The resulting system controls blinds to ensure even lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting. Our method works as generic control algorithms and are not preprogrammed for a particular place. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.
  • Keywords
    adaptive control; building management systems; computational complexity; control system synthesis; home automation; learning systems; lighting control; NP hard problem; adaptive lighting control system design; artificial lighting; computer controlled blinds; computer controlled lights; illumination sensors; self calibrating system; self learning system; smart buildings; smart homes; Calibration; Force; Lighting; Lighting control; Sensors; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control (ICNSC), 2015 IEEE 12th International Conference on
  • Conference_Location
    Taipei
  • Type

    conf

  • DOI
    10.1109/ICNSC.2015.7116079
  • Filename
    7116079