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
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;
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2015 IEEE 12th International Conference on
Conference_Location :
Taipei
DOI :
10.1109/ICNSC.2015.7116079