Designing an adaptive lighting control system for smart buildings and homes
Yuan Wang, Partha Dasgupta · 2015
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.