Computational Intelligence Algorithm Implemented in Indoor Environments based on Machine Learning for Lighting Control System

Abstract

Over the past decade, engineers and scientists dedicated a significant amount of effort and time to enhance an indoor system embedded with the state-of-the-art automation. Through innovative implementation of sensors, IoT and machine learning algorithm, the designing of indoor lighting control systems evolved over the period. Our research is based upon the development of a highly intelligent lighting system that will be cost effective and at the same time easily accessed in a remote mode. Devices like Ultra-wide band sensors and Lux sensors were collected and utilized in the designing of the system to retrieve information about the user’s location and existing brightness in the room, respectively. These data were then preprocessed, scaled and transmitted to various machine learning algorithms to predict suitable lighting condition. The application of our proposed lighting system will always keep the brightness range to a recommended level of 200-400 Lux which is extremely compatible for its use in homes, offices, schools and high rage apartments. In addition, the remote access facility allows users to operate the system anywhere in the world providing user experience beyond imagination. Lastly, as the system comprises of low-cost components that are also easily replaceable and only provide lighting when needed, it can provide savings in terms of cost and power