Implementation of Smart LED Lighting and Efficient Data Management System for Buildings. (December 2017)

• Record Type: Journal Article
• Authors: Kumar, Arun; Kar, Pushpendu; Warrier, Rakesh; Kajale, Aditi; Panda, Sanjib Kumar
• Is Part Of: Energy procedia. Volume 143(2017)
• Page Start: 173
• Page End: 178
• Publication Date: 2017-12
• Subjects: visual comfort -- wireless sensor -- actuator network -- database management system -- personal -- automatic control; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.12.667
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Recent studies have shown that energy-efficient smart LED lighting systems provide a better visual comfort-working environment at a reduced energy consumption compared to existing lighting systems. Present daylighting systems are able to regulate the light intensities via communication technologies utilizing smart sensors. This paper presents implementation of a smart LED lighting system utilizing different energy-efficient techniques without compromising the visual comfort of occupants. The proposed lighting system uses ZigBee and Wi-Fi communication protocols to control the lights of commercial/residential buildings according to natural daylight, occupancy or as per the requirements of the inhabitants of the building. The lighting system can be operated in three different modes: Manual, Auto, and Hybrid to account for various applications. A wireless sensor and actuator network (WSAN) is used to collect available data, regarding the usage of personalised smart LED lights by occupants in the building. A complete design and implementation of the smart lighting system are presented in the paper. The paper also presents the detailed test-bed implementation of the proposed smart lighting technique and data management system to illustrate the impact of the proposed lighting system on energy consumption and occupants' visual satisfaction. The proposed lighting system aims to reduce energy consumption by 60-70% compared to the existing lighting system while satisfying the visual comfort of the occupants. The proposed work also suggests the guidelines to incorporate intelligence into the system such that it can automatically predict the occupant preferences in a decentralized framework for better visual comfort and improved energy utilization in existing buildings.