Development of a portable prototype of energy-saving LED lighting system

Abstract

In Singapore, where corporations and households contribute nearly half of the total energy consumption, there's a pressing need for technologies promoting energy efficiency. This can be achieved partly through regulating indoor electricity use based on room occupancy. Current systems, like Building Management Systems, utilize motion sensors for automatic lighting control, demonstrably reducing energy waste. However, these systems often lack the ability to actively adapt to user room usage needs and personal preferences.

This project addresses this limitation by proposing a room lighting control system that integrates user control with automatic adjustments based on both room occupancy and activity. By combining user preferences with activity recognition through sensors and machine learning, the system would automatically adjust lighting base on needs (such as reading, working, entertainment, emergencies) – maximizing energy savings and user comfort while requiring minimal user intervention. This caters to the need for adaptable lighting solutions in spaces designed for various activities.

A functional proof-of-concept prototype was successfully designed and constructed to simulate the response from human presence, ambient light intensity, and gestures, concluding a potential for more advanced developments of such a system.