Direct Illuminance-Contribution-Based Lighting Control for IoT-Based Lighting Systems in Smart Buildings

Author:

Kim Dae Ho1ORCID,Jeon Seung Hyun2ORCID,Sung Jung-Sik1

Affiliation:

1. Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of Korea

2. Department of Computer Engineering, Daejeon University, Daejeon 35235, Republic of Korea

Abstract

With the advent of low-voltage light-emitting diodes (LEDs) and advances in Internet of Things (IoT) technologies, smart buildings have recently become more energy efficient. Nevertheless, the lighting-control system is one of the major sources of electrical energy consumption in commercial buildings. This study proposes a direct illuminance-contribution-based lighting-control framework to reduce the energy of LED luminaires and ensure illuminance for user requirements in smart buildings. Specifically, we designed a direct illuminance-contribution-based lighting-control algorithm (DIC-LCA) using luminaires that are ideally axisymmetric with all light emitted below the horizontal plane and developed a WiFi lighting controller for the IoT-based lighting-control systems in smart buildings. The DIC-LCA can adjust the dimming level by calculating the illuminance based on the line of sight (LOS) distance for energy saving and user satisfaction. After simulation analysis, we prove that energy savings can be achieved by controlling the dimming levels of LED luminaires with high light contribution.

Funder

Ministry of Trade, Industry and Energy

Publisher

MDPI AG

Reference38 articles.

1. Nair, G.B., and Dhoble, S.J. (2020). The Fundamentals and Applications of Light-Emitting Diodes, Woodhead Publishing.

2. Sensorless illumination control of a networked LED-lighting system using feedforward neural network;Tran;IEEE Trans. Ind. Electron.,2014

3. A Dimmable LED Driver With Resistive DAC Feedback Control for Adaptive Voltage Regulation;Lohaus;IEEE Trans. Ind. Appl.,2015

4. Daylighting Control and Simulation for LED-Based Energy-Efficient Lighting Systems;Boscarino;IEEE Trans. Ind. Inf.,2016

5. (2023, December 07). EIA, Available online: https://www.eia.gov/consumption/commercial/reports/2012/lighting.

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