Smart Room Lighting System for Energy Efficiency in Indoor Environment

  • Rafika Rizky Ramadhani Politeknik Elektronika Negeri Surabaya
  • Mike Yuliana Politeknik Elektronika Negeri Surabaya
  • Aries Pratiarso Politeknik Elektronika Negeri Surabaya
Abstract views: 54 , PDF downloads: 50
Keywords: Smart Lighting, Smart Room Lighting System, Internet of Things, Fuzzy Logic, Dimming System

Abstract

The building sector absorbs 40% of global energy sources. Energy demand in the building sector is dominated by around 60 – 70% electricity, mainly used for air conditioning, water pumping machines, and lighting. On average, artificial lighting can consume 37% of the total electrical energy needs. Meanwhile, sunlight enters the room through the morning window from noon until the afternoon. Using unnecessary or excessive room lighting when there is a natural light source in the room consumes a relatively large total energy requirement of the building. There is a need for a smart lighting system specifically for indoors for efficient energy management and a lighting control system integrated with IoT, which utilizes the intensity of natural light in a room. In this paper, we proposed that the Smart Room Lighting System uses the fuzzy logic method based on ESP32 to control the lighting in the room to save electricity usage for a room lamp. The result of the tool's design, it can control the light starting from bright, dim, and lights go out. The results obtained by the Smart Room Lighting System can reduce power consumption by up to 93% and energy by up to 70%.

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Author Biographies

Rafika Rizky Ramadhani, Politeknik Elektronika Negeri Surabaya

Dept. of Electrical Engineering

Mike Yuliana, Politeknik Elektronika Negeri Surabaya

Dept. of Electrical Engineering

Aries Pratiarso, Politeknik Elektronika Negeri Surabaya

Dept. of Electrical Engineering

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Published
2022-11-30
How to Cite
Ramadhani, R. R., Yuliana, M., & Pratiarso, A. (2022). Smart Room Lighting System for Energy Efficiency in Indoor Environment. International Journal of Artificial Intelligence & Robotics (IJAIR), 4(2), 48-58. https://doi.org/10.25139/ijair.v4i2.5266