Smart Light Electricity Automation and Monitoring System Based on the Internet of Things (IOT) on Campus Environment Prototype

Efficient management of electrical energy is very important in the campus environment to support energy savings. This research aims to design and implement an Internet of Things (IoT)-based Smart Light system that automates light control and monitors electricity consumption in real-time. The system uses an ESP32 microcontroller integrated with PIR sensor and LDR sensor modules for automatic control, as well as ACS712 current and ZMPT101B voltage sensors to monitor electrical power. The collected data is processed in the microcontroller to calculate the electric power and cost, then displayed through a PHP and MySQL-based web dashboard that can be accessed in real-time. Tests were conducted on the campus prototype, showing an average error of 2.78% for current and 0.086% for voltage on indoor devices, and 2.86% for current and 0.343% for voltage on outdoor devices. The system is proven to be able to control lights automatically based on user presence and lighting conditions. Test results show that the system provides accurate monitoring of electricity consumption while improving operational efficiency. For example, the indoor device has higher accuracy in monitoring consumption data than the outdoor device, even though both devices show optimal performance. This system is expected to support electrical energy savings, improve energy use efficiency, and become an innovative solution in IoT-based energy management on campus.

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Publication Details

Journal
Brilliance Research of Artificial Intelligence
Published
2024-12-28
DOI
https://doi.org/10.47709/brilliance.v4i2.5082
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
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article

Smart Light Electricity Automation and Monitoring System Based on the Internet of Things (IOT) on Campus Environment Prototype

Ramiati Ramiati, Ratna Dewi, J. Mercy Geraldine
Brilliance Research of Artificial Intelligence
IoT-based Smart Home Systems
article

Smart Light Electricity Automation and Monitoring System Based on the Internet of Things (IOT) on Campus Environment Prototype

Ramiati Ramiati, Ratna Dewi, J. Mercy Geraldine
article en

Abstract

Efficient management of electrical energy is very important in the campus environment to support energy savings. This research aims to design and implement an Internet of Things (IoT)-based Smart Light system that automates light control and monitors electricity consumption in real-time. The system uses an ESP32 microcontroller integrated with PIR sensor and LDR sensor modules for automatic control, as well as ACS712 current and ZMPT101B voltage sensors to monitor electrical power. The collected data is processed in the microcontroller to calculate the electric power and cost, then displayed through a PHP and MySQL-based web dashboard that can be accessed in real-time. Tests were conducted on the campus prototype, showing an average error of 2.78% for current and 0.086% for voltage on indoor devices, and 2.86% for current and 0.343% for voltage on outdoor devices. The system is proven to be able to control lights automatically based on user presence and lighting conditions. Test results show that the system provides accurate monitoring of electricity consumption while improving operational efficiency. For example, the indoor device has higher accuracy in monitoring consumption data than the outdoor device, even though both devices show optimal performance. This system is expected to support electrical energy savings, improve energy use efficiency, and become an innovative solution in IoT-based energy management on campus.

Brilliance Research of Artificial IntelligenceVol. 4(2)
State University of Padang (ID)
Openalex Percentile: Top 76%
IoT-based Smart Home Systems
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Smart Light Electricity Automation and Monitoring System Based on the Internet of Things (IOT) on Campus Environment Prototype — Ramiati Ramiati, Ratna Dewi, et al. · Brilliance Research of Artificial Intelligence (2024) | TGRS Research Map | TGRS