Analysis of the Effectiveness of IoT-Based Automatic Street Lighting Control Using Linear Regression Method - Saputra, Tino; Surapati, Untung (Lembaga Komunitas Informasi Teknologi Aceh (KITA), 2024)
Public street lighting (PJU) is a crucial component of infrastructure that ensures security during nighttime. This research aims to design an automatic PJU control system utilizing Internet of Things (IoT) technology, employing light and motion sensors integrated with an ESP32 microcontroller. The system enables remote control of PJU lamps via a web-based platform, offering significant flexibility for users. The ESP32 microcontroller is linked to a PIR sensor that detects motion, which triggers an increase in the intensity of the PJU lamps. Conversely, when no motion is detected, the light intensity is reduced to conserve energy. Users can manage the PJU lamps from any internet-connected device. Experimental results demonstrate a notable improvement in energy efficiency, with an average reduction in power consumption of 13.77 watts and an efficiency increase of 42.67%. The linear regression model employed yields an R-squared value of 0.629, indicating a reasonably good fit in explaining the variability in power consumption. This system offers real-time monitoring and autonomous operation of street lights, contributing to the advancement of smarter and more efficient PJU systems.