Implementation of an IoT-Based Control and Monitoring System for Neon Box Conditions in the Electrical Engineering Building - Hikmatul Amri; Zulkifli Zulkifli; Stephan Stephan; Hardi B; Ilham Haris; Azzahra Zulaika; Riski Kurniansyah; Jefri Lianda; Marzuarman Marzuarman (Program Studi Teknik Elektro Universitas Khairun, 2026)
The implementation of an Internet of Things (IoT)-based control and monitoring system for the neon box at the Electrical Engineering Department Building aims to improve operational efficiency, installation safety, and the effectiveness of outdoor lighting maintenance. As an information medium and building identity, the neon box requires real-time monitoring of power, voltage, current, light intensity, and operational status. In this study, a system was designed and implemented using a NodeMCU ESP8266 microcontroller as the main controller, a PZEM-004T sensor to measure voltage, current, and power, a TSL2561 lux sensor to read the light intensity produced by the neon box, and a relay module as an actuator to control the neon box lamp. The Blynk IoT platform is used as the interface to display monitoring data and control the neon box remotely. The system is capable of sending data periodically to the server and displaying information such as voltage, current, power, energy, and illumination levels through a digital dashboard, allowing users to monitor the neon box condition at any time via a smartphone. In addition to monitoring functions, the relay module integrated with the IoT system enables operators to remotely turn the neon box on or off through the Blynk IoT application. The Blynk IoT interface successfully displays four main parameters: voltage, electrical power, lumen, and neon box status at the Electrical Engineering Building. The PZEM-004T sensor achieved an average reading error of 0.66% for voltage and 2.53% for current, while the TSL2561 sensor had an average error of 1.42%. The system can detect lamp failure through combined voltage and power readings, with a response time of 0.856 seconds on the Blynk IoT application, which is influenced by internet network quality.