IoT-Based Remote Electricity Control and Management Monitoring System Using Blynk Application - Muksin, Andreanata Pradifta; Tjahjono, Budi (INSPIRETECH GLOBAL INSIGHT, 2025)
Purpose of the study: This research seeks to create an IoT-based system for remote electricity control and monitoring, ensuring precise, real-time energy management through a user-friendly interface. The study emphasizes the design of a cohesive hardware-software system utilizing NodeMCU ESP32, PZEM-004T sensors, relay modules, and the Blynk application, while evaluating performance concerning response time, accuracy, stability, and reliability in domestic settings. Materials and methods: An experimental methodology was adopted, encompassing needs analysis, design, development, implementation, and evaluation phases. The system employs NodeMCU ESP32 as the principal microcontroller, relay modules as electronic switches, PZEM-004T sensors for monitoring electricity usage, and an LCD for information display. It interfaces with the Blynk application for remote control and monitoring, with testing conducted in a controlled household setting to assess response speed, accuracy, stability, and scheduling reliability. Results: The system exhibited exceptional performance, achieving WiFi connectivity within 2 seconds and command execution in under 2 seconds. The PZEM-004T sensor attained over 98% accuracy for voltage, current, power, and energy parameters when compared to calibrated standards. The automatic scheduling feature functioned with a 100% success rate during thorough testing. Real-time data was transmitted every 5 seconds, providing prompt feedback through the Blynk interface and integrated LCD. Conclusions: The IoT-based remote electricity control system presents an innovative solution for household energy management, realizing a 70% enhancement in electricity usage efficiency. It features rapid response times, high accuracy, dependable scheduling, and user-friendly interfaces, catering to users with diverse technical skills. Despite limitations like internet dependency and sensor constraints, it serves as an effective and cost-efficient solution for smart energy management in residential settings.