Real-Time Monitoring of Solar Battery and Lamp Conditions Using Internet of Things - Affan Bachri; Arief Budi Laksono; Eko Wahyu Santoso; Achmad Rifqi Adi Firmansyah (Universitas Nurul Jadid, 2026)
Solar photovoltaic battery systems require continuous observation to prevent unnoticed voltage decline, abnormal temperature, and lamp failure. This study developed a compact Internet of Things monitoring prototype using an ESP32 microcontroller, an INA219 sensor for voltage, current, and power, an LM35 sensor for battery temperature, and a light-dependent resistor for lamp-state detection. Sensor data were shown locally on a 16x2 liquid-crystal display and transmitted through Wi-Fi to a Blynk dashboard at a five-second update interval. The study applied experimental and engineering research procedures covering hardware design, software integration, component validation, and integrated tests under off, three load, and charging conditions. The INA219 achieved average accuracies of 99.69% for voltage, 99.32% for current, and 99.49% for power, while the LM35 reached 97.08% accuracy. The light sensor correctly separated the tested off condition at 3 lux from lamp-on conditions between 230 and 2100 lux. Across all operating modes, the local display and Blynk presented consistent measurements, and negative current reliably indicated charging. The prototype therefore provides accessible real-time monitoring of battery electrical behavior, temperature, charging direction, and lamp status, although long-term data logging and field-scale validation remain necessary.