<![CDATA[The availability of electrical energy is a crucial factor in maintaining the continuity of broadcasting station operations. Public Broadcasting Institution (LPP) TVRI North Sulawesi, where a generator set (genset) is used as a backup power source during interruptions to the main electrical supply. The primary challenge is the limited capability of conventional monitoring systems to observe electrical parameters, including current, power, energy consumption, and power source status, in real time. This study aims to develop an Internet of Things (IoT)-based generator energy monitoring system using an ESP32 microcontroller, SCT-013 current sensor, Liquid Crystal Display (LCD), and cloud-based monitoring platforms. The proposed system measures electrical parameters in real time and transmits the data via a Wi-Fi network to the Blynk application and Google Spreadsheet, enabling remote monitoring by operators. Experimental results show that the proposed system measures electrical current with a measurement error ranging from 1% to 8%, yielding an average error of 4.17% and an average measurement accuracy of 95.83% compared with a reference clamp meter. The system also successfully calculates electrical power up to 2,640 W at a current of 15 A, automatically records monitoring data in Google Spreadsheet, and displays real-time information through the Blynk application when a Wi-Fi connection is available. Furthermore, the system accurately detects PLN ON, Generator ON, and both sources OFF conditions based on current variations in the Automatic Transfer Switch (ATS). The main contribution of this study is the development of an integrated IoT-based generator energy monitoring system capable of measuring electrical current, calculating power and energy consumption, detecting PLN–generator switching status through the ATS, storing historical data in Google Spreadsheet, and providing real-time monitoring and notifications via the Blynk platform to support reliable energy management in broadcasting stations. These results demonstrate that the proposed system provides reliable real-time generator monitoring and improves the effectiveness of monitoring, data logging, and maintenance activities, thereby enhancing the reliability of the electrical system at TVRI North Sulawesi Broadcasting Station.]]>
