USER-CONFIGURABLE VOLTAGE AND CONTROL OF IOT-BASED ELECTRICAL LOAD MONITORING SYSTEM (ELMS) FOR RESIDENTIAL APPLICATIONS
DOI:
https://doi.org/10.35631/IJIREV.826007Keywords:
Electrical Load Monitoring, Embedded Systems, Internet of Things (IoT), Residential Energy Management, User-Configurable VoltageAbstract
The increasing adoption of Internet of Things (IoT) technologies in smart residential environments has intensified the need for scalable and cost-effective electrical load monitoring systems. Most existing IoT-based Electrical Load Monitoring Systems (ELMS) rely on dedicated voltage and current sensing circuits, increasing hardware complexity, calibration requirements, and deployment cost. However, for residential environments with relatively stable supply voltages, continuous voltage sensing provides limited additional benefit while significantly increasing system complexity. This study proposes an IoT-enabled ELMS that replaces dedicated voltage sensing with a cloud-configurable voltage estimation mechanism, enabling real-time power monitoring using only non-invasive current measurements. The proposed system integrates a non-invasive current transformer, an ESP32 microcontroller, and a cloud-based IoT platform to estimate real-time power consumption through user-configurable voltage parameters while supporting wireless data synchronization and remote monitoring. Experimental evaluation under varying load conditions demonstrated accurate real-time power computation, reliable wireless communication, and correct transitions between standby, normal, and overload operating states. Compared with conventional ELMS, the proposed architecture reduces hardware complexity by eliminating dedicated voltage-sensing circuitry while maintaining sufficient accuracy for residential energy monitoring. These findings demonstrate that configurable voltage estimation provides a practical, low-cost, and scalable solution for IoT-based residential energy awareness applications by significantly reducing hardware complexity without compromising real-time monitoring capability.
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