Real-Time Monitoring of Household Electrical Power Using IoT for Energy Prediction
Keywords:
internet of things, energy monitoring, arduino, voltage sensor, current sensor, smart home, power managementAbstract
The increasing demand for efficient household energy management necessitates accurate and accessible monitoring solutions. This study presents the design, implementation, and validation of an Internet of Things (IoT)-based electricity monitoring system integrating Arduino Uno, NodeMCU ESP8266, ZMPT101B voltage sensor, and ACS712 current sensor to measure voltage, current, instantaneous power, energy consumption (kWh), power factor, and cost estimation in real time, with data accessible locally via a 2x16 LCD and remotely through a cloud server. Experimental validation was conducted on nine common household appliances representing both resistive and inductive loads, with measurements compared against calibrated reference instruments, yielding an average voltage error of 0.30% and current error of 0.28%, indicating high precision suitable for residential applications. Results revealed substantial variation in energy usage, with incandescent lamps consuming the most energy (0.36 kWh) due to low luminous efficacy and soldering iron consuming the least (0.04 kWh). The system maintained consistent synchronization between local and remote displays with a data transmission latency of 10–15 seconds, and the integrated relay module enabled automated load control based on predefined thresholds, supporting demand-side management strategies. This work offers a cost-effective, accurate, and replicable solution for appliance-level energy monitoring, providing actionable consumption insights to facilitate data-driven decision-making, promote energy conservation, and align with global sustainable energy goals, with future improvements including integration of dynamic pricing models, advanced predictive analytics, and power quality assessment.
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Copyright (c) 2025 Ferdiansyah, Agus Salim Wardana (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
