IoT-Based Real-Time Monitoring and Energy Consumption Analysis for Residential Electrical Systems

Ferdiansyah; Agus Salim Wardana

Authors

Ferdiansyah Sekolah Tinggi Teknologi Nusantara Lampung
Agus Salim Wardana Sekolah Tinggi Teknologi Nusantara Lampung

Keywords:

internet of things, real-time energy monitoring, residential electrical systems, energy consumption analysis, smart energy management

Abstract

The growing demand for efficient and transparent household energy management has increased the need for accurate, real-time electricity monitoring systems. This study presents the design, implementation, and experimental validation of an Internet of Things (IoT)-based system for real-time monitoring and analysis of residential electrical energy consumption. The proposed system integrates voltage and current sensing with wireless data transmission to measure voltage, current, instantaneous power, energy consumption (kWh), power factor, and electricity cost estimation, with data displayed locally and remotely through a cloud-based platform. An experimental methodology was employed to evaluate system performance using various household appliances representing resistive and inductive loads. Measurement accuracy was assessed by comparison with calibrated reference instruments, yielding an average voltage error of 0.30% and current error of 0.28%, indicating high precision suitable for residential applications. The results reveal significant variation in energy consumption across appliances, highlighting inefficient loads with disproportionate energy usage. The system demonstrates stable data synchronization between local and remote interfaces with acceptable transmission latency, and incorporates automated load control to support demand-side energy management. This study contributes to the field of smart energy systems by providing a cost-effective, accurate, and scalable IoT-based solution for appliance-level energy monitoring and consumption analysis. The proposed approach offers practical insights for data-driven energy conservation, supports predictive energy management strategies, and aligns with global efforts toward sustainable and intelligent residential power systems.

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