IoT-based cost-effective energy meter monitoring system for smart home applications: Design, implementation, and analysis

This research presents the design, implementation, and analysis of a cost-effective energy meter monitoring system utilizing Internet of Things (IoT) technology for smart home applications. The system aims to address the growing need for efficient energy management, particularly in student housing...

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Bibliographic Details
Main Authors: Ruslan, Eliyana, Abdul Hadi, Dayanasari, Johari, Siti Halma, Md. Rozali, Sahazati, Che Mid, Ernie
Format: Article
Language:en
Published: Human Resource Management Academic Research Society 2024
Online Access:http://eprints.utem.edu.my/id/eprint/28446/2/0206715012025114161597.pdf
http://eprints.utem.edu.my/id/eprint/28446/
https://hrmars.com/papers_submitted/24398/iot-based-cost-effective-energy-meter-monitoring-system-for-smart-home-applications-design-implementation-and-analysis.pdf
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Summary:This research presents the design, implementation, and analysis of a cost-effective energy meter monitoring system utilizing Internet of Things (IoT) technology for smart home applications. The system aims to address the growing need for efficient energy management, particularly in student housing environments where energy consumption awareness is crucial. A novel approach that integrates NodeMCU ESP8266, PZEM-004T current sensor, and a custom-designed mobile application to provide real-time energy consumption data and remote- control capabilities is proposed. The methodology involves a comprehensive system design, hardware integration, and software development using Arduino IDE and MIT App Inventor. The experimental setup monitored energy consumption patterns over a week, analysing both daytime and nighttime usage. Results demonstrate the system's efficacy in tracking power consumption, with notable variations observed between weekdays and weekends. The implemented IoT solution successfully enabled remote monitoring and control of household appliances, potentially leading to significant energy savings. Data analysis revealed peak consumption periods and usage patterns, providing valuable insights for energy management strategies. This cost-effective solution shows promise in promoting energy conservation awareness among users, particularly students, and has potential applications in broader smart city initiatives for sustainable energy management.