1 Department of Electrical and Electronics Engineering, Michael Okpara University of Agriculture, Umudike, Abia State Nigeria.
2 National Centre of Artificial Intelligence and Robotics, Abuja, Nigeria.
3 Department of Electrical Engineering, George Washington University, DIstrict of Columbia, Washington, USA.
4 Department of Civil Engineering, Federal University of Oye Ekiti, Ekiti State, Nigeria.
5 Department of Electrical and Computer Engineering, Florida State University, Tallahassee, Florida, USA.
6 Department of Electrical Engineering, Yaba College of Technology, Lagos, Nigeria.
7 Department of Civil Engineering, Federal University of Technology Akure, Ondo State, Nigeria.
World Journal of Advanced Research and Reviews, 2024, 23(01), 765–769
Article DOI: 10.30574/wjarr.2024.23.1.2054
DOI url: https://doi.org/10.30574/wjarr.2024.23.1.2054
Received on 31 May 2024; revised on 07 July 2024; accepted on 09 July 2024
The traditional approach to energy meter reading is a antiquated practice that is plagued by inefficiencies, inaccuracies, and unnecessary expenses. The costs of manual meter reading are invariably passed on to consumers, adding to their financial burden. Smart energy meters offer a viable solution, but the astronomical cost of replacing existing meters with new ones poses a significant hurdle. However, this paper proposes a innovative solution that leverages the power of IoT technology and Raspberry Pi devices to transform legacy meters into smart prepaid meters without the need for costly replacements. This ground breaking approach enables remote meter monitoring, mobile app control, automated notifications, and seamless integration with existing infrastructure. By harnessing the potential of IoT, this solution revolutionizes energy metering, making it more efficient, convenient, and cost-effective for consumers.
IoT; Energy Management; Sustainability, Cloud Computing; Real-time Monitoring; Artificial Intelligence
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Victor Ikechukwu Stephen, Abdulahi Akintayo Taiwo, Christain Chukwuemeka Nzeanorue, Peter Dayo Fakoyede, Ridwan Olamilekan Jamiu, Samuel Ayanwunmi Olanrewaju, Qudus Omotayo Ajiboye and Ewemade Cornelius Enabulele. Development of an IoT-based smart energy management system for industrial applications. World Journal of Advanced Research and Reviews, 2024, 23(01), 765–769. Article DOI: https://doi.org/10.30574/wjarr.2024.23.1.2054
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