IOT-BASED SMART ENERGY METER MONITORING WITH THEFT CONTROL

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Keywords

Electricity Theft Detection
Energy Usage Tracking
Real-time Monitoring
Remote Control
Safety Preventive Measures

How to Cite

Chong Hock Siong. (2025). IOT-BASED SMART ENERGY METER MONITORING WITH THEFT CONTROL. Journal of Engineering & Technological Advances , 9(2), 115-130. https://doi.org/10.35934/segi.v9i2.122

Abstract

Electricity theft is an escalating issue, worsened by global warming, which contributes to unbalanced power supply and increased safety concerns. Unauthorized power usage exceeding supply limits often leads to system shutdowns and reduced transmission efficiency. Illegal circuit bypassing has also caused fires, resulting in property damage and threats to public safety. This study presents the design and development of a real-time Internet of Things (IoT)-based smart meter using Arduino technology to monitor energy usage and detect electricity theft. The proposed system involves partial circuit simulation and the development of a full prototype using a direct current (DC) circuit. A Global System for Mobile Communications (GSM) module is integrated to provide remote monitoring and control through Short Message Service (SMS), offering reliable and cost-effective connectivity. When theft is detected, the system triggers a buzzer alarm, displays warnings, and sends power shutdown alerts via GSM. Authorities can then intervene using SMS commands to restore safety. Energy consumption is monitored in real time with updates every 30 seconds. The prototype was tested and successfully validated, showing a maximum error margin of 18% when comparing real and measured power data. The system demonstrated efficient theft detection, real-time monitoring, and remote power control capabilities. This study confirms the feasibility of an Arduino-GSM-based IoT smart meter for real-time electricity monitoring and theft detection. The proposed solution enhances grid safety and efficiency by providing accurate energy tracking, early warning systems, and remote intervention tools.

https://doi.org/10.35934/segi.v9i2.122

References

Bayram, I. S., & Ustun, T. S. (2017). A survey on behind the meter energy management systems in smart grid. Renewable and Sustainable Energy Reviews, 72, 1208-1232.

Behrendt, F. (2019). Cycling the smart and sustainable city: analyzing EC policy documents on internet of things, mobility and transport, and smart cities. Sustainability, 11(3), 763.

Deb, S., Bhowmik, P. K., & Paul, A. (2011). Remote detection of illegal electricity usage employing smart energy meter-A current based technique. In ISGT2011-India. (pp. 391-395). IEEE.

Depuru, S. S. S. R., Wang, L., Devabhaktuni, V., & Gudi, N. (2011). Smart meters for power grid—Challenges, issues, advantages and status. In 2011 IEEE/PES Power Systems Conference and Exposition (pp. 1-7). IEEE.

Every, J., Li, L., & Dorrell, D. G. (2017). Leveraging smart meter data for economic optimization of residential photovoltaics under existing tariff structures and incentive schemes. Applied Energy, 201, 158-173.

Gatsis, K., & Pappas, G. J. (2017). Wireless control for the IOT: Power, spectrum, and security challenges. In Proceedings of the Second International Conference on Internet-of-Things Design and Implementation (pp. 341-342).

Hossain, M. R., Oo, A. M. T., & Ali, A. S. (2010). Evolution of smart grid and some pertinent issues. In 2010 20th Australasian Universities Power Engineering Conference (pp. 1-6). IEEE.

Jiang, R., Lu, R., Lai, C., Luo, J., & Shen, X. (2013). Robust group key management with revocation and collusion resistance for SCADA in smart grid. In 2013 IEEE global communications conference (GLOBECOM) (pp. 802-807). IEEE.

Kumar, S., Tiwari, P., & Zymbler, M. (2019). Internet of Things is a revolutionary approach for future technology enhancement: a review. Journal of Big data, 6(1), 1-21.

Langhammer, N., & Kays, R. (2012). Performance evaluation of wireless home automation networks in indoor scenarios. IEEE Transactions on Smart Grid, 3(4), 2252-2261. Lorek, M. C., Chraim, F., & Pister, K. S. (2015). Plug-through energy monitor for plug load electrical devices. In 2015 IEEE SENSORS (pp. 1-4). IEEE.

Maitra, S. (2008). Embedded Energy Meter-A new concept to measure the energy consumed by a consumer and to pay the bill. In 2008 Joint International Conference on Power System Technology and IEEE Power India Conference (pp. 1-8). IEEE.

Pereira, R., Figueiredo, J., Melicio, R., Mendes, V. M. F., Martins, J., & Quadrado, J. C. (2015). Consumer energy management system with integration of smart meters. Energy Reports, 1, 22-29.

Sfar, A. R., Natalizio, E., Challal, Y., & Chtourou, Z. (2018). A roadmap for security challenges in the Internet of Things. Digital Communications and Networks, 4(2), 118-137.

Umang, P., & Mitul, M. (2015). A review on smart meter system. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, 3(12), 70-73.

Vadda, P., & Seelam, S. M. (2013). Smart metering for smart electricity consumption, Blekinge Institute of Technology, Karlskrona, Sweden.

Visalatchi, S., and Sandeep, K.K. (2017). Smart energy metering and power theft control using arduino & GSM, 2nd International Conference for Convergence in Technology (I2CT) (pp. 858-961), IEEE.

Yao, H. W., Wang, X. W., Wu, L. S., Jiang, D., Luo, T., & Liang, D. (2018). Prediction method for smart meter life based on big data. Procedia engineering, 211, 1111-1114.

Zhou, J., Cao, Z., Dong, X., & Vasilakos, A. V. (2017). Security and privacy for cloud-based IoT: Challenges. IEEE Communications Magazine, 55(1), 26-33.

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