Volume : 12, Issue : 4, APR 2026

REAL-TIME ENERGY MONITORING AND COST ESTIMATION USING AN IOT-ENABLED SMART METERING SYSTEM

K. BHARATHI*, K.VENU, K.SRINIVASARAO, M.MANOHAR, R.NARAYANARAO

Abstract

The increasing demand for efficient energy utilization necessitates the development of intelligent monitoring systems capable of real-time data acquisition and analysis. Conventional energy meters lack the capability to provide continuous monitoring and remote accessibility, resulting in inefficient energy management. This paper presents the design and implementation of an Internet of Things (IoT)-enabled smart energy meter capable of real-time measurement of electrical parameters such as voltage, current, and energy consumption along with cost estimation. The proposed system integrates voltage and current sensors with a microcontroller-based processing unit to compute instantaneous power and cumulative energy consumption. The system transmits data through IoT communication modules, enabling remote monitoring via mobile or cloud platforms. Additionally, GSM-based communication is incorporated for user interaction and alert notifications. Experimental validation demonstrates accurate measurement and real-time visualization of electrical parameters. The developed system provides a cost-effective, scalable, and efficient solution for modern smart grid and energy management applications.

Keywords

IOT ENERGY METER, SMART METERING, REAL-TIME MONITORING, VOLTAGE SENSOR, CURRENT SENSOR, GSM COMMUNICATION, ENERGY COST ESTIMATION, EMBEDDED SYSTEMS.

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IESRJ

International Educational Scientific Research Journal

E-ISSN: 2455-295X

International Indexed Journal | Multi-Disciplinary Refereed Research Journal

ISSN: 2455-295X

Peer-Reviewed Journal - Equivalent to UGC Approved Journal

Peer-Reviewed Journal

Article No : 7

Number of Downloads : 39

References

1. Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., &Hancke, G. P., “Smart Grid Technologies: Communication Technologies and Standards,” IEEE Transactions on Industrial Informatics, vol. 7, no. 4, pp. 529–539, 2011.

2. Alam, M. R., Reaz, M. B. I., & Ali, M. A. M., “A Review of Smart Homes—Past, Present, and Future,” IEEE Transactions on Systems, Man, and Cybernetics: Part C, vol. 42, no. 6, pp. 1190–1203, 2012.

3. Kabalci, Y., “A Survey on Smart Metering and Smart Grid Communication,” Renewable and Sustainable Energy Reviews, vol. 57, pp. 302–318, 2016.

4. Depuru, S. S. S. R., Wang, L., &Devabhaktuni, V., “Smart Meters for Power Grid: Challenges, Issues, Advantages and Status,” Renewable and Sustainable Energy Reviews, vol. 15, no. 6, pp. 2736–2742, 2011.

5. Zhang, Y., Wang, L., Sun, W., Green, R. C., &Alam, M., “Distributed Intrusion Detection System in a Multi-Layer Network Architecture of Smart Grids,” IEEE Transactions on Smart Grid, vol. 2, no. 4, pp. 796–808, 2011.

6. Hancke, G. P., de Carvalho e Silva, B., &Hancke Jr, G. P., “The Role of Advanced Sensing in Smart Cities,” Sensors, vol. 13, no. 1, pp. 393–425, 2013.

7. Mohsenian-Rad, A. H., Wong, V. W. S., Jatskevich, J., Schober, R., & Leon-Garcia, A., “Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid,” IEEE Transactions on Smart Grid, vol. 1, no. 3, pp. 320–331, 2010.

8. Palattella, M. R., Dohler, M., Grieco, A., Rizzo, G., Torsner, J., Engel, T., &Ladid, L., “Internet of Things in the 5G Era: Enablers, Architecture, and Business Models,” IEEE Journal on Selected Areas in Communications, vol. 34, no. 3, pp. 510–527, 2016.

9. Zhou, K., Fu, C., & Yang, S., “Big Data Driven Smart Energy Management: From Big Data to Big Insights,” Renewable and Sustainable Energy Reviews, vol. 56, pp. 215–225, 2016.

10. Raza, S., Wallgren, L., & Voigt, T., “SVELTE: Real-Time Intrusion Detection in the Internet of Things,” Ad Hoc Networks, vol. 11, no. 8, pp. 2661–2674, 2013.