IoT-Based Power Monitoring System

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 16 | 01 | Page :
    By

    Swapnil Takale,

  • Altaf Mulani,

  • Vaibhav Godase,

  • Rahul Ghodake,

  1. Assistant Professor, Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur, Maharashtra, India
  2. Assistant Professor, Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur, Maharashtra, India
  3. Assistant Professor, Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur, Maharashtra, India
  4. Assistant Professor, Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur, Maharashtra, India

Abstract

Today, in many smart systems, IOT plays an important role. It is mostly used in power monitoring, Household applications, and also in industrial applications. In that, power is the most important thing that is to be monitored, controlled and properly utilized. In this paper, a system is designed for monitor and control the street lights of particular area. With the help of LDR, power consumption is possible. Customers and system operators can view real-time energy use patterns with an intuitive web-based dashboard. Users can obtain important insights into their electricity consumption through graphical representations and historical data analysis, which facilitates more efficient load management, energy conservation, and cost optimization. By giving end users comprehensive and easily accessible information, the suggested smart energy meter improves energy use transparency. Additionally, it supports the shift to intelligent energy management systems by enhancing energy efficiency and facilitating informed decision-making. The design, which makes use of IoT technology, is a major step toward the modernization of smart grids and sustainable energy management systems. It also marks a substantial improvement in smart metering infrastructure. Users can view energy statistics from any location with internet connectivity thanks to the system’s remote monitoring capabilities.This system is useful to measure the electrical quantities like voltage, current, power, frequency, and power 2 factor. By using the WI-FI module, all these quantities will be sent to the Thingspeak. Things peak is the server or software-based application that is used to store all this data and will be updated automatically.

Keywords: Arduino, IOT, PZEM004T meter, WI-FI module, LDR

How to cite this article:
Swapnil Takale, Altaf Mulani, Vaibhav Godase, Rahul Ghodake. IoT-Based Power Monitoring System. Journal of Power Electronics and Power Systems. 2026; 16(01):-.
How to cite this URL:
Swapnil Takale, Altaf Mulani, Vaibhav Godase, Rahul Ghodake. IoT-Based Power Monitoring System. Journal of Power Electronics and Power Systems. 2026; 16(01):-. Available from: https://journals.stmjournals.com/jopeps/article=2026/view=238830


References

1. Khan F, Siddiqui MA, Rehman AU, Khan J, Asad MT, Asad A. IoT based power monitoring system for smart grid applications. In2020 international conference on engineering and emerging technologies (ICEET) 2020 Feb 22 (pp. 1-5). IEEE.

2. Gopal M, Prakash TC, Ramakrishna NV, Yadav BP. IoT based solar power monitoring system. InIOP conference series: materials science and engineering 2020 Dec 1 (Vol. 981, No. 3, p. 032037). IOP Publishing.

3. Krishna Rao C, Sahoo SK, Yanine FF. An IoT-based intelligent smart energy monitoring system for solar PV power generation. Energy Harvesting and Systems. 2024 Jan 29;11(1):20230015.

4. Nayyef IM, Husein AA. Design and implementation of IoT based smart power monitoring and management system using WSNS. International Journal of Embedded Systems and Applications (IJESA). 2018 Dec;8(4):1-6.

5. Zhao L, Matsuo IB, Zhou Y, Lee WJ. Design of an industrial IoT-based monitoring system for power substations. IEEE Transactions on Industry Applications. 2019 Sep 10;55(6):5666-74.

6. Rani DP, Suresh D, Kapula PR, Akram CM, Hemalatha N, Soni PK. IoT based smart solar energy monitoring systems. Materials Today: Proceedings. 2023 Jan 1;80:3540-5.

7. Mudaliar MD, Sivakumar N. IoT based real time energy monitoring system using Raspberry Pi. Internet of Things. 2020 Dec 1;12:100292.

8. Patil SM, Vijayalashmi M, Tapaskar R. IoT based solar energy monitoring system. In2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) 2017 Aug 1 (pp. 1574-1579). IEEE.

9. Ghosh S. Neuro-fuzzy-based IoT assisted power monitoring system for smart grid. IEEE Access. 2021 Dec 23;9:168587-99.

10. Nuhin MI, Shariar MA, Khan JM, Kongkon TN, Imam MH. Design of an IoT based power monitoring system model for a grid connected solar PV. International Journal of Advanced Technology and Engineering Exploration. 2022 Jul 1;9(92):923.

11. Khandel H, Pandey S, Reynolds D. IoT based power consumption monitoring and controlling system. International Research Journal of Engineering and Technology (IRJET). 2018;5(7):2211-8.

12. Kambale A. Home automation using google assistant. UGC care approved journal. 2023;32(1):1071-7. 11

13. ABHANGRAO MR, JADHAV MS, GHODKE MP, MULANI A. Design And Implementation Of 8-bit Vedic Multiplier. International Journal of Research Publications in Engineering and Technology (ISSN No: 2454-7875). 2017 Mar.

14. Gadade B, Mulani AO, Harale AD. Iot based smart school bus and student monitoring system. Naturalista Campano. 2024;28(1):730-7.

15. Mulani DA. A Comprehensive Survey on Semi-Automatic Solar-Powered Pesticide Sprayers for Farming. Journal of Energy Engineering and Thermodynamics (JEET) ISSN. 2024:2815-0945.

16. Salunkhe DS, Mulani DA. Solar Mount Design Using High-Density Polyethylene. NATURALISTA CAMPANO. 2024;28(1).

17. Mulani AO, Jadhav MM, Seth M. Painless machine learning approach to estimate blood glucose level with non-invasive devices. InArtificial intelligence, internet of things (IoT) and smart materials for energy applications 2022 Oct 12 (pp. 83-100). CRC Press. 18. Pol DR. Cloud Based Memory Efficient Biometric Attendance System Using Face Recognition. Stochastic Modeling & Applications. 2021;25(2).

Ahead of Print Subscription Review Article
Volume 16
01
Received 22/01/2026
Accepted 27/01/2026
Published 19/03/2026
Publication Time 56 Days
34

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