Volt Vision

Abstract

Since the world is consuming more power and now it is much worried about sustainability, it is necessary to use intelligence in controlling and monitoring electricity. With a combination of intelligent automation and Internet of Things (IoT), we can monitor energy consumption in real time, automate the control systems, and make better use of energy. Since the world is consuming more power and now it is much worried about sustainability, it is necessary to use intelligence in controlling and monitoring electricity. With a combination of intelligent automation and Internet of Things (IoT), we can monitor energy consumption in real time, automate the control systems, and make better use of energy. This essay describes how smart energy systems through IoT are constructed and deployed. It considers important technologies such as smart meters, edge devices, cloud computing, and machine learning. These materials assist in saving energy, waste reduction, and cost reduction in homes, offices, and factories. It also illustrates how artificial intelligence (AI) and forecasting tools can enable us to plan energy consumption more effectively, load management, and system automation according to real-time data. Intelligent grids—complex energy systems that integrate these technologies—make electricity more secure and enable greater amounts of solar and wind energy. In brief, the paper clearly shows us the way in which AI and IoT are assisting in power monitoring, making our energy infrastructure more intelligent, efficient, and future-ready.

Introduction

Rapid urbanization and technological growth have significantly increased energy consumption across industrial, commercial, and domestic sectors. Traditional energy monitoring methods, relying on manual data collection and post-event analysis, lack real-time capabilities and predictive insights, leading to energy inefficiencies, wastage, and higher costs.

The Internet of Things (IoT) offers a transformative solution by enabling interconnected devices for real-time energy monitoring, analytics, and remote management. IoT-based power monitoring systems combine smart sensors, cloud computing, and AI-driven analytics to optimize energy use, reduce wastage, and lower costs.

Key benefits of IoT-based monitoring include real-time consumption tracking, remote control, automated energy optimization, predictive analytics, and substantial cost savings. This approach supports global efforts to reduce energy consumption and carbon footprints.

The text also reviews several existing IoT-powered energy monitoring projects that use technologies such as Arduino, GSM, Wi-Fi, and Bluetooth for automated meter reading, power management, and consumer alerts, emphasizing the move toward intelligent, automated energy systems.

Finally, the proposed Smart Metering Infrastructure for Intelligent Facilities and IoT (SMIFI) integrates embedded hardware, wireless communication, and cloud visualization to provide a comprehensive, real-time energy monitoring and control platform, addressing limitations of traditional meters.

Conclusion

The development of the Smart Metering Infrastructure for Intelligent Facilities and IoT (SMIFI) has demonstrated an effective approach to modern energy monitoring and control. By integrating the ESP32 microcontroller with the ZMCT102 current sensor, relays, and cloud communication via MQTT, the system delivers real-time insights into power consumption and enables remote appliance control. The web dashboard further enhances user interaction by providing a clear and accessible interface for data visualisation and device management. Overall, SMIFI offers a scalable, cost-efficient solution for smart energy systems, contributing to improved energy efficiency and reduced manual intervention in residential and industrial environments.

References

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Copyright

Copyright © 2025 Prashant Kumar Singh, Amiya Krishna Gupta, Piyush Kumar Jha, Upkar Tiwari, Mayank Deep Khare. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.