Aug 2026· International Journal for Sciences and Technology· 0 citations· 26 references
TL;DR
Experimental validation demonstrates reliable phase detection, rapid relay response, and effective remote alerting, confirming the system's suitability for industrial automation, motor protection, and smart energy management applications.
Abstract
Three-phase induction motors are extensively utilized in industrial and commercial applications due to their robustness, efficiency, and capability to handle high-power loads. However, these motors are vulnerable to damage from phase failure conditions, including single-phasing, voltage imbalance, and phase loss, which can lead to overheating, reduced efficiency, and permanent equipment failure. This paper presents the design and development of a low-cost, intelligent three-phase monitoring and protection system integrated with Internet of Things (IoT) communication for real-time fault notification. The proposed system employs an Arduino Uno microcontroller as the central processing unit, continuously monitoring the availability of R, Y, and B phases through voltage sensor modules. Upon detection of any phase failure, the system automatically disconnects relay-controlled loads to prevent single-phasing damage. Local status indication is provided through an I2C LCD display and audible buzzer alerts, while remote monitoring is achieved via an ESP32 DevKit module that transmits fault notifications to a Telegram application through Wi-Fi connectivity. The system architecture combines embedded control, automated protection, and wireless communication into a single scalable platform. Experimental validation demonstrates reliable phase detection, rapid relay response, and effective remote alerting, confirming the system's suitability for industrial automation, motor protection, and smart energy management applications.
This research presents an internet of things (IoT-based) system for real-time monitoring and control of a three-phase induction motor that enables continuous monitoring, early fault detection, and predictive maintenance, thereby improving overall operational efficiency and reducing downtime.
Y. S. Pawar, Sandip Rahane, A. Thakare et al.· Bulletin of Electrical Engin...· 0 citations
The proposed framework provides a scalable smart distribution monitoring platform and a future enhancement path towards implementation with hardware, event logging, fault-location techniques and machine-learning based fault classification.
H. Ali, R. Asif, Muhammad Rizwan· Journal of Global Social Tra...· 0 citations
The novelty of this research lies in the integration of a responsive, cost-effective, multi-parameter control and monitoring platform equipped with automatic data logging within a single integrated HMI interface, which is ready to be applied for research as well as industrial automation laboratory practices.
Fahrul Marcello Rombon, Kevind Lefinro Rompas, N. Lombok et al.· Jambura Journal of Electrica...· 0 citations
IoT is one of the significant enabling technologies in the contemporary energy landscape. This work addresses intelligent load management under fault, under-load, and overload conditions. Electrical equipment requires automatic and rapid response to avoid damage and prevent service interruption. In contrast to traditio...
Jeevitha Kandasamy, Kalaivani C, Shashank S Bhagwat et al.· 2026 4th International Confe...· 0 citations
An Internet of Things (IoT)-enabled Automatic Transfer Switch (ATS) monitoring system based on an expert system approach for electrical energy backup to enable adaptive, rule-based decision-making that overcomes the rigidity of conventional fixed-threshold ATS systems.
Rafiuddin Syam, Ara Akdzal Al Tariq, Efri Sandi et al.· SPEKTRA Jurnal Fisika dan Ap...· 0 citations
The Sudden equipment failures are common in industrial systems, which means more downtime and higher maintenance costs. A Smart AI-Integrated Predictive Maintenance and Condition Monitoring System is proposed to solve this problem. It will allow for real-time monitoring and early fault detection in industrial machines....
V. R. Kumar, P. Poornima, M. Abinesh et al.· International Conference on...· 0 citations
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