Skip to content
Open access

Internet of things-enabled smart monitoring of induction motors for industrial applications

Aug 2026 · Bulletin of Electrical Engineering and Informatics · 0 citations · 37 references

TL;DR

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.

Abstract

AC motors, particularly induction motors, remain the most widely used machines in industrial applications due to their simplicity, robustness, and efficiency. Given their critical role, continuous monitoring and regulation of induction motor parameters are essential to ensure reliability and prevent unexpected failures. This research presents an internet of things (IoT-based) system for real-time monitoring and control of a three-phase induction motor. Various sensors are employed to measure key parameters such as motor temperature, current, and voltage, with the collected data transmitted to a processing unit and displayed on a server for remote access. To enhance fault resilience, the system integrates both automatic and manual control mechanisms for starting or stopping motors under abnormal conditions. The proposed approach enables continuous monitoring, early fault detection, and predictive maintenance, thereby improving overall operational efficiency and reducing downtime. Induction motors, first introduced by Nikola Tesla, account for over 50% of global electricity consumption and are deployed in nearly 90% of industrial operations. Their dominance stems from inherent advantages, including being self-starting, cost-effective, reliable, and maintenance-friendly, as well as offering a strong power factor, compact design, and high efficiency. By leveraging IoT technology, this work bridges the gap between traditional motor operation and modern Industry 4.0 practices, providing a scalable solution for smart industrial environments.

Read PDF

Similar papers

Review Open access Jun 2026

Survey on Smart Embedded Platforms for Motor Condition and Severity Analysis

The suggested innovation refers to a smart embedded system to monitor the operational state of an induction motor and analyze fault levels in real time and provides local monitoring along with IoT-based remote transmission.

C. R, Byra Reddy G R, Chaithra S et al. · 0 citations
Open access Jun 2026

Smart Energy Management and Surveillance Using Internet of Things

The design and execution of a low-cost, locally adjustable smart energy monitoring and load control system for residential and small-scale industrial applications and the results show that low-cost IoT-based devices can improve energy efficiency, cut expenses.

W. Bello, Miriam I. Chukwuma- Uchegbu, A. Abdul et al. · 0 citations
Conference Jul 2026

An IoT-based Real-Time Health Monitoring System for Industrial Machines using ESP32 and Cloud-based Automated Shutdown

Industrial machinery operating in manufacturing and process environments is frequently subjected to adverse operating conditions such as excessive temperature rise, abnormal current consumption, and mechanical vibrations, which may lead to performance degradation, unexpected failures, production losses, and safety haza...

Sudharshana, Kratika V Ulman, Kishan K Kulal et al. · 0 citations
Conference Aug 2026

Smart AI-Integrated System for Predictive Maintenance and Condition Monitoring in Industries

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. · 0 citations
Open access Aug 2026

Monitoring and Analysis of Induction Motor Behavior Using Haiwell Cloud SCADA with Tension Control Method

Haiwell Cloud SCADA-based monitoring system to analyze the behavior of induction motors in real-time voltage, current, speed, frequency, and temperature, and a tension control method using a magnetic powder brake to simulate changes in the load dynamically is offered.

Hanif Rifai Adha, Daeng Rahmatullah, Danang Arengga W · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.