Internet of Things (IoTs)-based three-phase induction motor control for Ethiopian industry

The integration of Internet of Things (IoT) technology into motor control systems enhances real-time monitoring, automation, and precise control over the operational parameters of three-phase induction motors. The system leverages IoT sensors to continuously collect data on motor parameters such as voltage, current, vibration, and temperature, which are transmitted to a cloud-based server. A proportional integral derivative controller (PID), embedded within the IoT platform, dynamically adjusts the motor’s current and voltage supplied to the motors. The material used to implement the research work is an IoT device, Sensors, and IoT platforms. Quantitative evaluations were performed by comparing the motor’s performance with and without the IoT system. In experiments conducted at different load conditions, the IoT-based control system demonstrated overshoot by 25%, an improvement in settling time by 5.0%, and enhanced energy efficiency by 4.61%. The proposed system is to generate maintenance alerts, contributing to a 15% decrease in maintenance costs. The latency in communication was maintained below 100 milliseconds, ensuring real-time responsiveness. These results indicate that the IoT-based control system provides more efficient, advanced, and accurate voltage regulation, current regulation, temperature regulation, energy, power, and vibration regulation, with potential for substantial energy savings and operational cost reductions in industrial applications.

Authors

Publication Details

Journal
Results in Engineering
Published
2026-02-09
DOI
https://doi.org/10.1016/j.rineng.2026.109497
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
0.00
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article

Internet of Things (IoTs)-based three-phase induction motor control for Ethiopian industry

Nagarajan MP Sockalingam S, Velmurugan Paramasivam, Bereket Haile Woldegiorgis, Adimike Getaw Bibeyen
Results in Engineering
Sensorless Control of Electric Motors
article

Internet of Things (IoTs)-based three-phase induction motor control for Ethiopian industry

Nagarajan MP Sockalingam S, Velmurugan Paramasivam, Bereket Haile Woldegiorgis, Adimike Getaw Bibeyen
article en

Abstract

The integration of Internet of Things (IoT) technology into motor control systems enhances real-time monitoring, automation, and precise control over the operational parameters of three-phase induction motors. The system leverages IoT sensors to continuously collect data on motor parameters such as voltage, current, vibration, and temperature, which are transmitted to a cloud-based server. A proportional integral derivative controller (PID), embedded within the IoT platform, dynamically adjusts the motor’s current and voltage supplied to the motors. The material used to implement the research work is an IoT device, Sensors, and IoT platforms. Quantitative evaluations were performed by comparing the motor’s performance with and without the IoT system. In experiments conducted at different load conditions, the IoT-based control system demonstrated overshoot by 25%, an improvement in settling time by 5.0%, and enhanced energy efficiency by 4.61%. The proposed system is to generate maintenance alerts, contributing to a 15% decrease in maintenance costs. The latency in communication was maintained below 100 milliseconds, ensuring real-time responsiveness. These results indicate that the IoT-based control system provides more efficient, advanced, and accurate voltage regulation, current regulation, temperature regulation, energy, power, and vibration regulation, with potential for substantial energy savings and operational cost reductions in industrial applications.

Results in EngineeringVol. 29
Affordable and clean energy
Openalex Percentile: Top 62%
Sensorless Control of Electric Motors
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Internet of Things (IoTs)-based three-phase induction motor control for Ethiopian industry — Nagarajan MP Sockalingam S, Velmurugan Paramasivam, et al. · Results in Engineering (2026) | TGRS Research Map | TGRS