IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction

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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 : 04 | 01 | Page :
    By

    Mr. Gaurav B. Landage,

  • Prof. Pragati B. Chandane,

  • Prof. Jagruti R. Mahajan,

  • Dr. Hemant kumar B. Jadhav,

  • Dr. Pradeep M. Patil,

  1. Student, Department of Computer Engineering, Adsul Technical Campus, Ahilyanagar, Maharashtra, India
  2. Assistant Professor, Department of Computer Engineering, Adsul Technical Campus, Ahilyanagar, Maharashtra, India
  3. Assistant Professor, Department of Computer Engineering, Adsul Technical Campus, Ahilyanagar, Maharashtra, India
  4. Assistant Professor, Department of Computer Engineering, Adsul Technical Campus, Ahilyanagar, Maharashtra, India
  5. Principal, Department of Computer Engineering, Adsul Technical Campus, Ahilyanagar, Maharashtra, India

Abstract

Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things (IoT) technology with machine learning (ML) for early defect prediction and real-time condition monitoring in order to get around these restrictions. Using embedded sensors mounted on the motor, the suggested system continuously gathers operating information like temperature, vibration, current, voltage, and rotational speed. An Internet of Things communication infrastructure is used to deliver this sensor information to These sensor readings are transmitted through an IoT communication framework to a cloud-based or edge-processing platform, where the data is stored, processed, and analyzed. Feature extraction techniques are applied to transform raw sensor data into meaningful indicators that reflect the motor’s health condition. Machine learning algorithms are then trained on historical and real-time datasets to identify abnormal patterns, classify fault types, and predict potential failures before they occur, boosting reliability, cutting expenses, and improving the performance of the entire system.

Keywords: Motor Health Monitoring, Predictive Maintenance, Internet of Things (IoT), Machine Learning, Condition Monitoring, Fault Diagnosis, Industrial Automation, Smart Maintenance

How to cite this article:
Mr. Gaurav B. Landage, Prof. Pragati B. Chandane, Prof. Jagruti R. Mahajan, Dr. Hemant kumar B. Jadhav, Dr. Pradeep M. Patil. IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction. International Journal of Electrical Machine Analysis and Design. 2026; 04(01):-.
How to cite this URL:
Mr. Gaurav B. Landage, Prof. Pragati B. Chandane, Prof. Jagruti R. Mahajan, Dr. Hemant kumar B. Jadhav, Dr. Pradeep M. Patil. IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction. International Journal of Electrical Machine Analysis and Design. 2026; 04(01):-. Available from: https://journals.stmjournals.com/ijemad/article=2026/view=240435


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Ahead of Print Subscription Review Article
Volume 04
01
Received 25/03/2026
Accepted 31/03/2026
Published 22/04/2026
Publication Time 28 Days
44

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