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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
Publication Fee: 599/- INR
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 7

Published on: July 2026

AN INTELLIGENT PREDICTIVE MAINTENANCE SYSTEM FOR INDUSTRIAL IOT APPLICATIONS

Govind More Shreyas Hon Piyush Kotkar Prof. Jai Rastogi Sakshi Kapse Prof. Rajeshwar Rao

Department of  Artificial Intelligence and Machine Learning ,
Sanjivani University,

Kopargaon, India
DOI:https://doi.org/10.55041/ijcope.v2i7.155

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

Predictive maintenance has become a key application of the Industrial Internet of Things (IIoT), helping industries improve equipment reliability and operational efficiency. Conventional maintenance approaches, such as reactive and preventive maintenance, often result in unexpected equipment failures, increased maintenance costs, and inefficient use of resources. By integrating real-time sensor monitoring with machine learning techniques, predictive maintenance enables early detection of potential faults, allowing maintenance activities to be performed only when necessary. This study presents a real-time predictive maintenance framework for Industrial IoT systems using machine learning. The proposed solution collects live sensor data, including temperature, vibration, and pressure, from industrial equipment. The data is preprocessed and analyzed using Python-based tools before being fed into machine learning models to identify anomalies and predict potential equipment failures. The system provides timely maintenance recommendations, minimizing unplanned downtime and improving overall equipment performance. Experimental results demonstrate that the proposed framework achieves high fault prediction accuracy, enhances system reliability, reduces maintenance costs, and supports data-driven decision-making in industrial environments.

Keywords—Industrial Automation, Machine Learning, Predictive Maintenance, Sensor Networks, Equipment Failure Prediction.

How to Cite this Paper

More, G., Hon, S., Kotkar, P., Rastogi, J., Kapse, S. & Rao, R. (2026). An Intelligent Predictive Maintenance System for Industrial IOT Applications. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(7), 1-9. https://doi.org/10.55041/ijcope.v2i7.155

More, Govind, et al.. "An Intelligent Predictive Maintenance System for Industrial IOT Applications." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i7.155.

More, Govind,Shreyas Hon,Piyush Kotkar,Jai Rastogi,Sakshi Kapse, and Rajeshwar Rao. "An Intelligent Predictive Maintenance System for Industrial IOT Applications." International Journal of Creative and Open Research in Engineering and Management 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i7.155.

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  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Jul 15 2026
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