AI-Based Predictive Fault Detection for Smart Electrical Equipment Using IoT and Machine Learning

• Author(s): Sumathi G; Muthukumar M; Balachandran C; S. Dharun Prabhu
• Paper ID: 1717727
• Page: 1780-1787
• Published Date: 15-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

Abstract

Smart electrical equipment such as transformers, induction motors, generators, and industrial automation systems are critical components in modern industries. Unexpected failures in these systems can cause production interruptions, increased maintenance cost, equipment degradation, and safety hazards. Traditional maintenance strategies, including reactive and preventive maintenance, are often inefficient because they either respond only after failures occur or rely on fixed maintenance schedules without considering real-time equipment conditions. To address these limitations, this paper proposes an AI-driven self-learning failure prediction system for smart electrical equipment using IoT-enabled monitoring and machine learning techniques.The proposed system continuously acquires real-time operational parameters such as temperature and current using embedded sensors integrated with a microcontroller-based edge computing unit. The collected sensor data is processed using machine learning algorithms including Random Forest (RF), Support Vector Machine (SVM), and Long Short-Term Memory (LSTM) networks to identify abnormal operating conditions and predict potential equipment failures. The system incorporates a self-learning mechanism that updates the prediction model using newly acquired operational data, thereby improving fault detection accuracy over time. An IoT-based communication framework provides real-time monitoring and instant fault alerts through cloud-connected applications.

Keywords

Predictive Maintenance, Artificial Intelligence, Internet of Things (IoT), Machine Learning, Smart Electrical Equipment, Failure Prediction, LSTM, Random Forest.

Citations

IRE Journals:
Sumathi G, Muthukumar M, Balachandran C, S. Dharun Prabhu "AI-Based Predictive Fault Detection for Smart Electrical Equipment Using IoT and Machine Learning" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 1780-1787 https://doi.org/10.64388/IREV9I11-1717727

IEEE:
Sumathi G, Muthukumar M, Balachandran C, S. Dharun Prabhu "AI-Based Predictive Fault Detection for Smart Electrical Equipment Using IoT and Machine Learning" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717727