IOT – Integrated Adaptive Edge Intelligence for Predictive Diagnostics In Smart Industrial Environments

Authors

  • Dr S Suganthi Dept. of ECE, Velammal Engineering College., Chennai, Tamilnadu, India Author
  • Tharani J Dept. of ECE, Velammal Engineering College., Chennai, Tamilnadu, India Author
  • Yuvashree K Dept. of ECE, Velammal Engineering College., Chennai, Tamilnadu, India Author
  • Sanjana M Dept. of ECE, Velammal Engineering College., Chennai, Tamilnadu, India Author

DOI:

https://doi.org/10.47392/IRJAEH.2026.0283

Keywords:

Embedded Systems, IoT devices, Real-Time Monitoring, Sensor Data Acquisition, STM32, Machine Learning

Abstract

The operation of machines continuously is essential in productivity, and breakdowns lead to downtimes, repairs and utilities. This paper provides a predictive diagnostic system based on Adaptive Edge Intelligence in industries. On the edge devices, real-time sensor data is preprocessed, features extracted and anomalies identified and this minimizes the latency and reliability. Patterns are updated by adaptive learning according to changes in situations. ThingSpeak cloud facilitates monitoring and visualization, warning generation, better prediction accuracy, response time, safety, productivity, and less downtime.

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Published

2026-04-27

How to Cite

IOT – Integrated Adaptive Edge Intelligence for Predictive Diagnostics In Smart Industrial Environments . (2026). International Research Journal on Advanced Engineering Hub (IRJAEH), 4(04), 2128-2135. https://doi.org/10.47392/IRJAEH.2026.0283