Deploying Lightweight AI models for Predictive Maintenance in Industrial IoT environments

This paper explores the use of optimized deep learning models – such as quantized and pruned networks that can detect anomalies and predict failures in real – time. This reduces reliance on cloud connectivity by enabling on device inference, thereby reducing latency and improving data privacy. The growing adoption of Industrial Internet of Things (IIoT) has created a need for intelligent and scalable solutions to monitor equipment health and ensure operational continuity