Integrating AWS IoT and Kafka for Real-Time Engine Failure Prediction in Commercial Vehicles Using Machine Learning Techniques

Vishwanadham Mandala

Abstract: Commercial vehicle-connected services can reduce costs and improve safety and vehicle management. Using AWS IoT Core, data is forwarded to applications in the AWS environment for real-time insights. A prototype composed of AWS IoT Core, AWS IoT Rules, Apache Kafka, and Kafka Streams predicts engine failures in commercial vehicles. Data is preprocessed using Kafka Streams for machine learning model predictions. This solution meets requirements and aims to prevent accidents through practical and cost-effective interventions. The challenge is ensuring satisfactory performance with AWS Lambda for predictions. The application uses a simplified IoT application with AWS Cloud Services and Kafka Streams.

Keywords: Failure Prediction, Industry 4.0, Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Smart Manufacturing (SM)