AI-Enabled Predictive Maintenance Framework For Connected Vehicles Using Cloud-Based Web Interfaces

Authors

  • Ravi Shankar Garapati, Dr Suresh Babu Daram

Keywords:

Data acquisition and transmission,Data prepro- cessing and feature extraction,Predictive modeling (e.g., machine learning or deep learning),Maintenance decision rules,Cloud and edge interactions,Web-based visualization and alerts,predictive maintenance, connected vehicle, AI, cloud, web interface.

Abstract

A predictive maintenance framework based on arti- ficial intelligence (AI) is presented. Connected vehicles transmit vehicle-generated data to a cloud server from multiple vehicles. The data is processed with the AI model to forecast vehicle main- tenance requirements and issues and for scheduling maintenance operations in advance. The results—displayed on an easy-to-use, cloud-based web interface—consist of multiple-choice dropdowns to select the desired query for the AI model for processing and forecasting. The web interface facilitates smooth access to the AI process results and allows users to analyze data and identify the maintenance needs of individual connected vehicles.

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How to Cite

Ravi Shankar Garapati, Dr Suresh Babu Daram. 2025. “AI-Enabled Predictive Maintenance Framework For Connected Vehicles Using Cloud-Based Web Interfaces”. Metallurgical and Materials Engineering, August, 75-88. https://metall-mater-eng.com/index.php/home/article/view/1887.

Issue

Vol. 31 No. 7 (2025)

Section

Research

License

Copyright (c) 2025 Ravi Shankar Garapati, Dr Suresh Babu Daram

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