AutoSense AI — Giving Every Vehicle a Mind to See Beyond the Road

AutoSense AI is an AI-powered vehicle fault diagnosis system designed to help users identify possible vehicle problems based on the symptoms they observe. The project was inspired by the difficulty of identifying vehicle faults without sufficient technical knowledge. I wanted to build a simple, accessible solution that helps users understand what might be wrong with their vehicles and provides initial troubleshooting suggestions.

I built the project using React, Vite, JavaScript, and rule-based AI. The system asks users to answer Yes/No questions about vehicle symptoms and analyzes their responses to identify possible issues, including battery failure, cooling-system problems, brake issues, low engine oil, and engine performance problems. It then displays a possible diagnosis along with relevant troubleshooting suggestions. I used Bolt AI to help develop the application, connected the project to GitHub for version control, and deployed it using Vercel.

Through this project, I learned how to turn an idea into a working web application, structure symptom-based diagnostic logic, build interactive user interfaces, and manage a project through GitHub and deployment tools. I also gained a better understanding of how AI-based decision systems can make technical information easier for everyday users to understand.

One of the main challenges was designing logical rules that connect different combinations of symptoms to relevant possible faults. Handling incomplete answers and situations where symptoms do not match known rules was another challenge. I addressed these by organizing the diagnostic conditions and including a fallback response for unrecognized symptoms.

This project strengthened my problem-solving, web development, and debugging skills while showing me how technology can address practical, real-world problems. My vision for AutoSense AI is to make vehicle fault identification more accessible, understandable, and intelligent.