Merging Automotive Diagnostics with AI
How my background in automotive and IT led to an ADAS diagnostic agent that predicts failures before they happen.
Problem
ADAS-equipped vehicles generate massive data streams, but technicians only get reactive error codes. Predictive diagnostics was missing.
Approach
I built an edge AI system on Raspberry Pi, connected to CANBus and ADAS sensors. Applied anomaly detection with Python + OpenCV, and served results in a Flask dashboard.
Results
- Predicted failures before downtime
- Improved fleet safety
- Reduced costs of unexpected breakdowns
References:
Need Expert Cybersecurity Guidance?
Get personalized insights and solutions for your specific security challenges.
Schedule a ConsultationMore Insights
AI for Cybersecurity in 2025: Smarter Defense for Small Businesses
How AI-powered tools can help even small organizations defend against modern threats — with examples, architectures, and reference studies.
Building Secure CI/CD Pipelines in 2025
Why security must be built into every deployment pipeline — and how I use GitHub Actions, SonarQube, and Terraform to enforce DevSecOps.