Develop an IoT-enabled edge computing system that uses AI vision models to detect manufacturing defects in real time, reducing production errors and cloud dependency.
Study edge computing architecture.
Integrate camera modules with edge devices (e.g., Raspberry Pi/Jetson).
Collect defect image datasets.
Train CNN-based defect detection model.
Deploy optimized AI model on edge hardware.
Implement real-time alert mechanism.
Compare cloud vs edge processing latency.
Optimize model for resource constraints.
Conduct accuracy testing under different lighting conditions.
Analyze production improvement metrics.
Ensure secure device communication.
Prepare system performance evaluation report.
