Developed and deployed a high-accuracy classification model to identify over 30 different types of gas cylinders used in automated gas filling robots. The model achieved 98% accuracy and was optimized for real-time inference on NVIDIA Jetson hardware, enabling seamless edge deployment with minimal latency. This AI solution significantly improved automation reliability and reduced manual verification steps.
