This case study highlights how Webelight Solutions developed a resource-efficient Computer Vision application for a robotic system operating in low-bandwidth environments.

By leveraging deep learning models, including YOLO, Faster R-CNN, and transformer-based architectures like DETR, we created a lightweight solution capable of real-time hand movement detection in live video streams.

This innovation powered an interactive game integrated into a robotic platform, demonstrating the scalability of AI in robotics, surveillance, logistics, and automation. From enhancing security systems to optimizing autonomous vehicles and revolutionizing healthcare applications, our expertise in Computer Vision ensures high accuracy, low latency, and efficient performance even in challenging conditions.