Automated the Camera light of Jetson robot for surgeries

Waruna Srinath

Data Modelling Analyst
ML Engineer
AI Model Developer
OpenCV
PyTorch
TensorFlow







Project Overview:

In collaboration with a dynamic and multidisciplinary team comprising mechanical engineers, electronics engineers, and computer vision specialists, we embarked on a groundbreaking project endorsed by a senior consultant. Our mission was to revolutionize surgical procedures by designing an automated camera light system for Jetson Nano robots used in operating theaters. This innovative system is engineered to streamline surgical processes by automatically detecting key surgical points, eliminating the need for manual light adjustments

Key Contributions:

  • Automated Camera Light System: Developed a sophisticated system that autonomously detects and focuses on critical surgical points, ensuring optimal lighting conditions without manual intervention.
  • Object Detection Application: Spearheaded the development and configuration of an advanced object detection application capable of precisely identifying specific surgical instruments.
  • Cutting-Edge Technology: Implemented state-of-the-art Convolutional Neural Network (CNN) algorithms and meticulously fine-tuned the system to achieve unparalleled accuracy in instrument detection.
  • Enhanced Surgical Efficiency: Our innovative solution significantly enhances the efficiency, accuracy, and safety of surgical procedures, contributing to better patient outcomes and streamlined operations.

Project Highlights:

  • Multidisciplinary Collaboration: Leveraged the expertise of a diverse team of engineers and computer vision specialists to achieve a comprehensive and robust solution.
  • Senior Consultant Endorsement: The project received endorsement from a leading senior consultant, underscoring its significance and potential impact on the medical field.
  • Technological Innovation: Our system represents a significant leap forward in the application of robotics and computer vision in surgery, setting new standards for automated surgical assistance.
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