To begin, open the graphical user interface server module. Enter the VVID port number in the VVID text field. Click on Create Socket to create and bind the socket.
Then click on Connect to establish a connection with the mobile app. Now click on Capture to capture and save the scene surveillance images in the local folder. Let the client module include a robotic arm designed to have rotational movement in its base, shoulder, elbow, wrist, and fingers.
Ensure that MG996R servos are used to govern the rotational movement at the base, shoulder, and elbow. Use the SG90 servo motor to control the rotational movement at the wrist and fingers. Compile the code given in the microcontroller integrated development environment to drive the robotic arm based on the commands received from the remote surgeon.
Read two images at a time in a sequence, one by one, from the local folder to identify the possible overlapping between them. Extract the features using the DITF method. Reconstruct three-dimensional images from the collected features using SFM.
Enable the surgeon to inspect the three-dimensional reconstructed image features using hand gesture controls for rotation and zoom in or out, allowing visualization from all perspectives. Normalize and map the distance between the tip of the surgeon's thumb and the index finger of the right hand into a corresponding angle of rotation. Transmit the hand gesture control through Bluetooth to the remote surgery environment.
Ensure that the rotation of the object platter at the remote site mirrors the rotation of the three-dimensional reconstructed features at the surgeon's end. The accuracy of motion mapping decreased as the distance between two fingers increased. The DITF algorithm achieved the lowest latency compared to ORB and BEBLID.
