Mohammed Kaif Khalander

Feb 2025- present

– Developed a deep learning-based image enhancement system to improve underwater visual perception for autonomous robots. Implemented convolutional neural network (CNN) models to reduce noise,correct color distortion, and enhance image clarity in low-visibility environments. The project focused on improving object detection and navigation accuracy in underwater conditions by integrating enhanced limage outputs into robotic vision pipelines using PSNR and SSIM. Tools and frameworks used include Python, TensorFlow/Keras, and OpenCV.

Feb 2024- Dec 2024

– Developed a system that detects ambulance sirens using a sound sensor and microcontroller to autocontrol traffic signals for emergency vehicle priority. Integrated Arduino and sound frequency analysis to distinguish sirens from background noise and enhance traffic management efficiency.

– Developed a wireless control system to operate electronic devices remotely using an IR or RF communication module integrated with an Arduino microcontroller. The system transmits control signals from a handheld remote to a receiver circuit, enabling efficient and safe device operation from a distance. Designed hardware and programmed the controller for reliable signal transmission and response. The project demonstrates practical applications in home automation and robotic control systems.