Apnea, a type of sleeping disorder wherein the patient tends to forget to breathe or suffers from intermittent gaps in breathing while asleep. Developed “Sleep Apnea Detector” device, which will capture the ECG signal and process it to extract the features which can uniquely identify OSA. After processing the signal, it will be fed to a trained SVM model for classification. An alarm system will immediately alert the patient and people nearby if apnea has been detected.
SIGN LANGUAGE RECOGNITION TO SOLVE MATHEMATICAL PROBLEMS
Built a computer based intelligent system that will enable specially-abled students significantly to learn better with all other students using their natural hand gestures.Sign language recognition was carried out using feature extraction (using variety of extraction techniques like eigen values, corners, HOG, moments, peaks, etc.).
This project was part of Smart India Hackathon -Hardware Edition 2018 under the Ministry of Environment and Forests. In a team of 6 people, Developed a smart and highly sensitive detection system in built in vehicles identify and classify animal. This system also incorporated radar sensor for obstacle detection in a given range and further classified and processed using camera and processor.
SMART SURVEILLANCE MODULE
A graphical user interface developed on MATLAB allows to capture image only if any intrusion is present in area of surveillance. This system reduces storage space requirements and power consumption compared to typical IP cameras. The stored image was displayed on mobile devices using Apache local host server network.