Saad Rhanmouni
- Master student, University of Ottawa
- Member of Health-Devices Research Group and CARG
Contact
srhan056@uottawa.ca
Bio
I am a mechanical engineering graduate with a master’s degree from the University of Ottawa, specializing in radar systems, machine learning, and point cloud data processing. I have experience with Python and have worked on projects involving anomaly detection, activity classification, and real-time data processing for healthcare and safety applications.
Project/Task in the Group:
My previous task involved executing a fall detection system using an HVRAE (Hierarchical Variational Recurrent Autoencoder) for anomaly detection. The project aimed to analyze sequential data and identify patterns deviating from normal behavior, such as falls. By leveraging HVRAE, I could model complex temporal relationships and detect anomalies. Combined with Z position change monitoring, this method proved effective in providing real-time alerts for fall incidents and contributed significantly to safety monitoring solutions. Currently, I am focused on designing a radar-based GUI for activity classification. The system processes point clouds, predicts activities like “Falling” or “Stand+Walking,” and logs the results in CSV format. I am also exploring thermal camera integration to improve labeling and streamline future deployments in environments such as nursing homes, while also assisting with project planning and coordinating between team memebers.