tinyML Talks – Sweden meetup
“Edge Machine Learning for Mobile Health Technologies”
Assistant Professor in the Department of Electrical and Information Technology
Machine learning will be an essential component of the next-generation Internet of Things (IoT) systems, including mobile health and wearable technologies. The adoption of machine learning in such systems creates several new opportunities, e.g., real-time and early detection of health abnormalities. However, enabling machine learning in mobile health and wearable technologies also involves several challenges. In particular, such systems are extremely limited in terms of resources (processing power, communication bandwidth, memory storage, and battery lifetime) due to the requirements w.r.t. portability, wearability, and social stigma. In this talk, we discuss the main challenges facing the TinyML community and introduce a new generation of edge machine-learning techniques for such resource-constrained mobile health and wearable technologies.