17th AIAI 2021, 25 - 27 June 2021, Greece

Collaborative Edge-Cloud Computing for Personalized Fall Detection

Anne Ngu, Shaun Coyne, Priyanka Srinivas, Vangelis Metsis


  The use of smartwatches as devices for tracking one’s health and well-being is becoming a common practice. This paper demonstrates the feasibility of running a real-time personalized deep learning-based fall detection system on a smartwatch device using a collaborative edgecloud framework. In particular, we demonstrate how we automate the fall detection pipeline, design an appropriate UI on the small screen of the watch, and implement strategies for the continuous data collection and automation of the personalization process with the limited computational and storage resources of a smartwatch.  

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