AI Case Study
The University of Alberta aims to ensure the safety and independence of seniors using deep learning and machine vision
Computing scientists the University of Alberta have leveraged software technology from Spxtrm AI to develop a system that can help seniors stay safe both at home and in care facilities. Using deep learning, machine vision and motion classification the system is able to track events in real time and detect events such as falls to alert caregivers or other professionals in real time.
Industry
Public And Social Sector
Education And Academia
Project Overview
"An autonomous intelligence system is helping seniors stay safe both at home and in care facilities, thanks to a collaboration between University of Alberta computing scientists and software technology company Spxtrm AI.
The new tool uses a deep-learning computer vision system and motion-classification algorithms to capture events such as falls in real time, alert caregivers and give health-care professionals the information they need for immediate triage.
The system—developed in part by the Multimedia Research Centre led by Irene Cheng in the Department of Computing Science—transfers real-time video to an autonomous computer vision lockbox. If an event is detected, the system alerts a specified caregiver and provides a redacted video of the event.
She added that videos are captured continuously and at high resolution.The system also maintains the privacy of seniors while providing caregivers with important triage information, including the moment of impact after the fall.
Reported Results
Proof of concept; results not yet available.
Technology
"The new tool uses a deep-learning computer vision system and motion-classification algorithms to capture events such as falls in real time, alert caregivers and give health-care professionals the information they need for immediate triage."
Function
R And D
Core Research And Development
Background
Benefits
Data
video footage