SciFest National Final 2023

Stand 33

A Kind Eye - A Risk Assessment Machine Learning Algorithm for Vulnerable Adults

Students Emma Fallon, Sofia Mc Gorisk
School Our Lady's Bower, Retreat Road, Athlone, Co Westmeath
Teacher Julie-Anne Greaney
Venue TUS Athlone

Purpose of the Project

This project proposes a personalised risk assessment App. The aim of the project is to create a machine learning risk assessment algorithm in a mobile app that will determine what’s normal for a user and alert a caregiver if there are changes from normality.

Description of the Project

There were three main objectives of the project: (1) to understand the inputs that are relevant to a user, e.g. traveling to town, wake/sleep times, contact with family/friends; (2) to develop an adaptive machine learning algorithm to adjust the level of risk for a particular user; (3) to build an app to capture the input data, implement the algorithm and communicate with care givers.


This work is experimentally based. Using the MIT App Inventor we created a demonstration app to detect sensory interactions of the person. The testing sample consisted of a representative sample of family and friends.

We set out three key areas for investigation:

  • A Baseline Survey of participant interaction and an indication of the need for assistance
  • Evaluating the effectiveness of crisp boundary logic
  • Evaluating the effectiveness of multivariate fuzzy logic


Both the crisp boundary and fuzzy logic approaches showed a close correlation between the estimated and survey results: crisp boundaries 66%; fuzzy logic 88%. The fuzzy logic approach had an average 22% performance improvement in comparison to the crisp boundary approach.

Poster Click here
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