Activities of Daily Living (ADL) Recognition

The project shall explore the cutting-edge research and technologies in monitoring daily activities using a set of sensors deployed in the house. The objective of the research is to provide a feasible solution for improving care for patients with chronic disease, while significantly reducing the healthcare cost. We will conduct a comparative study on the existing models for characterizing human activities, and algorithms for activity recognition. Focusing on the open problem of multiple persons monitoring, we will identify an optimal set of sensors, design an algorithm for ADL recognition based on machine learning, and implement a prototype. We will test and evaluate our prototype using available datasets from other researchers. Kanayo will benefit from the results of the research, as well as the prototype implementations.

Faculty Supervisor:

Dr. Evangelos Milios

Student:

Love Kalra

Partner:

Kanayo Software Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Dalhousie University

Program:

Accelerate

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