We are currently hiring:
- Post-Doctoral Fellows in Software Engineering
- Research Assistants/Professionals
Students/Researchers interested in joining the AMI Laboratory are welcome to send a CV and a two pages research statement describing what they aspire to work on to our lab’s email amilab-info[@]usherbrooke[dot]ca
Projects for undergrad students
Sorry, this section is under construction. Please visit the French version for more details.
Projects for graduate students
All graduate positions are filled out at this stage. Please check back later.
We have numerous research project that involves graduate and undergrad students. The research project list includes, but not limited to:
» Monitoring of health condition of seniors
Aging process is related to serious decline in health condition. Thus, early detection of these health changes is important to improve classical assessments that are mainly based on interviews, and are insufficient to early diagnose all possible health changes. The goal of the project is to propose a technological approach that analyzes elderly people behavior on a daily basis, employs unobtrusive monitoring technologies, and applies statistical techniques to identify continuous changes in monitored behavior. The aim is to detect significant long-term changes that are highly related to health problems.
» Unobtrusive IoT based Sleep monitoring:
Sleep plays a vital role in a person’s health and well-being. Millions of people worldwide are suffering from sleep problems. Unfortunately, most people with sleep problems remain without diagnosis and treatment because the current sleep assessment systems are inconvenient and expensive. The goal of the project is to propose a non-invasive and non-intrusive sleep quality monitoring system using a microbend fiber optic sleep mat placed under the bed mattress. The assessment of the sleep quality is based on various Artificial Intelligence methods applied to study user context parameters, i.e., sleep interruptions, wake up and sleep time or vital signs such as heart rate and respiratory rate. The system is to be integrated into an existing Ambient Assisted Living framework in order to be validated in real scenarios.
» Adaptable Context-Aware Cooking-Safe System:
Kitchen safety is a highly important concern for daily living activities. Cooking, usually, is accompanied with several risks particularly for elderly people, due to aging associated impairments. Therefore, cooking-safe environment is required to enhance safety. The goal of the project is to propose a cooking-safe smart oven system that manages the detection of risk situations and determines their severity levels according to the contextual information around oven. The context is gathered via sensors deployed in kitchen environment. The project also includes building risk prevention algorithms which constitute the basic concepts of the reasoning engine.
» Dynamic domain model for micro context-aware application adaptation in smart city:
Adapting application to diverse/dynamic domains is required to enlarge pervasive computing use and to satisfy people demand in terms of continuity of services. In addition, the proliferation of smart devices and ubiquitous services motivate the need for a quick development of applications that support people in dynamic domains. We target in this project raising the level of adaptation for rapid application development in dynamic domains. The project involves improving the formal definition of domain knowledge/applications to be created by domain experts, propose a context-based semantic framework. In this framework, domain knowledge is described by means of meaningful context that includes unambiguous terms and operations, resulting in an enhancement of adaptation of applications. The applicability of the framework to describe dynamic domains and context-based services will be studied in a simulated smart city.
» Context-Aware in-Person Social Activity Recommendation System for seniors:
Active life style promotes healthy aging, and participation in social and physical activities improves aging people well-being. Nowadays, new media sources advertise large number of activities and for all age categories. These media, however, are not adapted to the aging population. The goal of the project to propose a context-aware in-person social activity recommendation system for seniors. The system interprets natural language descriptions of activities in social media and proposes suitable activities using AI, taking in consideration user-profile and contextual information.
» A Micro Context-Aware Agents for Ambient Assisted Living (AAL) in Smart cities:
AAL systems can denote the use of the smart cities to improve user well-being. Services provided by those systems include emergency treatment services, autonomy enhancement services, and/or comfort services. Still, the smart cities are open intelligent space where IoT Agents can act, communicate and move in an unconstrained physical manner. While such a space enables a wide range of contextual applications that address the needs of users, it introduces a new set of issues due to the dynamic nature of the Agent network. To address these issues, we propose an Agent-based framework and a distributed architecture for autonomic Agents that relies on a micro-level, local, approach to Context Awareness. Special attention is made to the identified four generic concerns for AAL systems: customizability, distribution, heterogeneity, and adaptability.
»»» Intern/Student projects in detail «««
Following a description of a selected project
- IoT platform for smart cities
- IoT platform to assist mobile users
- Big data platform for IoT in smart cities
- Context-Aware Social Activity Recommendation for Active Aging in Smart Cities
- IoT feedback platform for smart cities
- Interoperability of IoT components in smart cities
- IoT Proximity solution in smart cities
- IoT based Learning from activities in smart cities
- Unobtrusive monitoring of vital signs
- Fault Tolerance Analysis of IoT devices in smart cities
- IoT based Service provisioning for Active Aging in Smart Cities
- Execution plan of complex tasks in Smart cities
- Sensing Environment from Social Media Networks
- Learning from activities of daily living