Sujet de thèse N°1
Titre
IoT and Ressource-Efficient Machine Learning for Smart Health Monitoring
Laboratoire
TICLab - Laboratoire Technologies de l’information et de la communication
Collège
College of Engineering & Architecture
Date Limite
26-09-2022
Description
The objective is to develop a smart system for real-time health monitoring using IoT and edge intelligence. The latter includes intelligent sampling, intelligent transmission, and ressource-efficient machine learning. The focus will be on respiratory diseases. The system will include a mobile application to collect and preprocess physiological signals and air pollution measurements. Predictive models will be developed to help patients and doctors better manage respiratory diseases. This work is part of the i-Respire project (funded by OCP and CNRST) which is coordinated by UIR and carried out in partnership with Ibn Sina University Hospital and Lincoln Universitry.
- Experience in the design and implementation of IoT solutions.
- A good understanding of machine learning
- English writing skills
- Good communication skills in French and English
Main supervisor: Mounir Ghogho
Required academic qualifications & skills
- A good understanding of machine learning
- English writing skills
- Good communication skills in French and English
Main supervisor: Mounir Ghogho
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