Design And Realization Of Connected Glasses Dedicated To E-health Monitoring
2019
Mémoire de Master
Informatique

Université Larbi Ben M'hidi - Om-el-bouaghi

A
Ababsa, Abdelghani
K
Kouah, Sofia

Résumé: We're entering a new area of computing technology called the Internet of Things (IoT). We can see the IoT as billions of smart, connected "things" that will encompass every aspect of our lives, and its foundation is the intelligence that embedded processing provides. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can "command and control" things to make our lives much easier and safer and to reduce our impact on the environment. The creativity of this new area is boundless, with amazing potential to improve our lives. In order to establish a diagnostic method based on IoT system, and considering the distribution and diversity of processes and components involved in this system, multi agent systems present an adequate solution for the implementation of this application. It is the modeling of this system by autonomous, intelligent and cooperative entities called agents. These agents communicate with each other by using agent languages and protocols. The purpose of this dissertation is to realize an IoT based application for the medical diagnosis in E-Health area. This application uses connected glasses and facial recognition to ensure telemedicine of patients. It is modeled by means of MAS paradigm where we distinguish three kinds of agents: a global coordination agent (one instance), a local coordination agent (several instances) and agent of things (several instances). The agent of things receives and controls values issued from connected object, sends these values to the global coordination agent. The local coordination agent and global coordination agent cooperate together to diagnosis these values and make a decision. This approach is implemented by using Arduino platform, Jade platform and Android.

Mots-clès:

arduino
facial recognition
multi-agent system
diagnosis
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