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Résumé :
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In recent years, the Internet of Things (IoT) has become well known. It has attracted much attention thanks to its powerful application in different fields. Currently, billions of IoT devices are connected. The massive rise in the number of connected devices instantly produces further data that requires high storage and processing technology. Besides, the IoT equipment has limited processing, and storage capability did not allow data processing or even storage. Also, things cannot make smart and quick decisions to achieve their goals, and the thing ability to communicate with other things depends on service similarity and communication protocols; this will impact the performance, efficiency, development, and scalability of IoT applications. This thesis provides three main contributions, in the first contribution, we propose a Cloud-IoT approach to provide an efficient solution for the storage and analysis of data generated by IoT applications and improve IoT scalability. In order to demonstrate the viability of the proposed approach, a Cloud-IoT system for remote patient monitoring is developed. IoT security becomes a more challenging problem due to the computing and communication limits of IoT devices make IoT more vulnerable to security and privacy attacks. Hence, as a second contribution, we propose a robust solution based on lightweight cryptography to ensure data security. Also, we have used the access control mechanism to ensure data privacy. The experimentation demonstrates that the proposed solution more suitable for IoT devices. To tap the most out of massive data streams, IoT needs real-time management and analysis of data. In order to enhance the intelligence of IoT devices and to improve our first approach, we have developed an efficient, autonomous, and real-time solution based on the agent for data management and analysis as a third contribution. The proposed system can make fast and apt decisions in an emergency case.
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