چكيده به لاتين
Delay-sensitive and critical systems are used in many applications starting from the public, health, and military applications. As an emerging technology, the Internet of Things (IoT) to make the world a higher level of accessibility, integrity, availability, scalability, confidentiality, and interoperability, has been revolutionized these applications. These include environmental, and surveillance monitoring, healthcare, and wellbeing systems in response to the cardiovascular disease pandemic, and also the military system on the battlefield.
Nowadays, real-time Health Monitoring Systems use the Internet of Things to transmit patient's data over the network and analyzing them to reduce mortality, heart failure, and also for prevention and control of pandemic. The use of smartphones and other mobile devices based on the internet of things to deliver health care and preventative health services has made it possible to monitor people with recent advances in wireless sensors, mobile technology and cloud computing.
The Role of Edge and Fog Computing in the Internet of Health Things is an emerging technology that reduces response time and improves the quality of experiences and the quality of service. Despite the significant advancement in these emerging technologies, there are still requirements such as response time, scalability, latency, fault tolerance, and resource management.
Therefore, in this thesis, a 4-tier, hierarchical, and scalable architecture have been proposed to develop monitoring and surveillance systems, as an end-to-end solution, and to provide a real-time response to prevent abnormality and challenges. Real-time processing and technologies related to cloud computing, the Internet of Things, and resource management are used in this solution to provide services and remote monitoring.
The main purposes of this solution are data collection from heterogeneous devices and processing them in different levels of the processing that lead to real-time detection and analysis to predict abnormalities. It should be noted that in this study, due to the importance of heart disease continuous monitoring of health parameters is considered.
Furthermore, other applications such as military systems, situational awareness of the battlefield, and pandemic diseases are also considered and developed. The results show that the proposed system is capable of handling scalability and improve response time, power consumption, and quality of user experience with considering fault tolerance.
