Graduation Year


Document Type




Degree Name

Master of Science (M.S.)

Degree Granting Department

Electrical Engineering

Major Professor

Kwang-Cheng Chen, Ph.D.

Committee Member

Huseyin Arslan, Ph.D.

Committee Member

Ravi Sankar, Ph.D.


Edge computing, Smart healthcare system, Smartphone based system


The developing IoT concept offers many opportunities to service providers in the medical field. However, the functionality of the developed systems is increasing day by day, and it brings many different problems. One of the most important problems is the transmission of biomedical data of real-time monitoring systems to the medical server with the least delay. Network architectures are changing to meet the changing needs of densely connected devices, and “computing at the edge” is the new architectural approach emerging in IoT networks. This architecture is more dynamic than computation in the cloud because it enables data processing at each layer of the network. In this way, it solves two problems created by computing in the cloud: increase in data traffic and latency in the services provided.In this thesis, an IoT-based medical e-health system design has been proposed. It aims to transmit the vital data obtained in the proposed system to the medical server by sending it directly to the smartphone. The obtained data is transferred to the smartphone via BLE 5.0 and the BLE data channels used are specialized. The proposed smart health system is performed data analysis and data traffic performed on the smartphone. According to the analyzed health status, the intelligent data traffic structure of the system decides how often the data will be sent to the cloud dynamically. It is aimed to design in such a way that the use of bandwidth is optimal.