2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud) (2015)
Aug. 24, 2015 to Aug. 26, 2015
With the increasing availability of medical sensors and Internet of Things (IoT) devices for personal use, it becomes feasible to maintain a repository of measurements for personal health conditions. Consequently, it is tempting to analyze in-progress diseases and to identify the development of potential diseases with the measurement repository. However, there are a number of technical challenges in developing such applications, modeling the relationships between diseases and acquired measurements, representing medical expertise in machine-readable forms, and high complexity in diagnosing disease methods. We adopt a semantic-based approach to resolve the first two challenges, and utilize the concept of cloud computing to tackle with the last challenge. In this paper, we present a cloud platform which provides a core set of functionality needed to enable personal medical diagnosis over the network. We believe that the presented platform provides a comprehensive core functionality needed for various types of personal healthcare IoT applications.
Ontologies, Diseases, Medical diagnostic imaging, Medical diagnosis, Context, Sensors
H. J. La, H. T. Jung and S. D. Kim, "Extensible Disease Diagnosis Cloud Platform with Medical Sensors and IoT Devices," 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud)(FICLOUD), Rome, Italy, 2015, pp. 371-378.