JP Journal of Heat and Mass Transfer
Special Issue, Advances in ICT-Convergence, Pages 31 - 47
(September 2020) http://dx.doi.org/10.17654/HMSI20031 |
|
DESIGN OF EFFICIENT FOG-CLOUD SYSTEM THROUGH MACHINE LEARNING
Chi Gon Hwang, Tae Woo Kwon, Jong-Yong Lee and Kye-Dong Jung
|
Abstract: Recently, research on machine learning techniques for artificial intelligence has been carried out actively, and many techniques have emerged to apply them. It involves individual studies of techniques ranging from refining input data, learning algorithms, and forecasting. However, it has different areas of application according to techniques, and the semantic association does not apply to refine techniques of input data. To do this, a technique is required to connect the input data using ontology and to perform situational awareness using machine learning. In this paper, we propose a prediction system using machine learning and ontology. The applied machine learning technique is SVM. Through this, it is a system that learns the measured data from the sensor embedded in the smartphone possessed by the elderly and identifies and notifies their status. The main structure of this system uses DBaaS of cloud computing technology, collection, and processing of sensor data that uses fog computing. |
Keywords and phrases: DBaaS, ontology, machine learning, cloud computing, fog computing.
|
|
Number of Downloads: 324 | Number of Views: 875 |
|