Autors: Ivanova, D. A., S. Zahov.
Title: Ocean Big Data Processing in IoT Ecosystem
Keywords: IoT, Ocean Big Data, Machine Learning, Linear Regression, Support Vector Machines, Result Analysis

Abstract: This paper presents different methods of ocean data collection in the IoT ecosystem. Most of the ocean big data are connecting to sea surface temperature, subsurface temperature, water flows, air mass movement and their interaction at ocean-atmosphere level, sea level, sea ice concentration, and topography of the ocean floor, meteorological conditions and their influence on the ocean surface. All these characteristics of Ocean data are from significant importance with respect to the climate change and its influence on human life. In this paper, the conceptual model for big data analytics of ocean data based on machine learning will be proposed. The experimental framework is based on Apache Spark environment and python3 programming language optimized for big data processing is utilized. The experiments using the linear regression and support vector machine algorithms are conducted. Finally, the result analyses are presented.



    International Conference Automatics and Informatics, pp. 221 - 224, 2017, Bulgaria, Sofia, ISSN 1313-1850

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    Вид: публикация в международен форум, публикация в реферирано издание