SCF: Smart Big Data Classification Framework

摘要

Background/Objectives: Remote sensing produces huge data to be analyzed for different applications. The aim of this study is to develop smart big data classification platform based on AI techniques. Methods: The data differs in its types and format, text, images, audio, and video, and they might be structured or unstructured. Besides, data could be divided into categories, and each category needs to be analyzed by itself. Hence, the first step to handle this massive data is to classify them according to their types. Then, the classification phase is followed by the analysis phase. We proposed to utilize two AI algorithms: Fuzzy KNN and CNN. Findings: We proposed a novel and new smart big data classification platform based on AI techniques. It also involves cloud computing as a distributed environment to speed up the classification process of such huge data. The framework proposes a pre-analysis structure with suggested algorithms. The framework is examined against a regular/serial approach, and it proves its efficiency in the big data analysis.