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The new paradigm of Mobile Crowd Sensing (MCS) has resulted in large amounts of data from different sources. The heterogeneous nature of the generated data is a very difficult, complex method for analysis and knowledge extraction knowledge. Specifically, that mining these data will require processing with special attention. This article will provide an analysis of these data and focus on processing and exploration. We are collected using the notes and sensors, including a variety of environmental data. In this process is, we argue that mandatory benefit from different data sources in the context of the MCS. This article describes a workflow proposed to analyze the framework of outdated geography of the data series of the content of the MCS. We dive into the details of each component of the system. To save, reconnect the final shape for public access, data transmission and visualization, it begins at the description analysis stage of the latest collection.

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How to Cite
P.Renuga, & Mrs.K.Anbumathi. (2021). Big Data Series Analytics In The Context Of Environmental Crowd Sensing. International Journal of Intellectual Advancements and Research in Engineering Computations, 9(3), 8–14. Retrieved from