MistGIS: optimizing geospatial data analysis using mist computing
Document Type
Conference Proceeding
Date of Original Version
1-1-2018
Abstract
Geospatial data analysis with the help of cloud and fog computing is one of the emerging areas for processing, storing, and analysis of geospatial data. Mist computing is also one of the paradigms where fog devices help to reduce the latency period and increase throughput for assisting at the near of edge device of the client. It discusses the emergence of mist computing for mining analytics in geospatial big data from geospatial application. This paper developed a mist computing-based framework for mining analytics from geospatial big data. We developed MistGIS framework for Ganga River Management System using mist computing. It built a prototype using Raspberry Pi, an embedded microprocessor. The developed MistGIS framework has validated by doing preliminary analysis including K-means clustering and overlay analysis. The results showed that mist computing can assist the fog and cloud computing hold an immense promise for analysis of big data in geospatial application particularly in the management of Ganga River Basin.
Publication Title, e.g., Journal
Advances in Intelligent Systems and Computing
Volume
710
Citation/Publisher Attribution
Barik, Rabindra K., Ankita Tripathi, Harishchandra Dubey, Rakesh K. Lenka, Tanjappa Pratik, Suraj Sharma, Kunal Mankodiya, Vinay Kumar, and Himansu Das. "MistGIS: optimizing geospatial data analysis using mist computing." Advances in Intelligent Systems and Computing 710, (2018): 733-742. doi: 10.1007/978-981-10-7871-2_70.