TCloud: Cloud SDI model for tourism information infrastructure management

This chapter proposes and develops a cloud-computing-based SDI model named as TCloud for sharing, analysis, and processing of spatial data particularly in the Temple City of India, Bhubaneswar. The main purpose of TCloud is to integrate all the spatial information such as tourism sites which include various temples, mosques, churches, monuments, lakes, mountains, rivers, forests, etc. TCloud can help the decision maker or planner or common users to get enough information for their further research and studies. It has used open source GIS quantum GIS for the development of spatial database whereas QGIS plugin has been linked with quantum GIS for invoking cloud computing environment. It has also discussed the various spatial overlay analysis in TCloud environment

Hybrid mist-cloud systems for large scale geospatial big data analytics and processing: opportunities and challenges

The cloud and fog computing paradigms are developing area for storing, processing, and analysis of geospatial big data. Latest trend is mist computing which boost fog and cloud concepts for computing process where edge devices are used to help increase throughput and reduce latency to support at client edge. The present research article discussed the mist computing emergence for geospatial analysis of data from various geospatial applications. It also created a framework based on mist computing, i.e., MistGIS for analytics in mining domain from geospatial big data. The developed MistGIS platform is used in Tourism Information Infrastructure Management and Faculty Information Retrial System. Tourism Information Infrastructure Management is to assimilate entire geospatial data in context to travel/tourism places constitute of various lakes, mountains, rivers, forests, temples, mosques, churches, monuments, etc. It can aid all the stakeholders or users to acquire sufficient data in subsequent research studies. In this study, it has taken the Temple City of India, Bhubaneswar as the case study. Whereas Faculty Information Retrial System facilitated many functionalities with respect to finding the detail information of faculties according to their research area, contact details, and email ids, etc in all 31 National Institutes of Technology (NITs) in India. The framework is built with the Raspberry Pi microprocessor. The MistGIS platform has been confirmed by prelude analysis which includes cluster and overlay. The outcome show that mist computing assist cloud and fog computing to provide the analysis of geospatial big data

MistGIS: optimizing geospatial data analysis using mist computing

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