Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

A Systematic Approach For Data Cleansing Process of Geospatial Data to Perform Application Specific Data Analytics

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  • @INPROCEEDINGS{10.4108/eai.7-6-2021.2308858,
        author={M S Satyanarayana and Dr. Nageswara  Guptha M and Dr. Vasanthi  Kumari P},
        title={A Systematic Approach For Data Cleansing Process of Geospatial Data to Perform Application Specific Data Analytics},
        proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
        publisher={EAI},
        proceedings_a={I3CAC},
        year={2021},
        month={6},
        keywords={data analytics geospatial data structured quasi structured un-structured},
        doi={10.4108/eai.7-6-2021.2308858}
    }
    
  • M S Satyanarayana
    Dr. Nageswara Guptha M
    Dr. Vasanthi Kumari P
    Year: 2021
    A Systematic Approach For Data Cleansing Process of Geospatial Data to Perform Application Specific Data Analytics
    I3CAC
    EAI
    DOI: 10.4108/eai.7-6-2021.2308858
M S Satyanarayana1,*, Dr. Nageswara Guptha M2, Dr. Vasanthi Kumari P3
  • 1: Research Scholar, SVCE, Bengaluru
  • 2: Associate Professor Senior Grade 2, VIT Bhopal University, Sehore
  • 3: Sehore, Associate Professor, Dayanand Sagar University, Bengaluru
*Contact email: satya.satya2011@gmail.com

Abstract

Data Analytics is the key word of today's era. Huge data is getting generated day by day from various resources starting from social networking sites to sensors then machines. How this can be handled in effective manner to get some value out of it, this is the biggest question in front of all engineers today. Geo Spatial Data, this data is another type of data which is getting produced because of the objects on the surface either they are static or dynamic. As per the statistics every year there is a 20% increase in Geospatial data production. And this Geospatial Data can be used for multiple purposes in various applications like autonomous vehicles, location based services, identifying the object in surface etc..., but the biggest challenge faced here is how this data can be analyzed and stored for future purpose. This data may be live data or stored data, it might be structured, un-structured or quasi structured data, it might be with duplicates or without duplicates and with null values or without null values. The challenge here is how this data can be used to perform data analytics and produce the results which can be used for future use. In the proposed research the main concentration is on how Geospatial data can be cleaned and made ready to use for data analytics for future use in applications like driverless vehicles, Location Based Services etc.., the first step in performing data analytics is collecting the