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A Graph Based Analysis of User Mobility for a Smart City Project

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Next Generation Computing Technologies on Computational Intelligence (NGCT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 922))

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Abstract

Information and Communication Technologies (ICT) and Internet of Things (IOT) devices generate large amount of data for any Smart City projects. Data structure for storing multidisciplinary large scale data extracted from these types of data loggers become a challenging task. Research work presented in this paper emphasizes on robust data extraction (data streaming), data preprocessing, and integration. A graph based data analysis on different mobile movement is generated by different mobile tracer (data loggers) placed in diverse locations. Using data ingestion tools like Kafka/Flume/MQTT and Spark-Streaming data can be stored in a distributed storage, HDFS is used for storing such huge size of data. As we know due to the data volume and data generation speed, this problem is considered under Big Data Analysis (BDA) problem. Heat map has been used to depict the movement of customer carrying mobile phone in different locations of store. A ping signal collected whenever a person is moving from the range of sensor device. PageRank algorithm is used to assign a numerical rank to each vertex as per the in-degree links to that vertex. It considers a random walk from any selected vertex with the traversed connected vertexes. The rank of vertices that are representing mobile tracer sensors shows the movement of customers during a specific time period. It can be used for making decision about the reorganization of a store layout.

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Authors and Affiliations

  1. Institute of Technology, Nirma University, Ahmedabad, India

    Jai Prakash Verma, Sapan H. Mankad & Sanjay Garg

Authors
  1. Jai Prakash Verma
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  2. Sapan H. Mankad
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  3. Sanjay Garg
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Corresponding author

Correspondence to Jai Prakash Verma .

Editor information

Editors and Affiliations

  1. University of Petroleum and Energy Studies, Dehradun, India

    Manish Prateek

  2. University of Petroleum and Energy Studies, Dehradun, India

    Durgansh Sharma

  3. University of Petroleum and Energy Studies, Dehradun, India

    Rajeev Tiwari

  4. University of Petroleum and Energy Studies, Dehradun, India

    Rashmi Sharma

  5. National Institute of Technology, Srinagar, Uttrakhand, India

    Kamal Kumar

  6. Thapar University, Patiala, India

    Neeraj Kumar

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Verma, J.P., Mankad, S.H., Garg, S. (2019). A Graph Based Analysis of User Mobility for a Smart City Project. In: Prateek, M., Sharma, D., Tiwari, R., Sharma, R., Kumar, K., Kumar, N. (eds) Next Generation Computing Technologies on Computational Intelligence. NGCT 2018. Communications in Computer and Information Science, vol 922. Springer, Singapore. https://doi.org/10.1007/978-981-15-1718-1_12

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  • DOI: https://doi.org/10.1007/978-981-15-1718-1_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1717-4

  • Online ISBN: 978-981-15-1718-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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