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Big Data Analytics and Big Data Processing for IOT-Based Sensing Devices

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Transforming Management with AI, Big-Data, and IoT

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Abstract

The current development and growth in the social and industrial sectors have evolved the use of sensing and smart devices, collectively called the Internet of Things (IoT). Huge volume of information being produced and collected by these IoT devices is also called Big Data, which needs to be managed, processed, and analyzed for the development of the social sector such as health care, education and smart community, and industrial sectors like manufacturing and production. Big Data analytics and processing have contributed to the advancement of society as well as improved the industrial processes. High speed and continuous sensing generate huge volumes of complex data, and processing and analyzing these data in a certain time limit is a big challenge. For a real-time decision-making and monitoring system, data processing and analysis are challenging due to limited computational, communicational, and storage resources. Big Data analytics and processing tools can be applied over these massive data as per the type of application and outcome required. Different types of applications need to be supported by a variety of tools based on different principles and approaches. Big Data is a set of voluminous and heterogeneous information in a coordinate, semi-structured, and unstructured form. Modern innovation in machine learning (ML), deep learning (DL), and artificial intelligence (AI) fulfills the requirement of Big Data analytics processing for advanced real-time decision-making, monitoring, and controlling systems. Classification and processing of stream of data generated by sensing devices help predict future insights. It identifies information required to control and monitor decisions for an individual, a society, an organization, and an industrial application. In this chapter, we discuss the algorithm, principal tools, and technologies required for Big Data analytics and processing over data gathered by different sensing and Internet of Things devices.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, PSIT, Kanpur, Uttar Pradesh, India

    Pawan Kumar Pal, Charu Awasthi & Prashant Kumar Mishra

  2. Department of Information Technology, PSIT College of Engineering, Kanpur, Uttar Pradesh, India

    Isha Sehgal

Authors
  1. Pawan Kumar Pal
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  2. Charu Awasthi
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  3. Isha Sehgal
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  4. Prashant Kumar Mishra
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Corresponding author

Correspondence to Charu Awasthi .

Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence Engineering, AI and Robotics Institute, Near East University, Mersin, Turkey

    Fadi Al-Turjman

  2. Department of Computer Science and Engineering, G. L. Bajaj Institute of Technology and Management (GLBITM), Affiliated to AKTU, Greater Noida, India

    Satya Prakash Yadav

  3. School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttar Pradesh, India

    Manoj Kumar

  4. Department of Information Technology, Rajkiya Engineering College, Banda, Uttar Pradesh, India

    Vibhash Yadav

  5. Department of Computer Science and Engineering, Faculty of Engineering and Technology, M. S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India

    Thompson Stephan

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Pal, P.K., Awasthi, C., Sehgal, I., Mishra, P.K. (2022). Big Data Analytics and Big Data Processing for IOT-Based Sensing Devices. In: Al-Turjman, F., Yadav, S.P., Kumar, M., Yadav, V., Stephan, T. (eds) Transforming Management with AI, Big-Data, and IoT. Springer, Cham. https://doi.org/10.1007/978-3-030-86749-2_2

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  • DOI: https://doi.org/10.1007/978-3-030-86749-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86748-5

  • Online ISBN: 978-3-030-86749-2

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