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Real-time event-driven sensor data analytics at the edge-Internet of Things for smart personal healthcare

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Abstract

Real-time service has become a key for efficient serving of the Internet of Things (IoT)-based smart e-Healthcare. Several orientations have tried to pave this side of the technology but severely lacked in terms of incorporations of lightweight and open IoT-based frameworks. This study presents two different experiments that deals with the real-time visualization, charting and analytics while using real-time and open java script frameworks that includes Node.js, Johnny-Five, SperialPort, PubNub client, EON.js, Chart.js, Express Server and Socket.io. The objective of this work is to investigate the IoT-based real-time analytics behavior in cost-effective e-health sensor deployment scenario. The results found from the study advocates for the growth and assimilation of IoT-based open-source java script frameworks for serving real-time sensor data analytics in e-Healthcare sector.

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Authors and Affiliations

  1. Department of Computer Applications, Sikkim University, Gangtok, India

    Partha Pratim Ray

  2. Department of Computer Science and Engineering, National Institute of Technology Patna, Patna, India

    Dinesh Dash

  3. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Debashis De

Authors
  1. Partha Pratim Ray
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  2. Dinesh Dash
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  3. Debashis De
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Correspondence to Partha Pratim Ray.

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Ray, P.P., Dash, D. & De, D. Real-time event-driven sensor data analytics at the edge-Internet of Things for smart personal healthcare. J Supercomput 76, 6648–6668 (2020). https://doi.org/10.1007/s11227-019-03089-w

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