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Smartphone Architecture for Edge-Centric IoT Analytics.

Bockarie Daniel Marah1, Zilong Jing1, Tinghuai Ma1

  • 1School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210-044, Jiangsu,China.

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Summary
This summary is machine-generated.

This study introduces a novel smartphone IoT architecture (SMIoT) for edge computing, enabling real-time model validation and updates on devices. This enhances the sustainability and reliability of Internet of Things (IoT) solutions at the network edge.

Keywords:
artificial neural networks (ANN), cloud and regression analysis.edge computinginternet of things (IoT), smartphone

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Data Science

Background:

  • Traditional Internet of Things (IoT) architectures rely heavily on cloud/core for data analysis and storage.
  • Edge computing is increasingly recommended for IoT solutions to enhance efficiency and reduce latency.
  • Smartphones possess significant computational capabilities suitable for edge processing in IoT.

Purpose of the Study:

  • To propose an edge-centric IoT architecture specifically designed for smartphones.
  • To introduce a novel architecture supporting comprehensive machine learning model lifecycle management on the device.
  • To develop a real-time model evaluation and updating mechanism for sustained edge performance.

Main Methods:

  • Formulation of a novel smartphone IoT architecture (SMIoT).
  • Implementation of functionalities for data capture, preprocessing, model deployment, evaluation, and updating.
  • Development of a real-time scheme for model validation and adaptation to changing data patterns.

Main Results:

  • The proposed SMIoT architecture effectively supports edge computing tasks on smartphones.
  • The novel evaluation and updating scheme ensures real-time model validation at the network edge.
  • The architecture demonstrates sustainability and reliability by automatically adjusting to IoT data subspace changes.

Conclusions:

  • The SMIoT architecture offers a viable edge-centric approach for smartphone-based IoT applications.
  • Real-time model management at the edge enhances the performance and adaptability of IoT systems.
  • This research contributes to the development of more efficient and responsive IoT solutions.