Smartphone Architecture for Edge-Centric IoT Analytics.

Clicks: 168
ID: 103873
2020
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Abstract
The current baseline architectures in the field of the Internet of Things (IoT) strongly recommends the use of edge computing in the design of the solution applications instead of the traditional approach which solely uses the cloud/core for analysis and data storage. This research, therefore, focuses on formulating an edge-centric IoT architecture for smartphones which are very popular electronic devices that are capable of executing complex computational tasks at the network edge. A novel smartphone IoT architecture (SMIoT) is introduced that supports data capture and preprocessing, model (i.e., machine learning models) deployment, model evaluation and model updating tasks. Moreover, a novel model evaluation and updating scheme is provided which ensures model validation in real-time. This ensures a sustainable and reliable model at the network edge that automatically adjusts to changes in the IoT data subspace. Finally, the proposed architecture is tested and evaluated using an IoT use case.
Reference Key
marah2020smartphonesensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Marah, Bockarie Daniel;Jing, Zilong;Ma, Tinghuai;Alsabri, Raeed;Anaadumba, Raphael;Al-Dhelaan, Abdullah;Al-Dhelaan, Mohammed;
Journal sensors
Year 2020
DOI
E892
URL
Keywords
edge computing artificial neural networks (ann), cloud and regression analysis. internet of things (iot), smartphone

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