A Scalable IoT Video Data Analytics for Smart Cities

Doan, Mien Phuoc and Tran, Vu The and Huynh, Hung Huu and Huynh, Hiep Xuan (2019) A Scalable IoT Video Data Analytics for Smart Cities. EAI Endorsed Transactions on Context-aware Systems and Applications, 6 (19): e3. ISSN 2409-0026

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Abstract

The smart city is a comprehensive application of information resources and a high degree of information technology integration. With the technical support from IoT (Internet of things), smart city need to have three features of being instrumented, interconnected and intelligent. IoT provides the ability to manage, remotely monitor and control devices from massive streams of real-time data.Our model offers a scalable IoT video data analytics applications for Smart cities to end users, who can exploit scalability in both data storage and processing power to execute analysis on large or complex datasets. This model provides data analytics programming suites and environments in which developers and researchers can design scalable analytics services and applications. A cloud/edge-based automated video analysis system to process large numbers of video streams, where the underlying infrastructure is able to scale based on the number of camera devices and easy to integrate analytic application. The system automates the video analysis process and reduces manual intervention. The design of our model is developed to be easily extended for new kinds of IoT devices, message routing and queueing, and data analytics, to permit specific application to be programmed via the paradigm to be flexible yet simple.

Item Type: Article
Uncontrolled Keywords: Scalable, video data analytics, smart city
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 14 Sep 2020 11:18
Last Modified: 14 Sep 2020 11:18
URI: https://eprints.eudl.eu/id/eprint/281

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