UAV-Based IoT Platform: A Crowd Surveillance Use Case

Naser Hossein Motlagh*, Miloud Bagaa, Tarik Taleb

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

407 Citations (Scopus)


Unmanned aerial vehicles are gaining a lot of popularity among an ever growing community of amateurs as well as service providers. Emerging technologies, such as LTE 4G/5G networks and mobile edge computing, will widen the use case scenarios of UAVs. In this article, we discuss the potential of UAVs, equipped with loT devices, in delivering loT services from great heights. A high-level view of a UAV-based integrative loT platform for the delivery of loT services from large height, along with the overall system orchestrator, is presented in this article. As an envisioned use case of the platform, the article demonstrates how UAVs can be used for crowd surveillance based on face recognition. To evaluate the use case, we study the offloading of video data processing to a MEC node compared to the local processing of video data onboard UAVs. For this, we developed a testbed consisting of a local processing node and one MEC node. To perform face recognition, the Local Binary Pattern Histogram method from the Open Source Computer Vision is used. The obtained results demonstrate the efficiency of the MEC-based offloading approach in saving the scarce energy of UAVs, reducing the processing time of recognition, and promptly detecting suspicious persons.

Original languageEnglish
Pages (from-to)128-134
Number of pages7
JournalIEEE Communications Magazine
Issue number2
Publication statusPublished - Feb 2017
MoE publication typeA1 Journal article-refereed


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