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      An IoT Surveillance System Based on a Decentralised Architecture

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          Abstract

          In the last few years, we witnessed numerous episodes of terrorist attacks and menaces in public crowded places. The necessity of better surveillance in these places pushed the development of new automated solutions to spot and notify possible menaces as fast as possible. In this work, we propose a novel approach to create a decentralized architecture to manage patrolling drones and cameras exploiting lightweight protocols used in the internet of things (IoT) domain. Through the adoption of the mist computing paradigm it is possible to give to all the object of the smart ecosystem a cognitive intelligence to speed up the recognition and analysis tasks. Distributing the intelligence among all the objects of the surveillance ecosystem allows a faster recognition and reaction to possible warning situations. The recognition of unusual objects in certain areas, e.g., airports, train stations and bus stations, has been made using computer vision algorithms. The adoption of the IoT protocols in a hierarchical architecture provides high scalability allowing an easy and painless join of other smart objects. Also a study on the soft real-time feasibility has been conducted and is herein presented.

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          Most cited references49

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          Wireless communications with unmanned aerial vehicles: opportunities and challenges

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            Hybrid Method for Minimizing Service Delay in Edge Cloud Computing Through VM Migration and Transmission Power Control

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              The Benefits of Self-Awareness and Attention in Fog and Mist Computing

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                26 March 2019
                March 2019
                : 19
                : 6
                : 1469
                Affiliations
                DIMES Department—University of Calabria, via Pietro Bucci cubo 39/c V piano, 87036 Rende (CS), Italy; p.raimondo@ 123456dimes.unical.it (P.R.); m.tropea@ 123456dimes.unical.it (M.T.); derango@ 123456dimes.unical.it (F.D.R.); aiello.carmine@ 123456outlook.it (C.A.)
                Author notes
                [* ]Correspondence: afsantamaria@ 123456dimes.unical.it ; Tel.: +39-984-494660
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0003-0748-3511
                https://orcid.org/0000-0003-0593-5254
                Article
                sensors-19-01469
                10.3390/s19061469
                6471351
                30917519
                7644b95f-a7f4-4170-9437-5a1b06f65989
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 January 2019
                : 17 March 2019
                Categories
                Article

                Biomedical engineering
                computer vision,surveillance,drones,internet of things,lightweight protocols,mist computing,opencv

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