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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In the last years, vehicular networking has grown up in terms of interest and transmission capability, due to the possibility of exploiting the distributed communication paradigm in a mobile scenario, where moving nodes are represented by vehicles. The different existing standards for vehicular ad-hoc networks, such as dedicate short range communication (DSRC), wireless access for vehicular environment (WAVE)/IEEE802.11p, have given to the research community the possibility of developing new medium access control (MAC) and routing schemes, in order to enhance the quality and the comfort of mobile users who are driving their vehicles. In this paper, we focus our attention on the optimization of traffic flowing in a vehicular environment with vehicle-2-roadside capability. As shown later, the proposed idea exploits the information that is gathered by road-side units to redirect traffic flows (in terms of vehicles) to less congested roads, with an overall system optimization, also in terms of carbon dioxide emissions reduction. An analytical model, as well as a set of pseudo-code instructions, have been introduced in the paper. A deep campaign of simulations has been carried out to give more effectiveness to our proposal. Index Terms-VANET, IEEE 802.11p, wireless access for vehicular environment (WAVE), dedicate Short Range Communication (DSRC), congestion, traffic flow, predictive re-routing, CO 2 emissions. I. INTRODUCTIONI N THE last years, the interest in vehicular opportunities and potentialities has drastically grown, due to the numerous advantages inherited from mobility solutions in urban/suburban environments. In particular, Vehicular Ad-hoc NETworks (VANETs) represent a new and modern paradigm of communication, where the nodes are able to communicate in a distributed manner, based on the ad-hoc paradigm [1], [2].VANETs are going to be considered as one of the first adhoc networking reality in nowadays applications, enabling the transmission among nearby vehicles as well as between vehicles and nearby external devices. In fact, each node is equipped with a wireless device, the On-Board Unit (OBU), which is able to interact with the infrastructure equipment for comfort/security applications, trade and infotainment services.

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