Air pollution monitoring has recently become an issue of utmost importance in our society. Despite the fact that crowdsensing approaches could be an adequate solution for urban areas, they cannot be implemented in rural environments. Instead, deploying a fleet of UAVs could be considered an acceptable alternative. Embracing this approach, this paper proposes the use of UAVs equipped with off-the-shelf sensors to perform air pollution monitoring tasks. These UAVs are guided by our proposed Pollution-driven UAV Control (PdUC) algorithm, which is based on a chemotaxis metaheuristic and a local particle swarm optimization strategy. Together, they allow automatically performing the monitoring of a specified area using UAVs. Experimental results show that, when using PdUC, an implicit priority guides the construction of pollution maps by focusing on areas where the pollutants' concentration is higher. This way, accurate maps can be constructed in a faster manner when compared to other strategies. The PdUC scheme is compared against various standard mobility models through simulation, showing that it achieves better performance. In particular, it is able to find the most polluted areas with more accuracy and provides a higher coverage within the time bounds defined by the UAV flight time.
The concept of smart city has emerged worldwide as a feasible answer to the challenges raised by the increasing urbanisation. From the technological point of view, guaranteeing ubiquitous connectivity, reliable communications and seamless integration of multiple network access technologies are mandatory in a smart city. This is in contrast with the current infrastructure deployment in several urban areas, which is characterised by lack of ubiquitous connectivity and coverage and by fragmentation of networks that are usually deployed by different operators and without any centralised control by the city authorities. In this paper, we look at the heterogeneity of devices and network technologies under a different perspective by not perceiving it as a limitation but as a potential to increase the connectivity in a smart city. We propose a new generation of network nodes, called stem nodes, based on the innovative idea of 'stemness', which pushes forward the well-known self-configuration and self-management concepts towards the idea of node mutation and evolution. We also deployed prototypes that demonstrate the stem-node architecture and basic operations in different hardware platforms of common communication devices (an Alix-based router, a laptop and a smartphone).
International audienceMobile devices currently available on the market have a plethoraof features and enough computing power to make them, at the same time,information consumers, forwarders and producers. Since they are also providedwith a set of sensors and usually battery operating, they are perfect candidatesto devise a network infrastructure tailored to function during disruptive events.When everything else fails, they could autonomously reorganize and provide tothe civilians and rescue teams valuable services and information. In this paperwe adapt and enhance a previous designed framework, capable to epidemicallydiuse the proper software updates to its nodes, in order to deploy any kind ofservice as a prompt response to the needs raised in emergency situations. Wefurther propose and integrate a new smart positioning strategy, to speed up thediusion of software updates by also keeping under control the overall networkoverhead. The achieved results show the feasibility of our proposal and howthe dynamics of diusion are enhanced by the smart positioning algorithm
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