Optimal Deployment of Wireless Sensor Networks for Air Pollution Monitoring

International audienceRecently, air pollution monitoring emerges as a main service of smart cities because of the increasing industrialization and the massive urbanization. Wireless sensor networks (WSN) are a suitable technology for this purpose thanks to their substantial benefits including low cost and autonomy. Minimizing the deployment cost is one of the major challenges in WSN design, therefore sensors positions have to be carefully determined. In this paper, we propose two integer linear programming formulations based on real pollutants dispersion modeling to deal with the minimum cost WSN deployment for air pollution monitoring. We illustrate the concept by applying our models on real world data, namely the Nottingham City street lights. We compare the two models in terms of execution time and show that the second flow-based formulation is much better. We finally conduct extensive simulations to study the impact of some parameters and derive some guidelines for efficient WSN deployment for air pollution monitoring

Performance Evaluation of Channel Access Methods for Dedicated IoT Networks

International audienceNetworking technologies dedicated for the Internet of Things are different from the classical mobile networks in terms of architecture and applications. This new type of network is facing several challenges to satisfy specific user requirements. Sharing the communication medium between (hundreds of)thousands of connected nodes and one base station is one of these main requirements, hence the necessity to imagine new solutions, or to adapt existing ones, for medium access control. In this paper, we start by comparing two classical medium access control protocols, CSMA/CA and Aloha, in the context of Internet of Things dedicated networks. We continue by evaluating a specific adaptation of Aloha, already used in low-power wide areanetworks, where no acknowledgement messages are transmitted in the network. Finally, we apply the same concept to CSMA/CA, showing that this can bring a number of benefits. The results we obtain after a thorough simulation study show that the choice of the best protocol depends on many parameters (number of connected objects, traffic arrival rate, allowed retransmissionnumber), as well as on the metric of interest (e.g. packet reception probability or energy consumption)

Augmented Reality in Smart Cities: A Multimedia Approach

Intro: This paper presents an advance overview of utilizing Augmented Reality (AR) in smart cities. Although, Smart cities contain six major aspects (mobility, economy, government, environment, living, and people), this paper focuses on three of them that have more potentiality in using virtual assistant (mobility, environment, and living). Methodology: Presenting a state-of-the-art review studies undertake between 2013 and 2017, which is driven from highlighted libraries is the aim of this research. After exact examine, 15 emphasized studies are chosen to divide the main aspects while 120 selective articles are supporting them. These categorizes have been critically compared with an aim, method and chronological perspectives. Results: First of All, Environmental issues (Museums industry) attract the most attention of researchers while the living issues (maintenance) have lower significant compare t latter and mobility (indoor-outdoor navigation) attract the least. Moreover, a close connection between academic and industry fields is going to be created. Conclusions: it has been concluded that, because of economic advantages, utilizing AR technology has improved in the tourism and maintenance. Moreover, until now, most of studies try to prove their concept rather than illustrate well stablished analytic approach. Because of hardware and software improvement, it is essential for the future studies to evaluate their hypothesis in a real urban context

Resilient IoT-based Monitoring System for Crude Oil Pipelines

International audiencePipeline networks dominate the oil and gas mid-stream sector, and although the safest means of transportation for oil and gas products, they are susceptible to failures. These failures are due to manufacturing defects, environmental effects, material degradation, or third party interference through sabotage and vandalism. Internet of Things (IoT)-based solutions are promising to address these by monitoring and predicting failures. However, some challenges remain in the deployment of industrial IoT-based solutions, as the reliability, the robustness, the maintainability, the scalability, the energy consumption, etc. This paper is therefore aimed at highlighting potential solutions for detection and mitigation of pipeline failures while addressing the robustness, the cost and scalability issues of such approach efficiently across the network infrastructure, data and service layers

Optimal WSN Deployment Models for Air Pollution Monitoring

International audienceAir pollution has become a major issue of modern megalopolis because of industrial emissions and increasing urbanization along with traffic jams and heating/cooling of buildings. Monitoring urban air quality is therefore required by municipalities and by the civil society. Current monitoring systems rely on reference sensing stations that are precise but massive, costly and therefore seldom. In this paper, we focus on an alternative or complementary approach, with a network of low cost and autonomic wireless sensors, aiming at a finer spatiotemporal granularity of sensing. Generic deployment models of the literature are not adapted to the stochastic nature of pollution sensing. Our main contribution is to design integer linear programming models that compute sensor deployments capturing both the coverage of pollution under time-varying weather conditions and the connectivity of the infrastructure. We evaluate our deployment models on a real data set of Greater London. We analyze the performance of the proposed models and show that our joint coverage and connectivity formulation is tight and compact, with a reasonable enough execution time. We also conduct extensive simulations to derive engineering insights for effective deployments of air pollution sensors in an urban environment

On the Deployment of Wireless Sensor Networks for Air Quality Mapping: Optimization Models and Algorithms

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Méthodes d'Accès au Canal pour les Réseaux Dédiés à l'Internet des Objets

Dedicated networks for the Internet of Things appeared with the promise of connecting thousands of nodes, or even more, to a single base station in a star topology. This new logic represents a fundamental change in the way of thinking about networks, after decades during which research work mainly focused on multi-hop networks.Internet of Things networks are characterized by long transmission range, wide geographic coverage, low energy consumption and low set-up costs. This made it necessary to adapt the protocols at different architectural layers in order to meet the needs of these networks.Several players compete in the Internet of Things market, each trying to establish the most efficient solution. These players are mostly focused on modifying the physical layer, on the hardware part or through proposing new modulations. However, with regard to the channel access control solution (known as the MAC protocol), all the solutions proposed by these players are based on classic approaches such as Aloha and CSMA.The objective of this thesis is to propose a dynamic MAC solution for networks dedicated to the Internet of Things. The proposed solution has the ability to adapt to network conditions. This solution is based on a machine learning algorithm that learns from network history in order to establish the relationship between network conditions, MAC layer parameters and network performance in terms of reliability and energy consumption. The solution also has the originality of making possible the coexistence of nodes using different MAC configurations within the same network. The results of simulations have shown that a MAC solution based on machine learning could take advantage of the good properties of different conventional MAC protocols. The results also show that a cognitive MAC solution always offers the best compromise between reliability and energy consumption, while taking into account the fairness between the nodes of the network. The cognitive MAC solution tested for high density networks has proven better scalability compared to conventional MAC protocols, which is another important advantage of our solution.Les réseaux dédiés pour l’Internet des Objets sont apparus avec la promesse de connecter des milliers de nœuds, voire plus, à une seule station de base dans une topologie en étoile. Cette nouvelle logique représente un changement fondamental dans la façon de penser les réseaux, après des décennies pendant lesquelles les travaux de recherche se sont focalisés sur les réseaux multi-sauts.Les réseaux pour l’Internet des Objets se caractérisent par la longue portée des transmissions, la vaste couverture géographique, une faible consommation d’énergie et un bas coût de mise en place. Cela a rendu nécessaire des adaptations à tous les niveaux protocolaires afin de satisfaire les besoins de ces réseaux.Plusieurs acteurs sont en concurrence sur le marché de l’Internet des Objets, essayant chacun d’établir la solution la plus efficiente. Ces acteurs se sont concentrés sur la modification de la couche physique, soit au niveau de la partie matérielle, soit par la proposition de nouvelles techniques de modulation. Toutefois, en ce qui concerne la solution de contrôle d’accès au canal (connue sous le nom de couche MAC), toutes les solutions proposées par ces acteurs se fondent sur des approches classiques, tel que Aloha et CSMA.L'objectif de cette thèse est de proposer une solution MAC dynamique pour les réseaux dédiés à l’Internet des Objets. La solution proposée a la capacité de s'adapter aux conditions du réseau. Cette solution est basée sur un algorithme d'apprentissage automatique, qui apprend de l'historique du réseau afin d'établir la relation entre les conditions du réseau, les paramètres de la couche MAC et les performances du réseau en termes de fiabilité et de consommation d'énergie. La solution possède également l'originalité de faire coexister des nœuds utilisant de différentes configurations MAC au sein du même réseau. Les résultats de simulations ont montré qu'une solution MAC basée sur l'apprentissage automatique pourrait tirer profit des avantages des différents protocoles MAC classiques. Les résultats montrent aussi qu'une solution MAC cognitive offre toujours le meilleur compromis entre fiabilité et consommation d'énergie, tout en prenant en compte l'équité entre les nœuds du réseau. La solution MAC cognitive testée pour des réseaux à haute densité a prouvé des bonnes propriétés de passage à l’échelle par rapport aux protocoles MACs classiques, ce qui constitue un autre atout important de notre solution

Optimal Deployment of Wireless Sensor Networks for Air Pollution Monitoring

International audienceRecently, air pollution monitoring emerges as a main service of smart cities because of the increasing industrialization and the massive urbanization. Wireless sensor networks (WSN) are a suitable technology for this purpose thanks to their substantial benefits including low cost and autonomy. Minimizing the deployment cost is one of the major challenges in WSN design, therefore sensors positions have to be carefully determined. In this paper, we propose two integer linear programming formulations based on real pollutants dispersion modeling to deal with the minimum cost WSN deployment for air pollution monitoring. We illustrate the concept by applying our models on real world data, namely the Nottingham City street lights. We compare the two models in terms of execution time and show that the second flow-based formulation is much better. We finally conduct extensive simulations to study the impact of some parameters and derive some guidelines for efficient WSN deployment for air pollution monitoring