Leveraging the Potential of WSN for an Efficient Correction of Air Pollution Fine-Grained Simulations

International audienc

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

International audienc

Target Tracking Using Wireless Sensor Networks

Tracking of targets in remote inaccessible areas is an important application of Wireless Sensor Networks (WSNs). The use of wired networks for detecting and tracking of intruders is not feasible in hard-to-reach areas. An alternate approach is the use of WSNs to detect and track targets. Furthermore, the requirements of the tracking problem may not necessarily be known at the time of deployment. However, issues such as low onboard power, lack of established network topology, and the inability to handle node failures have limited the use of WSNs in these applications. In this dissertation, the performance of WSNs in remote surveillance type of applications will be addressed through the development of distributed tracking algorithms. The algorithm will focus on identifying a minimal set of nodes to detect and track targets, estimating target location in the presence of measurement noise and uncertainty, and improving the performance of the WSN through distributed learning.The selection of a set of sensor nodes to detect and track a target is first studied. Inactive nodes are forced into `sleeping' mode to conserve power, and activated only when required to sense the target. The relative distance and angle of the target from sensor nodes are used to determine which of the sensors are needed to track the target.The effect of noisy measurements on the estimation of the position of the target is addressed through the implementation of a Kalman filter. Contrary to centralized Kalman filter implementations reported in the literature, implementation of the distributed Kalman filter is considered in the proposed solution.Distributed learning is implemented by passing on the knowledge of the target, i.e. the filter state and covariance matrix onto the subsequent node running the filter. The problem is mathematically formulated, and the stability and tracking error of the proposed strategy are rigorously examined. Numerical examples are then used to demonstrate the utility of the proposed technique.It will be shown by mathematical proofs and numerical simulation in this dissertation that distributed detection and tracking using a limited number of nodes can result in efficient tracking in the presence of measurement noise. Furthermore, minimizing the number of active sensors will reduce communication overhead and power consumption in networks, improve tracking efficiency, and increase the useful life span of WSNs

Networking and application interface technology for wireless sensor network surveillance and monitoring

Distributed unattended ground sensor (UGS) networks are commonly deployed to support wide area battlefield surveillance and monitoring missions. The information they generate has proven to be valuable in providing a necessary tactical information advantage for command and control, intelligence and reconnaissance field planning. Until recently, however, there has been greater emphasis within the defence research community for UGS networks to fulfil their mission objectives successfully, with minimal user interaction. For a distributed UGS scenario, this implies a network centric capability, where deployed UGS networks can self-manage their behaviour in response to dynamic environmental changes. In this thesis, we consider both the application interface and networking technologies required to achieve a network centric capability, within a distributed UGS surveillance setting. Three main areas of work are addressed towards achieving this. The first area of work focuses on a capability to support autonomous UGS network management for distributed surveillance operations. The network management aspect is framed in terms of how distributed sensors can collaborate to achieve their common mission objectives and at the same time, conserve their limited network resources. A situation awareness methodology is used, in order to enable sensors which have similar understanding towards a common objective to be utilised, for collaboration and to allow sensor resources to be managed as a direct relationship according to, the dynamics of a monitored threat. The second area of work focuses on the use of geographic routing to support distributed surveillance operations. Here we envisage the joint operation of unmanned air vehicles and UGS networks, working together to verify airborne threat observations. Aerial observations made in this way are typically restricted to a specific identified geographic area. Information queries sent to inquire about these observations can also be routed and restricted to using this geographic information. In this section, we present our bio-inspired geographic routing strategy, with an integrated topology control function to facilitate this. The third area of work focuses on channel aware packet forwarding. Distributed UGS networks typically operate in wireless environments, which can be unreliable for packet forwarding purposes. In this section, we develop a capability for UGS nodes to decide which packet forwarding links are reliable, in order to reduce packet transmission failures and improve overall distributed networking performance