Deployment of mobile nodes in a region of interest is a critical issue in building a mobile sensor network because it affects cost and detection capabilities of the system. The deployment of mobile sensors in essence is the movement of sensors from an initial position to a final optimal location. Considerable attention has recently been given to this deployment issue. Many of the distributed deployment schemes use the potential field method. In most cases, the negative gradient of the potential function becomes the feedback control input to a node. This assumes that the potential function is differentiable over the entire region. This assumption is valid primarily when the topology of the network is fixed. In this research, we analyze the stability of a network that uses piecewise smooth potential functions. A gravitation-like force is proposed to deploy a group of agents and to form a certain configuration. We use a nonsmooth version of the Lyapunov stability theory and LaSalle’s invariance principle to show asymptotic stability of the network which is governed by discontinuous dynamics. We propose a hierarchical structure using potential fields for mobile sensor network deployment. A group of mobile nodes first form a cluster using a potential field method and then cluster heads are used to establish a hexagonal structure that employs a higher level potential field. We consider specifically the problem of deploying a mobile sensor network so that a certain area coverage is realized and maintained. And we propose an algorithm for main taining the desired coverage that assumes the availability of a stochastic sensor model. The model reflects the decline of the sensor accuracy as the distance increases from the sensor. It is further assumed that each node’s sensor has a different sensing range to represent sensor performance deterioration due to power decay. The network deployment scheme combines artificial forces with individual sensor ranges. The validity and the effectiveness of the proposed algorithm are compared to the conventional methods in simulations. Simulation results confirm the effectiveness of the proposed algorithms with respect to a defined performance metric.

Autonomous mobile sensor networks consist of a number of autonomous mobile robots equipped with various sensors and tasked with a common mission. This thesis considers the topology control of such an ad hoc mobile sensor network. In particular, I studied the problem of controlling the size, with respect to a distance metric, of the network for general interactive forcing among agents. Developed is a stability result, allowing one to design force laws to control the spread of the network. Many of the current results assume a known and/or fixed topology of the graph representing the communication between the nodes, i.e. the graph laplacian is assumed constant. They also assume fixed and known force-laws. Hence, the results are limited to time-invariant dynamics. The research considers stability analysis of sensor networks, unconstrained by specific forcing functions or algorithms, and communication topologies. Since the graph topologies are allowed to change as the agents move about, the system dynamics become discontinuous in nature. Filippov’s calculus of differential equations with discontinuous right hand sides is used to formally characterize the multi-agent system with the above attributes. Lyapunov’s Stability Theory, applied to discontinuous systems, is then used to derive bounds on the norm of the system states given bounds on its initial states and input. The above derived stability results lend themselves to the derivation of methods for the design of algorithms or force-laws for mobile sensor networks. The efficacy of the derived results is illustrated through several examples where it is shown how they may be used for synthesizing a topology managing strategy. Examples are given of designing force-laws that limit the network in a desired area.

No description available.

In this thesis we develop a rigorous mathematical framework for analyzing and approximating optimal sensor placement problems for distributed parameter systems and apply these results to PDE problems defined by the convection-diffusion equations. The mathematical problem is formulated as a distributed parameter optimal control problem with integral Riccati equations as constraints. In order to prove existence of the optimal sensor network and to construct a framework in which to develop rigorous numerical integration of the Riccati equations, we develop a theory based on Bochner integrable solutions of the Riccati equations. In particular, we focus on ℐ_p-valued continuous solutions of the Bochner integral Riccati equation. We give new results concerning the smoothing effect achieved by multiplying a general strongly continuous mapping by operators in ℐ_p. These smoothing results are essential to the proofs of the existence of Bochner integrable solutions of the Riccati integral equations. We also establish that multiplication of continuous ℐ_p-valued functions improves convergence properties of strongly continuous approximating mappings and specifically approximating C₀-semigroups. We develop a Galerkin type numerical scheme for approximating the solutions of the integral Riccati equation and prove convergence of the approximating solutions in the ℐ_p-norm. Numerical examples are given to illustrate the theory. / Ph. D.

This research presents the development and proof of concept of a TeleGeoMonitoring (TGM) system for spatially monitoring and analyzing, in real-time, data derived from vehicle-mounted sensors. In response to the concern for vibration related injuries experienced by equipment operators in surface mining and construction operations, the prototype TGM system focuses on spatially monitoring vehicle vibration in real-time. The TGM vibration system consists of 3 components: (1) Data Acquisition Component, (2) Data Transfer Component, and (3) Data Analysis Component. A GPS receiver, laptop PC, data acquisition hardware, triaxial accelerometer, and client software make up the Data Acquisition Component. The Data Transfer Component consists of a wireless data network and a data server. The Data Analysis Component provides tools to the end user for spatially monitoring and analyzing vehicle vibration data in real-time via the web or GIS workstations. Functionality of the prototype TGM system was successfully demonstrated in both lab and field tests. The TGM vibration system presented in this research demonstrates the potential for TGM systems as a tool for research and management projects, which aim to spatially monitor and analyze data derived from mobile sensors in real-time. / Master of Science

There is an emerging class of applications that require long-term tracking and monitoring of mobile entities for characterising their contexts and behaviours using data from wireless sensors. Examples include monitoring animals in their natural habitat over the annual cycle; tracking shipping containers and their handling during transit; and monitoring air quality using sensors attached to bicycles used in public sharing schemes. All applications within this class require the acquisition of sensor data tagged with spatio-temporal information and uploaded wirelessly. Currently there is no solution targeting the entire class of applications, only point solutions focused on specific scenarios. This thesis presents a complete solution (firmware and hardware) for applications within this class that consists of attaching mobile sensor nodes to the entities for tracking and monitoring their behaviour, and deploying an infrastructure of base-stations for collecting the data wirelessly. The proposed solution is more energy efficient compared to the existing solutions that target specific scenarios, offering a longer deployment lifetime with a reduced size and weight of the devices. This is achieved mainly by using the VB-TDMA low-power data upload protocol proposed in this thesis. The mobile sensor nodes, consisting of the GPS and radio modules among others, and the base-stations are powered by batteries, and the optimisation of their energy usage is of primary concern. The presence of the GPS module, in particular its acquisition of accurate time, is used by the VB-TDMA protocol to synchronise the communication between nodes at no additional energy costs, resulting in an energy-efficient data upload protocol for sparse networks of mobile nodes, that can potentially be out of range of base-stations for extended periods of time. The VB-TDMA and an asynchronous data upload protocol were implemented on the custom-designed Prospeckz-5-based wireless sensor nodes. The protocols’ performances were simulated in the SpeckSim simulator and validated in real-world deployments of tracking and monitoring thirty-two Retuerta wild horses in the Doñana National Park in Spain, and a herd of domesticated horses in Edinburgh. The chosen test scenario of long-term wildlife tracking and monitoring is representative for the targeted class of applications. The VB-TDMA protocol showed a significantly lower power consumption than other comparable MAC protocols, effectively doubling the battery lifetime. The main contributions of the thesis are the development of the VB-TDMA data upload protocol and its performance evaluation, along with the development of simulation models for performance analysis of wireless sensor networks, validated using data from the two real-world deployments.

This thesis explores the role mobile sensor's mobility model and how it affects surveillance system performance in term of area coverage and detection effectiveness. Several algorithms which are categorized into three types, namely, fully coordinated mobility, fully random mobility and emergent mobility models are discussed with their advantages and limitations. A multi-agent platform to organize mobile sensor nodes, control nodes and actor nodes was implemented. It demonstrated great flexibility and was favourable for its distributed, autonomous and cooperative problem-solving characters. Realistic scenarios which are based on three KheperaIII mobile robots and a model which mimics Waterloo regional airport were used to examine the implementation platform and evaluate performance of different mobility algorithms. Several practical issues related to software configurations and interface library were addressed as by-products. The experimental results from both simulation and real platform show that the area coverage and the detection effectiveness vary with applying different mobility models. Fully coordinated model's super efficiency comes with carefully task planning and high requirements of sensor navigational accuracy. Fully random model is the least efficient in area coverage and detection because of the repetitive searching of each sensor and among sensors. A self-organizing algorithm named anti-flocking which mimics solitary animal's social behaviour was first proposed. It works based on quite simple rules for achieving purposeful coordinated group action without explicit global control. Experimental results demonstrate its attractive target detection efficiency in term of both detection rate and detection time while providing desirable features such as scalability, robustness and adaptivity. From the simulation results, the detection rate of the anti-flocking model increases by 36.5% and average detection time decreases by 46.2% comparing with the fully random motion model. The real platform results also reflect the superior performance improvement.

This thesis explores the role mobile sensor's mobility model and how it affects surveillance system performance in term of area coverage and detection effectiveness. Several algorithms which are categorized into three types, namely, fully coordinated mobility, fully random mobility and emergent mobility models are discussed with their advantages and limitations. A multi-agent platform to organize mobile sensor nodes, control nodes and actor nodes was implemented. It demonstrated great flexibility and was favourable for its distributed, autonomous and cooperative problem-solving characters. Realistic scenarios which are based on three KheperaIII mobile robots and a model which mimics Waterloo regional airport were used to examine the implementation platform and evaluate performance of different mobility algorithms. Several practical issues related to software configurations and interface library were addressed as by-products. The experimental results from both simulation and real platform show that the area coverage and the detection effectiveness vary with applying different mobility models. Fully coordinated model's super efficiency comes with carefully task planning and high requirements of sensor navigational accuracy. Fully random model is the least efficient in area coverage and detection because of the repetitive searching of each sensor and among sensors. A self-organizing algorithm named anti-flocking which mimics solitary animal's social behaviour was first proposed. It works based on quite simple rules for achieving purposeful coordinated group action without explicit global control. Experimental results demonstrate its attractive target detection efficiency in term of both detection rate and detection time while providing desirable features such as scalability, robustness and adaptivity. From the simulation results, the detection rate of the anti-flocking model increases by 36.5% and average detection time decreases by 46.2% comparing with the fully random motion model. The real platform results also reflect the superior performance improvement.

In wireless positioning system, in addition to channel error, the geometric re- lationship between sensor nodes and the target may also affect the positioning accuracy. The effect is called geometric dilution of precision (GDOP). GDOP is determined as ratio factor between location error and measurement error. A higher GDOP value indicates a larger location error in location estimation. Accordingly, the location performance will be poor. The GDOP can therefore be used as an in- dex of the positioning performance. In this thesis, approaches of tracking a moving target with extended Kalman filter (EKF) in a time-difference-of-arrival (TDOA) wireless positioning system are discussed. While the target changes its position with time, the geometric layout between sensor nodes and the target will become differ- ent. To maintain the good layout, the positioning system with mobile sensor nodes is considered. Therefore, the geometric layout can be possibly improved and GDOP effect can be reduced by the mobility of mobile sensor nodes. In order to find the positions that mobile sensor nodes should move to, a time-varying function based on the GDOP distribution is defined for finding the best solutions. Since the simu- lated annealing is capable of escaping local minima and finding the global minimum in an objective function, the simulated annealing algorithm is used in finding the best solutions in the defined function. Thus the best solutions can be determined as the destinations of mobile sensor nodes. When relocating mobile sensor nodes from their current positions to the destinations, they may pass through or stay in high GDOP regions before arriving at the destinations. To avoid the problem, we establish an objective function for path planning of mobile sensor nodes in order to minimize the overall positioning accuracy. Simulation results show that the mobile sensor nodes will accordingly change their positions while the target is moving. All the sensor nodes will maintain a surrounding region to localize the target and the GDOP effect can be effectively reduced.

A fundamental problem in mobile robotics is the exploration of unknown fields that might be inaccessible or hostile to humans. Exploration missions of great importance include geological survey, disaster prediction and recovery, and search and rescue. For missions in relatively large regions, mobile sensor networks (MSN) are ideal candidates. The basic idea of MSN is that mobile robots form a sensor network that collects information, meanwhile, the behaviors of the mobile robots adapt to changes in the environment. To design feasible motion patterns and control of MSN, we draw inspiration from biology, where animal groups demonstrate amazingly complex but adaptive collective behaviors to changing environments. The main contributions of this thesis include platform independent mathematical models for the coupled motion-sensing dynamics of MSN and biologically-inspired provably convergent cooperative control and filtering algorithms for MSN exploring unknown scalar fields in both 2D and 3D spaces. We introduce a novel model of behaviors of mobile agents that leads to fundamental theoretical results for evaluating the feasibility and difficulty of exploring a field using MSN. Under this framework, we propose and implement source seeking algorithms using MSN inspired by behaviors of fish schools. To balance the cost and performance in exploration tasks, a switching strategy, which allows the mobile sensing agents to switch between individual and cooperative exploration, is developed. Compared to fixed strategies, the switching strategy brings in more flexibility in engineering design. To reveal the geometry of 3D spaces, we propose a control and sensing co-design for MSN to detect and track a line of curvature on a desired level surface.