Wireless sensor and robot networks (WSRNs) are an integration of wireless sensor network (WSNs) and multi-robot systems. They comprise of networked sensor and mobile robots that communicate via wireless links to perform distributed sensing and actuation tasks in a region of interest (ROI). In addition to gathering and reporting data from the environment, sensors may also report failures of neighboring sensors or lack of coverage in certain neighborhood to nearby mobile robot. Once an event has been detected, robots coordinate with each other to make a decision on the most appropriate way to perform the action. Coverage can be established and improved in different ways in wireless sensor and robot networks. Initial random sensor placement, if applied, may be improved via robot-assisted sensor relocation or additional placement. One or more robots may carry sensors and move within the ROI; while traveling, they drop sensors at proper positions to construct desired coverage. Robots may relocate and place spare sensors according to certain energy optimality criteria. This thesis proposes a solution, which we call Election-Based Deployment (EBD), for simultaneous sensor deployment and coverage maintenance in multi-robot scenario in failure-prone environment. To our knowledge, it is the first carrier-based localized algorithm that is able to achieve 100% coverage of the ROI with multiple robots in failure-prone environment since it combines both sensor deployment and coverage maintenance process. We can observe from the simulation results that EBD outperforms the existing algorithms and balances the workload of robots while reducing the communication overhead to a great extent.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / For any automated surveillance operation to be successful, it is critical to have sensing resources strategically positioned to observe, interpret, react and maybe even predict events.In many practical scenarios, it is also expected that different zones within a surveillance area may have different probability of event detection (or false alarm) requirements. The operational objective in such surveillance systems is to optimize resources (number of sensors and the associated cost) and their deployment while guaranteeing a certain assured level of detection/false alarm performance. In this dissertation, we study two major challenges related to sensor deployment in distributed sensor networks (DSNs) for detection applications. The first problem we study is the sensor deployment problem in which we ask the following question: Given a finite number of sensors (with a known sensing profile), how can we deploy these sensors such that we best meet the detection and false alarm requirements in a DSN employing a specific information fusion rule? Even though sensor deployment has garnered significant interest in the past, a unified, analytical framework to model and study sensor deployment is lacking. Additionally, the algorithms proposed in literature are typically heuristic in nature and are limited to (1) simplistic DSN fusion architectures, and (2) DSNs with uniform detection/false alarm requirements. In this dissertation, we propose a novel treatment of the sensor deployment problem using concepts from optimal control theory. Specifically, the deployment problem is formulated as a linear quadratic regulator (LQR) problem which provides a rigorous and analytical framework to study the deployment problem. We develop new sensor deployment algorithms that are applicable to a wide range of DSN architectures employing different fusion rules such as (1) logical OR fusion; (2) value fusion; (3) majority decision fusion, and (4) optimal decision fusion. In all these cases, we demonstrate that our proposed control theoretic deployment approach is able to significantly outperform previously proposed algorithms. The second problem considered in this dissertation is the “self healing” problem in which we ask the following question: After the failure of a number of sensors, how can one reconfigure the DSN such that the performance degradation due to sensor loss is minimized? Prior efforts in tackling the self healing problem typically rely on assumptions that don’t accurately capture the behavior of practical sensors/networks and focus on minimizing performance degradation at a local area of the network instead of considering overall performance of the DSN. In this work, we propose two self healing strategies the first approach relies on adjusting decision thresholds at the fusion center. The second approach involves sensor redeployment based on our control theoretic deployment framework. Simulation results illustrate that the proposed algorithms are effective in alleviating the performance degradation due to sensor loss.

In this dissertation, we proposed solutions on novel sensor deployment and diagnoser design to efficiently detect stochastic faults in PLC based automated systems First, a fuzzy quantitative graph based sensor deployment was called upon to model cause-effect relationship between faults and sensors. Analytic hierarchy process (AHP) was used to aggregate the heterogeneous properties between sensors and faults into single edge values in fuzzy graph, thus quantitatively determining the fault detectability. An appropriate multiple objective model was set up to minimize fault unobservability and cost while achieving required detectability performance. Lexicographical mixed integer linear programming and greedy search were respectively used to optimize the model, thus assigning the sensors to faults. Second, a diagnoser based on real time fuzzy Petri net (RTFPN) was proposed to detect faults in discrete manufacturing systems. It used the real time PN to model the manufacturing plant while using fuzzy PN to isolate the faults. It has the capability of handling uncertainties and including industry knowledge to diagnose faults. The proposed approach was implemented using Visual Basic, and tested as well as validated on a dual robot arm. Finally, the proposed sensor deployment approach and diagnoser were comprehensively evaluated based on design of experiment techniques. Two-stage statistical analysis including analysis of variance (ANOVA) and least significance difference (LSD) were conducted to evaluate the diagnosis performance including positive detection rate, false alarm, accuracy and detect delay. It illustrated the proposed approaches have better performance on those evaluation metrics. The major contributions of this research include the following aspects: (1) a novel fuzzy quantitative graph based sensor deployment approach handling sensor heterogeneity, and optimizing multiple objectives based on lexicographical integer linear programming and greedy algorithm, respectively. A case study on a five tank system showed that system detectability was improved from the approach of signed directed graph's 0.62 to the proposed approach's 0.70. The other case study on a dual robot arm also show improvement on system's detectability improved from the approach of signed directed graph's 0.61 to the proposed approach's 0.65. (2) A novel real time fuzzy Petri net diagnoser was used to remedy nonsynchronization and integrate useful but incomplete knowledge for diagnosis purpose. The third case study on a dual robot arm shows that the diagnoser can achieve a high detection accuracy of 93% and maximum detection delay of eight steps. (3) The comprehensive evaluation approach can be referenced by other diagnosis systems' design, optimization and evaluation.

Experimental design can be vital when experiments are resource-exhaustive and time-consuming. In this work, we carry out experimental design in the Bayesian framework. To measure the amount of information that can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, MLMC can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the MLMC method imposes fewer assumptions, such as the asymptotic concentration of posterior measures, required for instance by the Laplace approximation (LA). We test the MLMC method using two numerical examples. The first example is the design of sensor deployment for a Darcy flow problem governed by a one-dimensional Poisson equation. We place the sensors in the locations where the pressure is measured, and we model the conductivity field as a piecewise constant random vector with two parameters. The second one is chemical Enhanced Oil Recovery (EOR) core flooding experiment assuming homogeneous permeability. We measure the cumulative oil recovery, from a horizontal core flooded by water, surfactant and polymer, for different injection rates. The model parameters consist of the endpoint relative permeabilities, the residual saturations and the relative permeability exponents for the three phases: water, oil and microemulsions. We also compare the performance of the MLMC to the LA and the direct Double Loop Monte Carlo (DLMC). In fact, we show that, in the case of the aforementioned examples, MLMC combined with LA turns to be the best method in terms of computational cost.

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Les progrès de la robotique mobile nous permettent aujourd'hui d'ajouter la notion de mobilité dans plusieurs classes de réseaux de capteurs sans fil. Le déploiement de capteurs mobiles est possible et utile dans de nombreuses applications, comme la surveillance de l'environnement, les applications dans l'industrie, dans la santé et le domaine militaire. Le terme robot mobile peut représenter n'importe quel type de robot avec la capacité de modifier sa position. Cette notion inclut une vaste gamme de robots industriels utilisés dans les lignes de production. Dans le contexte spécifique de cette thèse, l'attention se focalise uniquement sur les robots mobiles et plus particulièrement les véhicules autonomes dont les mouvements ne sont pas limités par leur taille physique. Ainsi, un robot ou un groupe de robots mobiles peuvent être utilisés pour explorer des environnements inconnus et effectuer une variété de fonctions. La mobilité du robot dans le contexte des réseaux de capteurs, nous permet de résoudre les problèmes qui ne pourraient pas être résolues dans un cas statique. Les robots mobiles permettent d'augmenter la robustesse du réseau en remplaçant des nœuds de capteurs et de s'adapter aux environnements inconnus ou dynamiques. Deux thèmes sont abordées dans cette thèse : la conception d'un intergiciels pour les réseaux de robots mobiles et un ensemble d'approches pour le déploiement de robots mobiles dans le cadre de réseaux de capteurs sans fil. L'intergiciel proposé et décrit dans cette thèse permet à l'utilisateur de facilement mettre en œuvre différents types d'algorithmes de déploiement pour les robots mobiles. Il permet de déployer une application sur la station de base centrale qui permet à un utilisateur de rassembler toutes les informations captées par la flotte de robots. L'application de la station de base permet à un utilisateur d'envoyer des commandes à un groupe ou à un robot, introduisant ainsi la commande manuelle en option dans le réseau robotique. L'intergiciel présenté dans ce travail est dédié à être utilisé avec des robots mobiles Wifibot. Il permet réaliser plusieurs tâches. Tout d'abord, il interagit avec le microgiciel du robot pour piloter les moteurs des roues et recueille les informations concernant la sortie du capteur et de l'état de la batterie. Deuxièmement, il gère la communication avec d'autres robots et les stations de base du réseau. Troisièmement, il traite les informations sur l'environnement et les messages reçus des voisins dans le réseau. Enfin, il réagit et il s'adapte de manière rapide et fiable pour aux événements de l'environnement. Dans la deuxième partie de la thèse, trois problèmes sont présentés et analysés : le problème de l'amélioration de la qualité de service avec l'utilisation des réseaux robotiques mobiles, la couverture du point d'intérêt avec des robots mobiles et la découverte de points d'intérêt et leur couverture avec l'utilisation des robots mobiles. Le premier problème est résolu avec l'utilisation de l'algorithme de déploiement qui améliore les performances de la transmission multimédia. Cet algorithme utilise une méthode intrusive pour réunir les métriques de qualité de service. Ensuite, l'attention est focalisé sur l'application des réseaux de capteurs sans fil est la surveillance de l'environnement. Au lieu de surveiller toute la région, couvrir seulement un ensemble de points d'intérêt spécifiques accroît les performances du réseau et réduit le coût de déploiement. Nous faison l'hypothèse que la station de base fixe est placé à l'intérieur du domaine d'intérêt, tandis que les robots mobiles disponibles couvrent le point d'intérêt et relayent l'information vers la station de base. L'approche pour résoudre le dernier problème est basée sur le mouvement continu et à vitesse variable de capteurs mobiles, qui suivent des trajectoires circulaires concentriques afin d'explorer et de couvrir le domaine d'intérêt. En se déplaçant constamment, les capteurs exécutent la tâche de découverte de l'environnement et, en ajustant la vitesse de déplacement, ils répondent aux contraintes de la couverture et la connectivité avec la station de base. L'algorithme installé sur tous les capteurs mobiles est distribué et introduit une nouvelle technique de calcul de la vitesse en fonction des informations disponibles à partir des capteurs dans le voisinage à un-saut. Ces algorithmes de déploiement de robots mobiles ont prouvé leur faisabilité à travers de nom- breuses simulations ainsi que dans la mise en pratique en s'appuyant sur l'intergiciel proposé.

Existen muchos trabajos relacionados con el diseño y desarrollo de nodos sensores, donde se presentan gran variedad de aplicaciones. Las redes de sensores inalámbricos pueden facilitarnos y mejorar algunos aspectos de nuestra vida diaria. Es fácil, pensar que si este tipo de dispositivo es tan beneficioso para nosotros y para el entorno donde vivimos, su precio debería ser relativamente barato. Pero podemos comprobar que esto no es así. ¿Por qué estos dispositivos son tan caros? ¿Sería posible desarrollar dispositivos con las mismas capacidades y precios más económicos? ¿Cómo puedo fabricar mis nodos sensores de bajo coste? Esta tesis responde a estas preguntas y muestra algunas de las muchas aplicaciones que los nodos sensores pueden tener. En esta tesis hemos propuesto (e implementado en algunos casos) el desarrollo de nodos sensores para la monitorización del medio, a partir de dispositivos de bajo coste. Para la implementación de un nodo sensor, y en definitiva la red que une a todos estos nodos, es importante conocer el medio donde trabajarán. A lo largo de este documento se presentan las investigaciones llevadas a cabo para el desarrollo de sensores en tres ámbitos de aplicación. En el primero de ellos, se desarrollan dispositivos multisenores para la monitorización del medio. La aplicación de las redes de sensores inalámbricas al medio natural, precisa un estudio de cómo se ven afectadas las señales, en función de la distancia, vegetación, humedad del ambiente, etc. Focalizamos nuestros desarrollos en la verificación de incendios en zonas rurales y en el control de plagas en viñedos donde la detección precoz de estos eventos genera elevados ahorros económicos. También proponemos el desarrollo de una red de collares sensores para ganado domestico, que nos ayudará a reducir y prevenir en muchos casos, los ataques de lobos y hurtos de crías. Por último, dentro de este grupo, presentamos una red permite detectar anomalía de los materiales en edificios y red de sensores que nos permite monitorizar las personas mayores o deficientes, que se mueven junto con un grupo, en una excursión o actividad. El segundo grupo de aplicaciones, hace referencia a la monitorización de espacios en entornos de interior. Para ello hemos analizado el comportamiento de las señales inalámbricas en diferentes escenarios. Los resultados, nos han permitido extraer un nuevo método de diseño de las redes inalámbricas en interiores. Nuestro método, permite definir la mejor ubicación de los dispositivos de red y nodos sensores en interiores con un ahorro en el número de sensores del 15%. Por último, se presenta el estudio sobre las comunicaciones subacuáticas basadas en las ondas electromagnéticas donde analizamos la dependencia de las comunicaciones subacuáticas en agua dulce en función de la frecuencia, temperatura, tasas de transferencia de datos y modulación. Relacionado con el medio subacuático, presentamos 2 propuestas. La primera de ellas hace referencia a la implementación de una red de sensores para granjas marinas que nos permite reducir la cantidad de residuos depositados en el lecho marino y reducir el porcentaje de comida desperdiciada. La segunda propuesta es el desarrollo de dos sensores oceanográficos que nos permitirían controlar la cantidad de comida y heces depositadas en el suelo y controlar la turbidez del agua de manera muy simple y económica Todos estos desarrollos y propuestas, han estado precedidos por un exhaustivo estudio sobre los problemas energéticos que las redes de sensores inalámbricas presentan y las técnicas que pueden emplearse, para prolongar la vida útil de la red y mejorar su estabilidad. / There are many works related to the design and development of sensor nodes which present several applications. Wireless sensor networks can facilitate and improve some aspects of our daily lives. It is easy to think that if this type of device is so beneficial to us and to our environment, its price should be relatively cheap. But we can see that this is not true. Why these devices are so expensive? Would it be possible to develop devices with the same capabilities and lower prices? How can I make my low-cost sensor nodes? This dissertation answers these questions and shows some of the many applications that sensor nodes may have. In this dissertation, we propose (and implement in some cases) the development of sensor nodes for environmental monitoring, from low-cost devices. For the implementation of a sensor node and network which joins all these nodes, it is important to know the environment where they will work. Throughout this dissertation, we present the research carried out for the development of sensors in three main application areas. In the first of these areas, we present multisensor devices developed for environmental monitoring. The application of wireless sensor networks to the environment requires a study of how signals are affected depending on the distance, vegetation, ambient humidity, etc. We focus our developments on the fire detection in rural areas and on the control of pests in vineyards where the early detection of these events generates high economic savings. We also propose the development of a sensor network which will help us to reduce and prevent wolves¿ attacks and theft in livestock. Finally, within this group, we present a network to detect material anomalies in building and a sensor network which allows us to monitor the elderly or disabled people who move along with a group on a tour or activity. The second group of applications is related to the monitoring of spaces in indoor environments. For this, we analyze the behavior of wireless signals in different scenarios. These results allowed us to extract a new method for designing wireless networks in indoor environments. Our method allows defining the best location of network devices and sensor nodes indoors saving 15% of the sensors needed. Finally, we present a study on underwater freshwater communications based on electromagnetic waves, where we analyze the dependency of underwater communications as a function of working frequency, temperature, data transfer rates and modulation. Related to underwater environment, we present two proposals. First one refers to the implementation of a sensor network for marine farms which allows us to reduce the amount of waste deposited on the seabed and reduce the percentage of wasted food. The second proposal is the development of two oceanographic sensors which allow us to control the amount of food and feces deposited in seabed and the water turbidity control in a very simple and inexpensive way. All these developments and proposals have been preceded by a comprehensive study on the energy problems in wireless sensor networks. We have also presented several techniques which can be used to prolong the network lifetime and improve its stability. / Sendra Compte, S. (2013). Deployment of Efficient Wireless Sensor Nodes for Monitoring in Rural, Indoor and Underwater Environments [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/32279