The Internet of Things (IoT) is an umbrella term for smart things connected to the Internet. Connected sensors may be used to the benefit of smart building management systems. This thesis describes the development of a sensor based building management system prototype, lightweight enough to run on a single network camera. The focus of the research was investigating if the system prototype was scalable, and capable of storing and analyzing data gathered from a large amount of sensors relevant to the field of building management. The prototype was developed through a five-stage systems development process, and evaluated using simulations and case studies. The finished prototype was able to gather and store data from a few hundred real-time sensors using limited hardware. Tests showed that the network camera should be capable of managing at least 100 sensors. The system itself is scalable with the use of more powerful hardware. However, using a distributed architecture would be preferable if more sensors are required. This could be achieved by creating a distributed network of cameras, where each camera manages its own set of sensors. This could both increase scalability and make the system more robust and reliable.

A Wireless Sensor Network (WSN) consists of a number of nodes, each typically having a small amount of non-replenishable energy. Some of the nodes have sensors, which may be used to gather environmental data. A common network abstraction used in WSNs is the (source, sink) architecture in which data is generated at one or more sources and sent to one or more sinks using wireless communication, possibly via intermediate nodes. In such systems, wireless communication is usually implemented using radio. Transmitting or receiving, even on a low power radio, is much more energy-expensive than other activities such as computation and consequently, the radio must be used judiciously to avoid unnecessary depletion of energy. Eventually, the loss of energy at each node will cause it to stop operating, resulting in the loss of data acquisition and data delivery. Whilst the loss of some nodes may be tolerable, albeit undesirable, the loss of certain critical nodes in a multi-hop routing environment may cause network partitions such that data may no longer be deliverable to sinks, reducing the usefulness of the network. This thesis presents a new heuristic known as node reliance and demonstrates its efficacy in prolonging the useful lifetime of WSNs. The node reliance heuristic attempts to keep as many sources and sinks connected for as long as possible. It achieves this using a reliance value that measures the degree to which a node is relied upon in routing data from sources to sinks. By forming routes that avoid high reliance nodes, the usefulness of the network may be extended. The hypothesis of this thesis is that the useful lifetime of a WSN may be improved by node reliance routing in which paths from sources to sinks avoid critical nodes where possible.

Energy harvesting is becoming increasingly important in low-power applications where energy from the environment is used to power the system alone, or to supplement a battery. For example, pulse oximeter sensors inside helmets of road racing cyclists are powered by the sun. These sensors have become smaller and more practical without the limitation of a finite energy supply. Harvested energy from an energy transducer (solar, piezoelectric, etc.) must be maximized to ensure these devices can survive periods where environmental energy is scarce. The conversion process from the transducer to usable power for the device is not perfectly efficient. Specifically, the output voltage of a solar cell is a function of the light intensity, and by extension the load it powers. A small perturbation of the light source quickly diminishes the available power. The wasted power reduces the energy available for the application, and can be improved using an approach called maximum power point tracking (MPPT). This technique maximizes harvesting efficiency by dynamically impedance matching the transducer to its load. This report introduces the Maximum Efficient Solar Harvester (MESH), an MPPT algorithm tuned for a specific Wireless Sensor Network (WSN) application. MESH specifically controls the operation of the DC-DC converter in a solar power management unit (PMU). The control is done by monitoring the available light and feeding that information to choose the optimal operating point DC-DC converter. This operating point has a direct dependency on the overall efficiency of the system. For MESH to be practical, the cost and power overhead of adding this functionality must be assessed. Empirical results indicate that MESH improves the maximum efficiency of the popular Texas Instruments (TI) RF2500-SEH WSN platform by an average of 20%, which far exceeds the power overhead it incurs. The cost is also found to be minimal, as WSN platforms already include a large portion of the hardware required to implement MESH. The report was done in collaboration with Stephen Kobdish. It covers the software implementation and MESH architecture definition; Kobdish's companion report focuses on hardware components and the bench automation environment. / text

Network growing mechanisms are used to construct random networks that have structural behaviors similar to existing networks such as genetic networks, in efforts of understanding the evolution of complex topologies. Popular mechanisms, such as preferential attachment, are capable of preserving network features such as the degree distribution. However, little is known about such randomly grown structures regarding robustness to disturbances (e.g., edge deletions). Moreover, preferential attachment does not target optimizing the network's functionality, such as information flow. Here, we consider a network to be optimal if it's natural functionality is relatively high in addition to possessing some degree of robustness to disturbances. Specifically, a robust network would continue to (1) transmit information, (2) preserve it's connectivity and (3) preserve internal clusters post failures. In efforts to pinpoint features that would possibly replace or collaborate with the degree of a node as criteria for preferential attachment, we present a case study on both; undirected and directed networks. For undirected networks, we make a case study on wireless sensor networks in which we outline a strategy using Support Vector Regression. For Directed networks, we formulate an Integer Linear Program to gauge the exact transcriptional regulatory network optimal structures, from there on we can identify variations in structural features post optimization.

In many practical problems, both decision and estimation are involved. This dissertation intends to study the relationship between decision and estimation in these problems, so that more accurate inference methods can be developed. Hybrid estimation is an important formulation that deals with state estimation and model structure identification simultaneously. Multiple-model (MM) methods are the most widelyused tool for hybrid estimation. A novel approach to predict the Internet end-to-end delay using MM methods is proposed. Based on preliminary analysis of the collected end-to-end delay data, we propose an off-line model set design procedure using vector quantization (VQ) and short-term time series analysis so that MM methods can be applied to predict on-line measurement data. Experimental results show that the proposed MM predictor outperforms two widely used adaptive filters in terms of prediction accuracy and robustness. Although hybrid estimation can identify model structure, it mainly focuses on the estimation part. When decision and estimation are of (nearly) equal importance, a joint solution is preferred. By noticing the resemblance, a new Bayes risk is generalized from those of decision and estimation, respectively. Based on this generalized Bayes risk, a novel, integrated solution to decision and estimation is introduced. Our study tries to give a more systematic view on the joint decision and estimation (JDE) problem, which we believe the work in various fields, such as target tracking, communications, time series modeling, will benefit greatly from. We apply this integrated Bayes solution to joint target tracking and classification, a very important topic in target inference, with simplified measurement models. The results of this new approach are compared with two conventional strategies. At last, a surveillance testbed is being built for such purposes as algorithm development and performance evaluation. We try to use the testbed to bridge the gap between theory and practice. In the dissertation, an overview as well as the architecture of the testbed is given and one case study is presented. The testbed is capable to serve the tasks with decision and/or estimation aspects, and is helpful for the development of the JDE algorithms.

Un réseau de capteurs sans fil (RCSF) est constitué d’un grand nombre de nœuds capteurs autonomes qui collaborent ensemble pour la surveillance d’une zone, d’une machine, d’une personne etc.. Dans certaines applications,les données critiques doivent être protégées contre toute utilisation frauduleuse et être accessibles en temps réel. Le besoin d’apporter une solution de sécurité fiable et adaptée paraît donc essentiel. Les solutions de sécurité utilisées dans les réseaux traditionnels ne sont pas directement applicables dans les RCSFs, car développer des primitives de sécurité en utilisant de faibles ressources devient un véritable défi. Dans cette thèse, nous proposons des solutions nouvelles peu gourmandes en ressources qui tiennent compte des faibles capacités de défense d’un réseau autonome. Dans cette optique nous appliquons des mécanismes cryptographiques bas´es sur les fonctions de hachage et les courbes elliptiques. Un focus sur différents mécanismes de sécurité peu gourmands en ressources nous permet la mise en évidence des rapports de forces entre les RCSFs et leurs vulnérabilités. Notre première contribution vise `a améliorer la sécurité et les performances en termes d’´énergie sur des protocoles d’authentification existants tout en utilisant les mêmes mécanismes. Dans la deuxième contribution, on utilise le concept de probabilité de risque afin de déterminer la consommation énergétique dans différentes architectures de déploiement. Dans la troisième contribution nous présentons un nouveau mécanisme d’accélération de la multiplication scalaire sur les courbes elliptiques définies dans des corps finis premiers. Ce mécanisme bas´e sur l’opposé et l’ordre d’un point, réduit le nombre d’opérations de points dans un intervalle donné, et présente en plus l’avantage de pouvoir être combiné avec les techniques existantes. Enfin dans notre dernière contribution, nous nous sommes intéressés à l’accélération du calcul des points résultants du partitionnement du scalaire qui introduisent des coûts additionnels de calcul et de stockage mémoire. Nous comparons différentes formules de points existantes en mettant en évidence leur efficacité. / A Wireless Sensor Network (WSN) consists of a large number of sensor nodes which collaborate so as tomonitor environnement. For various WSNs’ applications, the collected data should be protected by preventingunauthorized users from gaining the information. The need to find a reliable and adaptive security solution isvery important. Most current standard security protocols designed for traditional networks cannot be applieddirectly in WSN. For this reason, providing a variety of security functions with limited resources is a realchallenge. Our research work seeks to find secure efficient solutions that take into account the rather weakdefense of an autonomous network. In this way, we apply lightweight cryptography mechanisms based on hashfunction and elliptic curves. A focus on different security mechanisms and lightweight security algorithms canhighlight the strength ratio between WSNs and their vulnerabilities. Our first contribution is on a secure energyefficient solution, it uses the same mechanism and aims to enhance the security weaknesses of existing solutions.The second contribution uses the concept of probability risk analysis to show to which level the proposedsolution justifies the better energy consumption for a given network architecture. In the third contribution, wepresent a new technique to accelerate scalar multiplication on elliptic curves cryptography over prime field forlight-weight embedded devices like sensor nodes. Our method reduces the computation of scalar multiplicationby an equivalent representation of points based on point order in a given interval and can also act as a supportfor most existing methods. Finally our last contribution presents a fast pre-computation algorithm in a parallelscalar multiplication to avoid the storage of pre-computation points which requires extra memory. We alsoprovide a comparison of different formulas so as to find out their efficiency.

Os Wireless sensor networks (WSNs) evoluíram a partir da idéia de que sensores sem fio podem ser utilizados para coletar informações de ambientes nas mais diversas situações. Os primeiros trabalhos sobre WSNs foram desenvolvidos pelo Defense Advanced Research Projects Agency (DARPA)1, com o conceito de Smart Dust baseados em microelectromechanical systems (MEMS), dispositivos com capacidades de detectar luminosidade, temperatura, vibração, magnetismo ou elementos químicos, com processamento embarcado e capaz de transmitir dados via wireless. Atualmente tecnologias emergentes têm aproveitado a possibilidade de comunicação com a World Wide Web para ampliar o rol de aplicações desta tecnologia, dentre elas a Internet das Coisas (Internet of Things) IoT. Esta pesquisa estuda a implementação de um novo algoritmo e protocolo que possibilita o encaminhamento dos dados coletados nos microsensores em cenários de redes ad hoc com os sensores distribuídos aleatoriamente, em uma área adversa. Apesar de terem sido desenvolvidos vários dispositivos de hardware pela comunidade de pesquisa sobre WSN, existe um esforço liderado pela Internet Engineering Task Force (IETF)2, na implementação e padronização de protocolos que atendam a estes mecanismos, com limitações de recursos em energia e processamento. Este trabalho propõe a implementação de novos algoritmos de encaminhamento de pacotes utilizando o conceito de códigos convolucionais. Os resultados obtidos por meio de extensivas simulações mostram ganhos em termos da redução de latência e do consumo de energia em relação ao protocolo AODV. A complexidade de implementação é extremamente baixa e compatível com os poucos recursos de hardware dos elementos que usualmente compõem uma rede de sensores sem fio (WSN). Na seção de trabalhos futuros é indicado um extenso conjunto de aplicações em que os conceitos desenvolvidos podem ser aplicados. / Wireless sensor networks (WSNs) have evolved from the idea that small wireless sensors can be used to collect information from the physical environment in a large number of situations. Early work in WSNs were developed by Defense Advanced Research Projects Agency (DARPA)1, so called Smart Dust, based on microelectromechanical systems (MEMS), devices able to detect light, temperature, vibration, magnetism or chemicals, with embedded processing and capable of transmitting wireless data. Currently emerging technologies have taken advantage of the possibility of communication with the World Wide Web to expand to all applications of this technology, among them the Internet of Things IoT. This research, studies to implement a new algorithm and protocol that allows routing of data collected in micro sensors in ad hoc networks scenarios with randomly distributed sensors in adverse areas. Although they were developed several hardware devices by the research community on WSN, there is an effort led by Internet Engineering Task Force (IETF)2, in the implementation and standardization of protocols that meet these mechanisms, with limited energy and processing resources. This work proposes the implementation of new packets forwarding algorithms using the concept of convolutional codes. The results obtained by means of extensive simulations show gains in terms of latency and energy consumption reduction compared to the AODV protocol. The implementation complexity is extremely low and compatible with the few hardware resources usually available in the elements of a wireless sensor network (WSN). In the future works section a large set of applications for which the developed concepts can be applied is indicated.

A mitigação de desastres naturais exige respostas rápidas e confiáveis. No Brasil, a estação de chuvas provoca muitos alagamentos em regiões urbanas e, para monitorar esse fenômeno, foi instalada em São Carlos-SP uma rede de sensores sem fio para acompanhar o nível de água dos rios da cidade. Entretanto, essa rede de sensores está suscetível a falhas que podem comprometer o funcionamento do sistema, e a adoção de mecanismos redundantes e de redes móveis 3G podem acarretar em custos proibitivos à monitoração desses rios, além de não garantirem a operação normal desse monitoramento. Assim, este trabalho apresenta uma solução baseada em veículo aéreo não tripulado (VANT) para reduzir os problemas oriundos das falhas em uma rede de sensores para detectar desastres naturais como enchentes e deslizamentos. Na solução proposta, o VANT pode ser transportado para o sítio do desastre para minimizar os problemas provenientes das falhas (por exemplo, para servir como um roteador ou até mesmo para servir como uma mula de dados e transmitir imagens em tempo real para equipes de resgate). Estudos foram conduzidos em um protótipo real, equipado com o UAV Brain (módulo computacional desenvolvido especificamente para este projeto), para uma análise exploratória do consumo energético do VANT e do rádio transmissor que equipa o VANT. Os resultados mostram que a melhor situação para o rádio comunicador se dá quando o VANT está no ar e com uma antena de maior ganho, e os fatores que mais influenciam no consumo energético do rádio são a altura do VANT e o tipo de antena utilizado. Além disso, tais resultados mostram também a viabilidade desta proposta em redes de sensores sem fio linear e esparsa. / The mitigation of natural disasters requires quick and reliable answers. In Brazil, the rainy season causes many flooding in urban areas and, to monitor this phenomenon, a wireless sensor network to monitor the water level of the citys rivers was installed in São Carlos-SP. However, this sensor network is susceptible to failures that may jeopardize the operation of the system, and the adoption of redundant mechanisms and 3G mobile networks may result in prohibitive costs to the monitoring of these rivers, and does not guarantee the normal operation of monitoring. This work presents an aerial vehicle-based solution unmanned (UAV) to reduce the problems originated from failures in a network of sensors to detect natural disasters such as floods and landslides. In the proposed solution, the UAV can be transported to the disaster site to minimize problems arising from failures (eg, to serve as a router or even to serve as a data mule and transmit images in real time for rescue teams). Studies were conducted in a real prototype, equipped with UAV Brain (computational module developed specifically for this project), for an exploratory analysis of the energy consumption UAV and radio transmitter fitted to the UAV. The results show that the best situation for the radio communicator is when the UAV is in the air and with a higher gain antenna, and the factors that most influence on the radio energy consumption are the height of the UAV and the type of antenna used. Furthermore, these results also show the feasibility of this proposal in linear and sparse wireless sensor networks.

<div>Ensuring the robustness and resilience of safety-critical systems from civil aviation to military surveillance technologies requires improvements to target tracking capabilities. Implementing target tracking as a distributed function can improve the quality and availability of information for end users. Any errors in the model of a target's dynamics or a sensor network's measurement process will result in estimates with degraded accuracy or even filter divergence. This dissertation solves a distributed estimation problem for estimating the state of a dynamical system and the parameters defining a model of that system.</div><div>The novelty of this work lies in the ability of a sensor network to maintain consensus on state and parameter estimates through local communications between sensor platforms.</div>

Submitted by Jadson Francisco de Jesus SILVA (jadson@uefs.br) on 2018-08-01T22:49:01Z No. of bitstreams: 1 Disserta??o de Emerson Santos de Oliveira.pdf: 8680376 bytes, checksum: 50da6ed4976883dc246ce9d59cca44e6 (MD5) / Made available in DSpace on 2018-08-01T22:49:01Z (GMT). No. of bitstreams: 1 Disserta??o de Emerson Santos de Oliveira.pdf: 8680376 bytes, checksum: 50da6ed4976883dc246ce9d59cca44e6 (MD5) Previous issue date: 2018-05-04 / The development of new technologies in the last years in the areas of wireless commu- nications has brought many advantages to the development of many sectors of the city. Recent advances in sensor technology are providing an expansion of the possible appli- cations, creating an environment of increasingly efficient data communication. With this, we can see a great advance in the scientific researches related to the development of te- chniques and improvement of communication in Wireless Sensor Networks (WSN). In fact, this type of network has been applied in several areas, such as: smart cities, internet of things (IoT), environmental monitoring, Vehicle tracking, health applications, among others. In this context, this work proposes to develop an algorithm for positioning node sinks in urban areas for intelligent cities, in order to optimize the communication between mobile sink nodes and fixed sensors clustered in a WSN. This approach allows the opti- mization of WSN for the urban environment, providing an improvement in the rates of energy consumption, processing and transmission of data in the network. / O desenvolvimento de novas tecnologias ocorrido nos ?ltimos anos nas ?reas das comuni- ca??es sem fio tem trazido grandes benef?cios para o desenvolvimento de diversos setores da cidade. Avan?os recentes na tecnologia de sensores est?o proporcionando uma ex- pans?o das aplica??es poss?veis, criando um ambiente de comunica??o de dados cada vez mais eficiente. Com isso, nota-se um grande avan?o nas pesquisas cient?ficas relacionadas ao desenvolvimento de t?cnicas e aprimoramento da comunica??o em Redes de Sensores Sem Fio (RSSF). Com efeito, esse tipo de rede passou a ser aplicada em diversas ?reas, tais como: cidades inteligentes, internet das coisas (IoT), monitoramento ambiental, ras- treamento de ve?culos, aplica??es nas ?reas de sa?de, entre outros. Nesse contexto, este trabalho prop?e desenvolver um algoritmo de posicionamento de n?s sinks em zonas ur- banas para cidades inteligentes, com o prop?sito de otimizar a comunica??o entre os n?s sinks m?veis e sensores fixos agrupados em cluster em uma RSSF. Essa abordagem, per- mite a otimiza??o da RSSF para o ambiente urbano, proporcionando uma melhoria nas taxas de consumo de energia, processamento e transmiss?o de dados na rede.