A realtime wireless motion tracking system is developed. The system is capable of tracking the orientations of multiple wireless sensors, using a semi-distributed implementation to reduce network bandwidth and latency, to produce real-time animation of rigid body models, such as the human skeleton. The system has been demonstrated to be capable of full-body posture tracking of a human subject using fifteen devices communicating with a basestation over a single, low bandwidth, radio channel. The thesis covers the theory, design, and implementation of the tracking platform, the evaluation of the platform’s performance, and presents a summary of possible future applications.

This thesis is concerned with distributed estimation in a wireless sensor network (WSN) with analog transmission. For a scenario in which a large number of sensors are deployed under a limited bandwidth constraint, a semi-orthogonal multiple-access channelization (MAC) approach is proposed to provide transmission of observations from K sensors to a fusion center (FC) via N orthogonal channels, where K≥N. The proposed semi-orthogonal MAC can be implemented with either fixed sensor grouping or adaptive sensor grouping. The mean squared error (MSE) is adopted as the performance criterion and it is first studied under equal power allocation. The MSE can be expressed in terms of two indicators: the channel noise suppression capability and the observation noise suppression capability. The fixed version of the semi-orthogonal MAC is shown to have the same channel noise suppression capability and two times the observation noise suppression capability when compared to the orthogonal MAC under the same bandwidth resource. For the adaptive version, the performance improvement of the semi-orthogonal MAC over the orthogonal MAC is even more significant. In fact, the semi-orthogonal MAC with adaptive sensor grouping is shown to perform very close to that of the hybrid MAC, while requiring a much smaller amount of feedback. Another contribution of this thesis is an analysis of the behavior of the average MSE in terms of the number of sensors, namely the scaling law, under equal power allocation. It is shown that the proposed semi-orthogonal MAC with adaptive sensor grouping can achieve the optimal scaling law of the analog WSN studied in this thesis. Finally, improved power allocations for the proposed semi-orthogonal MAC are investigated. First, the improved power allocations in each sensor group for different scenarios are provided. Then an optimal solution of power allocation among sensor groups is obtained by the convex optimization theory, and shown to outperform equal power allocation. The issue of balancing between the performance improvement and extra feedback required by the improved power allocation is also thoroughly discussed.

Hop count, i.e., the number of wireless hops a packet has to go through to reach the destination, is a fundamental metric in multi-hop wireless ad-hoc networks. Network performance, such as throughput, end-to-end delay, energy consumption, and so on, depends critically on hop count. Previous work on modeling hop count is limited in making unrealistic simplifying assumptions either at the physical or network, or both layers of the communication protocol stack. A key contribution of this thesis is to present an analytical model to derive the probability distribution of hop count under realistic assumptions at both physical and network layers. Specifically, the model considers a log-normal shadowing radio propagation capable of accommodating the random signal fading observed in most wireless communication environments, and the widely used geographic routing at the network layer. Validation of the model is achieved by a comprehensive set of simulation experiments including a trace driven simulation of a real-word vehicular ad-hoc network. The model reveals that the presence of randomness in radio propagation reduces the required number of hops to reach a given destination significantly. To demonstrate the utility of the proposed hop count model, the thesis proposes three new applications which address some of the key challenges in multi-hop wireless networks. The first application derives the per-node packet forwarding load in multi-hop wireless sensor networks and reveals that the nodes in the vicinity of the base station has a significantly less forwarding load than previously thought under simplifying radio propagation and routing assumptions. The second application demonstrates that using hop count as a measure of distance traveled by a data packet, geocasting can be achieved in multi-hop wireless networks in situations when some of the network nodes do not have access to reliable location information. Finally, the proposed hop count model is used to evaluate the performance of the third application which demonstrates that the overhead of geographic routing can be reduced significantly by embracing a position update philosophy which adapts to the mobility and communication patterns of the underlying ad-hoc network.

Hop count, i.e., the number of wireless hops a packet has to go through to reach the destination, is a fundamental metric in multi-hop wireless ad-hoc networks. Network performance, such as throughput, end-to-end delay, energy consumption, and so on, depends critically on hop count. Previous work on modeling hop count is limited in making unrealistic simplifying assumptions either at the physical or network, or both layers of the communication protocol stack. A key contribution of this thesis is to present an analytical model to derive the probability distribution of hop count under realistic assumptions at both physical and network layers. Specifically, the model considers a log-normal shadowing radio propagation capable of accommodating the random signal fading observed in most wireless communication environments, and the widely used geographic routing at the network layer. Validation of the model is achieved by a comprehensive set of simulation experiments including a trace driven simulation of a real-word vehicular ad-hoc network. The model reveals that the presence of randomness in radio propagation reduces the required number of hops to reach a given destination significantly. To demonstrate the utility of the proposed hop count model, the thesis proposes three new applications which address some of the key challenges in multi-hop wireless networks. The first application derives the per-node packet forwarding load in multi-hop wireless sensor networks and reveals that the nodes in the vicinity of the base station has a significantly less forwarding load than previously thought under simplifying radio propagation and routing assumptions. The second application demonstrates that using hop count as a measure of distance traveled by a data packet, geocasting can be achieved in multi-hop wireless networks in situations when some of the network nodes do not have access to reliable location information. Finally, the proposed hop count model is used to evaluate the performance of the third application which demonstrates that the overhead of geographic routing can be reduced significantly by embracing a position update philosophy which adapts to the mobility and communication patterns of the underlying ad-hoc network.

This thesis proposes an implementation of battery-powered, time-synchronized wireless nodes that can be deployed in a wireless network topology. Wireless sensor networks are used in a wide variety of scenarios where emphasis is placed on the wireless nodes’ battery life. The main area of focus in this thesis is to examine how wireless nodes can save battery power by utilizing a deep sleep mode and wake up simultaneously using time synchronization to carry out their data communication. This was achieved by deploying five time-synchronized, battery-powered nodes in a wireless network topology. The difference in battery current draw between continuously running nodes and sleep-enabled nodes were measured, as well as the time duration needed by the nodes to successfully send their payloads and route other nodes’ data. The nodes needed between 1502 ms and 3273 ms on average to carry out their data communication, depending on where they were located in the network topology. Measurements show that sleep-enabled nodes on average draw substantially less current than continuously running nodes during a complete data communication cycle. When sleep-enabled nodes were powered by two AA batteries, an increase in battery life of up to 1800% was observed.

como cidades inteligentes e Internet das coisas demonstram que esta tecnologia está evoluindo em larga escala. Consequentemente, diversas aplicações desta tecnologia estão sendo desenvolvidas, muitas delas são altamente dependentes de redes de sensores sem fio, pois fazem a coleta de dados em ambientes inóspitos ou de difícil acesso. Para que estes dados coletados de diversos dispositivos possam ser analisados em conjunto é preciso que as coletas sejam simultâneas ou em intervalos próximos de tempo, o que implica que toda a rede de sensores tenha uma elevada precisão no sincronismo. Ademais, diversos protocolos de comunicação sem fio utilizam o sincronismo para estabelecer o compartilhamento do meio de propagação, tendo assim uma maior eficiência na troca de dados. Ao observar a importância de atender a essa necessidade de sincronização de tempo entre dispositivos usados em redes de sensores sem fio, este trabalho se concentra na proposta, implementação e teste de um serviço de sincronização de tempo para redes de sensores sem fio de baixa potência usando relógios de baixa frequência em tempo real em cada nó. Para implementar este serviço, são propostos três algoritmos baseados em estratégias diferentes para alcançar a sincronização desejada. O primeiro baseia-se em uma métrica simples de correção adaptativa; o segundo baseia-se em um mecanismo de predição; já o terceiro utiliza um mecanismo mais complexo, a correção analítica. Todos os algoritmos tem o mesmo objetivo: fazer com que os relógios dos nós sensores convirjam de forma ágil, em seguida, mantê-los com a maior similaridade possível. O objetivo deste trabalho é apresentar o melhor método que garanta a sincronização, mantendo o baixo consumo de energia em uma rede de sensores. Os resultados experimentais fornecem evidências do sucesso no cumprimento deste objetivo, bem como fornece meios para comparar estas três abordagens considerando os melhores resultados de sincronização e os seus custos em termos de consumo de energia. / Environmental monitoring systems are gaining more and more space, concepts such as smart cities and the Internet of things demonstrate that this technology has been developing a lot. Consequently, many applications of this technology are being developed, many of them are dependent on wireless sensor networks, which collect data in inhospitable or difficult-to-access environments. In order to these collected data from several devices to be analyzed together it is necessary that the data collection be simultaneous or at close intervals, which implies that the entire network of sensors has a high precision in the synchronism. In addition, several wireless communication protocols use the synchronism to establish sharing of medium networks, thus having a greater efficiency in the exchange of data. Observing the importance of time synchronization, this work focuses in proposing, implementing and testing time synchronization protocols for low power wireless sensor networks using real time low frequency clocks. To implement this service, three algorithms based on different strategies are proposed to achieve the desired synchronization. The first is based on the simple metric for self-correction; the second is based on a prediction mechanism; while the third uses a more complex mechanism for analytical correction. All the algorithms have the same goal: to make the clock of the sensor nodes converge in an agile way, then to keep them with the greatest possible similarity. The objective of this work is to present the best method to guarantee the synchronization, keeping the low power consumption in a network, sporadically, transmissions. The experimental results provide evidence of success in achieving this goal, as well as providing means to compare these three approaches considering the best synchronization results and their costs in terms of energy consumption. Keywords: Internet of things.

Submitted by ROGÉRIO ZANARDE BARBOSA null (rogerio.zanarde@hotmail.com) on 2016-02-15T16:09:03Z No. of bitstreams: 1 TESE_ROGERIO_FINAL (pdf).pdf: 3648253 bytes, checksum: 709d16b4ff9a0a30de2b8ad951471639 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-02-16T17:03:04Z (GMT) No. of bitstreams: 1 barbosa_rz_dr_bot.pdf: 3648253 bytes, checksum: 709d16b4ff9a0a30de2b8ad951471639 (MD5) / Made available in DSpace on 2016-02-16T17:03:04Z (GMT). No. of bitstreams: 1 barbosa_rz_dr_bot.pdf: 3648253 bytes, checksum: 709d16b4ff9a0a30de2b8ad951471639 (MD5) Previous issue date: 2015-12-16 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Este é um trabalho de tecnologia computacional aplicada na área agrícola, cujo objetivo principal do trabalho é desenvolver uma rede de sensores sem fio, que envolve aspectos de software e hardware, para o monitoramento térmico no interior de uma casa de vegetação. Além da rede propriamente dita, o trabalho também inclui a sua aplicação no levantamento quantitativo da variabilidade térmica na casa de vegetação o que pode ser aplicado em diversas atividades agrícolas a serem desenvolvidas no interior da estrutura. A proposta é que a rede desenvolvida seja de fácil implementação e manuseio, com baixo custo, e que use técnicas computacionais eficientes a fim de permitir a sua fácil adaptação a diferentes necessidades das pesquisas. As redes de sensores sem fios dependem fundamentalmente de estruturas chamadas de nós de sensoriamento, que são responsáveis pelas medições de um parâmetro físico e também pela troca de informações via rádio. No presente e trabalho, o nó de sensoriamento desenvolvido é constituído pelo módulo de rádio XBee Pro S2B; por um módulo de processamento Arduino Nano e por sensores de temperatura modelo LM35. O processador de cada nó de sensoriamento da rede desenvolvida executa um programa que faz a captura dos dados dos sensores de temperatura e os enviam por rádio à um computador onde existe um software que também foi desenvolvido no presente trabalho com o objetivo de receber, separar e gravar os dados de uma rede de sensores sem fio para o monitoramento térmico em casas de vegetação. Cada nó de sensoriamento possui capacidade de ser conectado a até 8 sensores LM35. Na análise térmica, foram distribuídos dois nós de sensoriamento e um total de 15 sensores distribuídos sistematicamente no interior de uma casa de vegetação do tipo teto em arco com dimensões de 8 X 16 metros localizada em Garça – SP. Os sensores foram corrigidos e instalados numa altura de 1,70 metros avaliando o comportamento, variação, e a variabilidade espacial da temperatura do ar no interior da estrutura. Foi avaliado também a distribuição espacial da evapotranspiração de referência utilizando a metodologia proposta por Hargreaves-Samani, que leva em consideração os valores de temperatura diária e radiação solar no topo da atmosfera. A avaliação dos dados mostra que o comportamento da temperatura do ar no interior da casa de vegetação sofreu variações significativas tanto em termos espaciais quanto temporais, evidenciando que o microclima neste ambiente é dinâmico, podendo modificar conforme a localização do sensor e hora do dia, sendo que as maiores variações térmicas ocorreram no período que varia das 8:00 às 14:00 horas. Com esta análise também é possível fazer um cálculo da evapotranspiração no interior da casa de vegetação, o que compõe no sistema desenvolvido uma ferramenta eficaz para a irrigação de precisão. A análise dos dados permite concluir que o sistema desenvolvido atendeu de maneira satisfatória o objetivo proposto, sendo uma importante ferramenta no monitoramento de parâmetros físicos à distância e em tempo real. O emprego desta tecnologia facilita a aquisição de dados e a tomada de decisão em cultivos agrícolas. / This work presents the use of computer technology applied in agricultural systems, which involves aspects of software and hardware for thermal monitoring inside a greenhouse. It includes detailed analyses of the thermal variability in the greenhouse, which can be used in various agricultural activities implemented within the structure. The work also includes de design of a wireless sensor network with main features are easy implementation, low cost, and efficient use of computational techniques to allow easy adaptation to new different needs of research. Wireless sensor networks depend of a structure called sensor node, which are responsible for measuring a physical parameter and by wireless information exchange. In this work, the sensing node was designed with a radio module XBee Pro S2B; an Arduino Nano by a processing module; and the LM35 temperature sensor. The sensor nodes processor runs a program that makes the capture of data from temperature sensors and sends them by radio to a computer where a software which was also developed in this work and aim to receive, separate and record data from a wireless sensor network for monitoring the air temperature inside greenhouses. Each sensor node has the ability to be connected to up to eight LM35 sensors. In greenhouse thermal analysis, they were distributed in two sensing nodes connected to 15 sensors systematically distributed into the greenhouse with dimensions of 8 x 16 meters located in Garça – SP, Brazil. The sensors were fixed and installed at a height of 1.70 meters evaluating the behavior variation and spatial variation of the air temperature inside the structure. It was also evaluated the spatial distribution of reference evapotranspiration using the methodology proposed by Hargreaves-Samani, which takes into account the daily temperatures and solar radiation in the top of the atmosphere. The temperature data analyses shows that the air temperature presents significant variations in spatial and temporal terms, showing that the microclimate in this environment is dynamic and can change as the sensor location and time of day with the greatest temperature changes occurred in the period ranging from 8:00AM to 2:00PM. This analysis is also possible to make a calculation of evapotranspiration inside the greenhouse, which makes up the system developed an effective tool for precision irrigation. The data analysis shows that the system developed satisfactorily met the proposed objective, being an important tool in monitoring physical parameters remotely and in real time. The use of this technology facilitates data acquisition and decision making in agricultural crops.

abstract: Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by having computer controlled air-conditioning systems. However, programming actuators in a large-scale environment for buildings and homes can be time consuming and expensive. This dissertation presents an approach that algorithmically sets up the control system that can automate any building without requiring custom programming. This is achieved by imbibing the system self calibrating and self learning abilities. For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting. For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control. The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

Time Difference Of Arrival (TDOA) based position tracking technique is one of the pinnacles of sports tracking technology. Using radio frequency com-munication, advanced filtering techniques and various computation methods, the position of a moving player in a virtually created sports arena can be iden-tified using MATLAB. It can also be related to player’s movement in real-time. For football in particular, this acts as a powerful tool for coaches to enhanceteam performance. Football clubs can use the player tracking data to boosttheir own team strengths and gain insight into their competing teams as well. This method helps to improve the success rate of Athletes and clubs by analyz-ing the results, which helps in crafting their tactical and strategic approach to game play. The algorithm can also be used to enhance the viewing experienceof audience in the stadium, as well as broadcast.In this thesis work, a typical football field scenario is assumed and an arrayof base stations (BS) are installed along perimeter of the field equidistantly.The player is attached with a radio transmitter which emits radio frequencythroughout the assigned game time. Using the concept of TDOA, the position estimates of the player are generated and the transmitter is tracked contin-uously by the BS. The position estimates are then fed to the Kalman filter, which filters and smoothens the position estimates of the player between the sample points considered. Different paths of the player as straight line, circu-lar, zig-zag paths in the field are animated and the positions of the player are tracked. Based on the error rate of the player’s estimated position, the perfor-mance of the Kalman filter is evaluated. The Kalman filter’s performance is analyzed by varying the number of sample points.

como cidades inteligentes e Internet das coisas demonstram que esta tecnologia está evoluindo em larga escala. Consequentemente, diversas aplicações desta tecnologia estão sendo desenvolvidas, muitas delas são altamente dependentes de redes de sensores sem fio, pois fazem a coleta de dados em ambientes inóspitos ou de difícil acesso. Para que estes dados coletados de diversos dispositivos possam ser analisados em conjunto é preciso que as coletas sejam simultâneas ou em intervalos próximos de tempo, o que implica que toda a rede de sensores tenha uma elevada precisão no sincronismo. Ademais, diversos protocolos de comunicação sem fio utilizam o sincronismo para estabelecer o compartilhamento do meio de propagação, tendo assim uma maior eficiência na troca de dados. Ao observar a importância de atender a essa necessidade de sincronização de tempo entre dispositivos usados em redes de sensores sem fio, este trabalho se concentra na proposta, implementação e teste de um serviço de sincronização de tempo para redes de sensores sem fio de baixa potência usando relógios de baixa frequência em tempo real em cada nó. Para implementar este serviço, são propostos três algoritmos baseados em estratégias diferentes para alcançar a sincronização desejada. O primeiro baseia-se em uma métrica simples de correção adaptativa; o segundo baseia-se em um mecanismo de predição; já o terceiro utiliza um mecanismo mais complexo, a correção analítica. Todos os algoritmos tem o mesmo objetivo: fazer com que os relógios dos nós sensores convirjam de forma ágil, em seguida, mantê-los com a maior similaridade possível. O objetivo deste trabalho é apresentar o melhor método que garanta a sincronização, mantendo o baixo consumo de energia em uma rede de sensores. Os resultados experimentais fornecem evidências do sucesso no cumprimento deste objetivo, bem como fornece meios para comparar estas três abordagens considerando os melhores resultados de sincronização e os seus custos em termos de consumo de energia. / Environmental monitoring systems are gaining more and more space, concepts such as smart cities and the Internet of things demonstrate that this technology has been developing a lot. Consequently, many applications of this technology are being developed, many of them are dependent on wireless sensor networks, which collect data in inhospitable or difficult-to-access environments. In order to these collected data from several devices to be analyzed together it is necessary that the data collection be simultaneous or at close intervals, which implies that the entire network of sensors has a high precision in the synchronism. In addition, several wireless communication protocols use the synchronism to establish sharing of medium networks, thus having a greater efficiency in the exchange of data. Observing the importance of time synchronization, this work focuses in proposing, implementing and testing time synchronization protocols for low power wireless sensor networks using real time low frequency clocks. To implement this service, three algorithms based on different strategies are proposed to achieve the desired synchronization. The first is based on the simple metric for self-correction; the second is based on a prediction mechanism; while the third uses a more complex mechanism for analytical correction. All the algorithms have the same goal: to make the clock of the sensor nodes converge in an agile way, then to keep them with the greatest possible similarity. The objective of this work is to present the best method to guarantee the synchronization, keeping the low power consumption in a network, sporadically, transmissions. The experimental results provide evidence of success in achieving this goal, as well as providing means to compare these three approaches considering the best synchronization results and their costs in terms of energy consumption. Keywords: Internet of things.