Com o aumento das aplicações e dispositivos para Internet das Coisas, muitos esforços para reduzir potência dissipada nos transceptores foram investidos. A maioria deles, entretanto, focam individualmente no rádio, nos conversores analógicos para digital e viceversa, e na arquitetura de banda base digital. Como consequência, há pouca margem para melhorias na potência dissipada nestes blocos isolados que compense o enorme esforço. Portanto, este trabalho propõe uma arquitetura adaptativa a nível de sistema focando em reduzir o consumo no conversor analógico para digital e no receptor digital. Ele utiliza um algoritmo robusto para o receptor banda base digital, um conversor analógico para digital topologia Sigma-Delta e um bloco de controle realimentado conforme a relação sinal ruído medida do pacote recebido. O sistema foi projetado para o protocolo IEEE 802.15.4. Para validação do sistema e estimar a potência consumida foi feito um modelo de sistema utilizando a ferramenta Matlab, uma descrição do hardware em linguagem Verilog e uma síntese lógica utilizando o processo da X-FAB XC018. As simulações mostram uma redução na potência consumida pelo sistema de até 13% e ainda atingindo os requisitos do protocolo. Os resultados deste trabalho foram publicados na conferência internacional em tecnologia de instrumentação e medidas de 2014 realizada na cidade de Montevidéu no Uruguai. / With the increase of Internet of Things applications and devices, many efforts to reduce power consumption in transceiver has been invested. Most of them targeted in RF frontend, converters, or in the digital baseband architecture individually. As result, there are few margins nowadays for power improvement in these blocks singly that compensates the huge hard work required. The next optimization step leads to a system level analysis seeking design space and new possibilities expansion. It is in this field that adaptive systems approaches are conquering ground recently. The solutions combines Radio Frequency (RF) and process variation techniques, Low Pass Filters (LPF) and Analog to Digital Converters (ADCs) adjustment for better performance, digital baseband bit width adaptive according to income packet SNR, configurable ADC resolution and topology, and others. In this scenario the current work proposes an adaptive system level architecture targeting ADC and digital receiver power reduction. It uses a robust algorithm for digital baseband receiver, a Sigma-Delta ADC, and suggests a feedback control block based on packet SNR measure. The system was designed for the IEEE 802.15.4 standard and required system modeling using Matlab tool, hardware description in Verilog language, and logic synthesis using X-FAB XC018 process for validation and power consumption estimation. Simulations show up to 15% of system power reduction and still meeting the standard requirements. The work results were published in the International Instrumentation and Measurement Technology Conference of 2014 occurred in Montevideo - Uruguay.

Wireless Sensor Network (WSN) technology has been one of the major avenues of Internet of Things (IoT) due to their potential role in digitising smart physical environments. WSNs are typically composed of a vast number of low-power, low–cost and multifunctional sensor nodes within an area that automatically cooperate to complete the application task. This emerging technology has already contributed to the advancement of a broad range of applications. Nevertheless, the development of WSNs is a challenging issue due to significant concerns, which need to be resolved to take full benefit of this remarkable technology. One of the main challenges of WSNs is how to reduce the energy consumption of a single node, in order to extend the network lifetime and improves the quality of service. For that reason, a newly design energy efficient communication protocol is required to tackle the issue. The clustering protocols designed for communication are alleged to be one of the most efficient solutions that can contribute to network scalability and energy consumption in WSNs. While different clustering protocols have been proposed to tackle the aforementioned issue, those solutions are either not scalable or do not provide the mechanisms to avoid a heavy loaded area. This thesis presents new adaptive energy management mechanisms, through which the limited critical energy source can be wisely managed so that the WSN application can achieve its intended design goals. Three protocols are introduced to manage the energy use. The first protocol presents an intra-cluster CH rotation approach that reduces the need for the execution of a periodical clustering process. The second protocol relates to load balancing in terms of the intra and inter-cluster communication patterns of clusters of unequal sizes. This proposed approach involves computing a threshold value that, when reached, triggers overall network re-clustering, with the condition that the network will be reconfigured into unequal cluster size. The third protocol proposes new performance factors in relation to CH selection. Based on these factors, the aggregated weight of each node is calculated, and the most suitable CH is selected. A comparison with existing communication protocols reveals that the proposed approaches balance effectively the energy consumption among all sensor nodes and significantly increase the network lifetime.

Operational time is becoming an increasingly important aspect in electronic devices and is also highly relevant in Underwater Acoustic Sensor Networks (UWSN). This thesis contains a study which explores what can be done to de-crease power consumption while maintaining the same functionality of an FPGA inside an underwater sensor-node network. A longer operational time means a more effective system since reconnaissance is one of UWSN’s area of application. The thesis will also cover the implementation of a new sensor-node ‘mode’ which will add new features and increase operational time.

FundaÃÃo de Amparo a Pesquisa do Estado do Piauà / A prediÃÃo de dados nÃo enviados ao sorvedouro à uma tÃcnica usada para economizar energia em RSSF atravÃs da reduÃÃo da quantidade de dados trafegados. PorÃm, os dispositivos devem rodar mecanismos simples devido as suas limitaÃÃes de recursos, os quais podem gerar erros indesejÃveis e isto pode nÃo ser muito preciso. Este trabalho propÃe um mÃtodo baseado na correlaÃÃo espacial e temporal multivariada para melhorar a precisÃo da prediÃÃo na reduÃÃo de dados de Redes de Sensores Sem Fio (RSSF). SimulaÃÃes foram feitas envolvendo funÃÃes de regressÃo linear simples e regressÃo linear mÃltipla para verificar o desempenho do mÃtodo proposto. Os resultados mostram um maior grau de correlaÃÃo entre as variÃveis coletadas em campo, quando comparadas com a variÃvel tempo, a qual à uma variÃvel independente usada para prediÃÃo. A precisÃo da prediÃÃo à menor quando a regressÃo linear simples à usada, enquanto a regressÃo linear mÃltipla à mais precisa. AlÃm disto, a soluÃÃo proposta supera algumas soluÃÃes atuais em cerca de 50% na prediÃÃo da variÃvel umidade e em cerca de 21% na prediÃÃo da variÃvel luminosidade. / Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, sensor devices must run simple mechanisms due to its constrained resources, which may cause unwanted errors and this may not be very accurate. This work proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to variable time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, the proposed solution outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction.

Este trabalho tem como objetivo a aplicação do conceito de data warehouse para a agregação, gerenciamento e apresentação de dados coletados por meio de Redes de Sensores Sem Fio que monitoram polinizadores. Os experimentos científicos que utilizam tais redes para monitorar habitat geram um volume de dados que precisa ser tratado e analisado, para que possa auxiliar os pesquisadores e demais interessados nas informações. Tais dados, gerenciados e correlacionados com informações de outras fontes, podem contribuir para a tomada de decisões e ainda realimentar outros experimentos. Para a avaliação da proposta, desenvolveu-se um modelo para extração, transformação e normalização dos dados coletados por redes de sensores sem fio, contemplando ainda a carga em data warehouse. Considerou- se no modelo, dados tabulados das redes de sensores sem fio, utilizados em experimentos com abelhas e ainda dados de outras fontes sobre o cultivo de abelhas, importantes para obtenção de visões do data warehouse mais apuradas. O uso de data warehouse aplicado a esse contexto mostrou-se um alternativa viável e útil, pois facilitou a obtenção de dados consolidados sobre o experimento, importante para a tomada de decisão pelos pesquisadores e ainda, diminui o tempo gasto pelos interessados em extrair essas informações, em comparação à tradicional análise em planilhas eletrônicas. / This work aims at applying the concept of data warehouse for data aggregation, management and presentation of data collected by Wireless Sensor Networks that monitor pollinators. Scientific experiments using such networks to monitor habitat generate a volume of data that must be addressed and analyzed, so that they can help researchers and others interested in the information. This data, managed and correlated with information from other sources may contribute to the making and still replenish other experiments. For the evaluation of the proposal, it was developed a model for the extraction, processing and standardization of data collected by wireless sensor networks, covering also the load on the data warehouse. It was considered in the model tabulated data networks of wireless sensors, used in experiments with bees and even data from other sources on the cultivation of bees, important to obtain views of the data warehouse more accurate. The use of data warehouse implemented in this context proved to be a viable and useful, as it facilitated the obtaining of information for decision making by researches and stakeholders and reduces time consumed by stakeholders to extract such information.

O crescente interesse pela caracterização de parâmetros acústicos marinhos esbarra nos poucos dispositivos eletrônicos que permitem capturar, armazenar, processar e difundir dados. Os equipamentos atuais que possibilitam obter dados referentes à vida marinha e permitem estudar as influências humanas sobre ela possuem alto custo e funcionam de forma isolada, ou seja, normalmente não há comunicação com outros dispositivos, o que dificulta a monitorização de eventos em tempo real. Sendo assim, neste trabalho são revisadas as características necessárias para estabelecer uma rede de sensores sem fio (RSSF) de alta confiabilidade, utilizando-se o conceito de Internet das Coisas (IoT). São comparados os protocolos MQTT-SN e CoAP com ferramentas de simulação e implementada uma rede de sensoriamento acústico aquático constituída de três nós sensores autônomos e um gateway usando o protocolo 6LowPAN. Também é implementada a tradução para o protocolo IPV4 no gateway, de modo que o funcionamento da rede de sensores pode ser monitorada num servidor remoto na Internet em tempo real. O desempenho da rede é avaliado com relação à autonomia energética, capacidade de memória, alcance e confiabilidade na entrega dos dados. As unidades autônomas desenvolvidas podem operar ininterruptamente, com uso de baterias, por aproximadamente 125 horas com memória de gravação de 48GB e alcance de 100m aproximadamente. Por fim, é implementado o pré-processamento dos dados sonoros visando a detecção de eventos acústicos aquáticos. / The increasing interest in the characterization of marine acoustic parameters needs electronic devices that allow capture, store, process, and diffuse data. Current equipment that provides data about the marine life and allow the study of human influences on it have high cost and work isolated, that is, without communication with other devices, which makes it difficult to monitor events in real time. Therefore, this work revises the necessary features to establish a high reliability wireless sensor network (WSN) by applying the concept of Internet of Things (IoT). The protocols MQTT-SN and CoAP are compared with simulation tools and a network is implemented to sense acoustic signals, composed by three autonomous sensor nodes and a gateway using the protocol 6LowPAN. The translation for the IPV4 protocol in the gateway is also implemented, so the operation of the sensor network can be monitored by a remote server on the Internet in real time. The performance of the network is evaluated in relation to power autonomy, memory capacity, reach and reliability. The autonomous sensor nodes can operate uninterrupted, with use of batteries, for approximately 125 hours with 48GB storage for recording and approximately 100m range. Finally, data pre-processing is implemented in order to detect aquatic acoustic events.

A área automotiva cada vez mais incorpora dispositivos e sistemas eletromecânicos na comunicação. Estes dispositivos são baseados nas informações internas e externas coletadas através de sensores específicos. Esta estrutura permite, por exemplo, a automatização de sistemas de transporte em ambientes controlados, monitoramento de veículos, informações de condições de trânsito e outros. Os protocolos de comunicação são fundamentais na troca de dados entre os módulos eletrônicos e certamente, se não fosse pela aplicação desses protocolos, não teríamos a integração de boa parte dos sistemas eletrônicos atualmente disponíveis. A integração dos sistemas de comunicação automotivos através de uma rede de sensores sem fio (RSSF) baseada nas especificações do padrão IEEE 802.15.4 ZigBee, constitui uma alternativa de comunicação nos ambientes automotivos. Além disso, esta integração em ambientes automotivos diminui a quantidade de fiação nos veículos. Neste trabalho apresentamos uma rede de sensores tipo estrela para a aquisição dos dados em um ambiente automotivo, realizando medições de intensidade do sinal, qualidade do sinal, throughput, pacotes perdidos. / The automotive area is including more and more devices and electromechanical systems at communication. Those devices are based in internal and external information collected through specific sensors. This structure allows, for example, automation of transport systems at controlled environments, vehicles monitoring, information of transit conditions and other. The communication protocols are fundamentals in data exchange between electronic modules and without those protocols, couldnt be possible integrate a majority of available electronic systems. The integration of automotive communication systems through wireless sensor network (WSN) based in the specifications of the standard IEEE 802.15.4 ZigBee constitute an alternative of communication in automotive environments. Besides, this integration in automotive environments reduces the quantity of wires in the vehicles. In this work we present a WSN star topology for data acquisition in automotive environment performing measurements of signal intensity, quality of signal, throughput, and lost packages.

Une grande partie des nouvelles générations d'objets connectés ne pourra se développer que s'il est possible de les rendre entièrement autonomes sur le plan énergétique. Même si l'utilisation de batteries ou de piles résout une partie de ce problème en assurant une autonomie qui peut-être importante avec des coûts relativement faibles, elle introduit non seulement des contraintes de maintenance incompatibles avec certaines applications, mais aussi des problèmes de pollution. La récupération de l'énergie thermique, mécanique, électromagnétique, solaire ou éolienne est une solution très prometteuse. Dans ce cas, la vie de l'objet connecté peut-être prolongée. Cependant, l'énergie récupérée dépend fortement des conditions au voisinage du dispositif et peut donc varier de façon périodique ou aléatoire. Il parait alors important d'adapter le système (mesure et transmission de données) aux contraintes de la récupération d'énergie. L'objectif de la thèse est de proposer une solution de capteur autonome basée sur un système de récupération et de gestion multisources d'énergies (solaire et éolienne) et pouvant-être mis en oeuvre dans différentes classes d'applications IoT. On s'intéresse, dans un premier temps, à la modélisation de la consommation du noeud capteur. Ensuite, on modélise le système de récupération multisources. Puis, on se focalise sur le management de puissance du système autonome. Ce management est basé sur des prédictions de l'énergie disponible et de celle consommée. Enfin, le travail de modélisation et d'optimisation est validé par des expérimentations afin d’avoir un démonstrateur de Capteur Communicant Autonome en Énergie pour les applications IoT. / Researchers aim to develop entirely autonomous sensors. By ensuring an important autonomy, the use of batteries solves part of the energy problem with relatively low costs. However, batteries introduce different problems such as maintenance and environmental pollution. Harvesting thermal, mechanical, electromagnetic, solar or wind energy present in the environment is an attractive solution. Using harvested energy from their surroundings, wireless sensor nodes can significantly increase their typical lifetime. Nevertheless, the harvested energy depends on the surrounding conditions of the device and can vary periodically or randomly. It seems important to adapt the system (measurement and data transmission) to the harvesting energy constraints. The thesis objective is to provide an autonomous sensor solution based on a multisources energy harvesting and management system (solar and wind energies), which can be used in different IoT applications. First, we are interested in modeling and optimizing the sensor node energy consumption. Then, the multiple harvesting system is modeled according to the energy needs of the sensor node. Besides, we focus on the power management of the autonomous system. This management part is based on predictions of both available and consumed energies. Finally, the proposed modeling and optimization studies are validated with experimental works in order to develop an Autonomous Communicating Sensor platform for IoT applications.

To get the best prices, sweet cherry growers must supply blemish-free fruit. Unfortunately, mature cherries have a fragile composition, rendering them susceptible to damage from heat, wind, birds, and rain. Rain is particularly devastating, because cherries split when they absorb too much water. Since rainstorms are common in the otherwise arid regions where most cherries are grown, growers must have a system for quickly deploying rain removal methods. The current industry solution relies on human observation and implementation, which is error-prone and costly. This project proposes an automated cherry wetness system using a Decagon Devices leaf wetness sensor (LWS) and a wireless sensor network (WSN). The research consists of analyzing industry and literature for uses of WSNs and LWSs in orchards and testing a LWS in a prototype WSN. The system will be evaluated for its potential to provide a precision-agriculture solution to the problem of remote cherry wetness detection.

This research proposed the use of state-of-the-art wireless communications and networked embedded systems technologies to provide environmental sensing for the early detection of natural disasters. The data is acquired, processed and transmitted, from the location where the disaster originates, to potentially threatened conurbations in order to promptly notify the population. The acquired data is transformed from its raw form into information that can be utilized by local authorities to rapidly assess emergency situations and then to apply disaster management procedures. Alternatively, the system can generate alerting signals without human intervention. Furthermore, recorded historical data can be made available for scientists to build models, to understand and to forecast the behavior of disasterous events. An additional, important, contribution of this research was the analysis and application of Wireless Sensor Network technology for disaster monitoring and alerting.