This thesis investigated the possibility of integrating a small photovoltaic module in a wireless sensor network node prototype made for use in crop production, mainly in greenhouses. The main question was if the simple photovoltaic module could provide enough power to the prototype's recharge system in order to continuously recharge the battery and thereby reducing the time maintaining the device due to its power consumption. Through measurements, both of the energy supplied by the potential photo voltaic modules and the prototype's power demand, the conclusion was that the power would not be sufficient due to the concealing environment in which the device would be placed. However, suggestions for further work was given in how the proposed idea could be developed.

Made available in DSpace on 2014-12-17T14:56:12Z (GMT). No. of bitstreams: 1 RafaelleACF_DISSERT.pdf: 3862937 bytes, checksum: 6acc4a4b451409b32a954e89796aec73 (MD5) Previous issue date: 2012-12-20 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Traditional irrigation projects do not locally determine the water availability in the soil. Then, irregular irrigation cycles may occur: some with insufficient amount that leads to water deficit, other with excessive watering that causes lack of oxygen in plants. Due to the nonlinear nature of this problem and the multivariable context of irrigation processes, fuzzy logic is suggested to replace commercial ON-OFF irrigation system with predefined timing. Other limitation of commercial solutions is that irrigation processes either consider the different watering needs throughout plant growth cycles or the climate changes. In order to fulfill location based agricultural needs, it is indicated to monitor environmental data using wireless sensors connected to an intelligent control system. This is more evident in applications as precision agriculture. This work presents the theoretical and experimental development of a fuzzy system to implement a spatially differentiated control of an irrigation system, based on soil moisture measurement with wireless sensor nodes. The control system architecture is modular: a fuzzy supervisor determines the soil moisture set point of each sensor node area (according to the soil-plant set) and another fuzzy system, embedded in the sensor node, does the local control and actuates in the irrigation system. The fuzzy control system was simulated with SIMULINK? programming tool and was experimentally built embedded in mobile device SunSPOTTM operating in ZigBee. Controller models were designed and evaluated in different combinations of input variables and inference rules base / Projetos de irriga??o tradicionais n?o determinam localmente a disponibilidade de ?gua no solo. Assim, podem ocorrer ciclos irregulares de irriga??o: alguns insuficientes, o que provoca d?ficit de ?gua; outros em demasia, o que causa falta de oxigena??o nas plantas. Devido ? natureza n?o-linear do problema e do ambiente multivari?vel de processos de irriga??o, a l?gica fuzzy ? sugerida como substituta aos sistemas comerciais de irriga??o tipo ON-OFF com temporiza??o pr?-definida. Outra limita??o das solu??es comerciais ? que os processos de irriga??o n?o atendem ?s diferentes necessidades h?dricas dos ciclos de crescimento das culturas nem ?s mudan?as nas vari?veis clim?ticas. Dessa maneira, para atender necessidades agr?colas baseadas em localiza??o, ? indicado monitorar dados ambientais usando sensores sem fio, interligados a um sistema de controle inteligente. Isso ? mais evidente em aplica??es de agricultura de precis?o. Este trabalho apresenta o desenvolvimento te?rico e experimental de um sistema de controle fuzzy espacialmente diferenciado para um sistema de irriga??o, baseado no sensoriamento da umidade do solo com n?s sensores sem fio. A arquitetura do sistema de controle ? modular: um sistema supervis?rio fuzzy determina o set point de umidade do solo da regi?o de atua??o do n? sensor (de acordo com o conjunto solo-plantaclima) e outro fuzzy, embarcado no n? sensor, faz o controle local e atua no sistema de irriga??o. O sistema de controle fuzzy foi simulado com a ferramenta de programa??o SIMULINK? e foi constru?do experimentalmente como sistema embarcado em um dispositivo m?vel SunSPOTTM operando com ZigBee. Modelos de controladores foram desenvolvidos e avaliados em diferentes combina??es de vari?veis de entrada e base de regras de infer?ncia

Wireless Sensor Networks (WSNets), consisting of a lot of Wireless Sensor Nodes (WSNs), play an important role in structural health and machine condition monitoring. But the WSNs provided by the current market cannot meet the diversity of application requirements because they have limited functions, unreliable node performance, high node cost, high system redundancy, and short node lifespan. The aim of the research is to design the architecture of a WSN with low power consumption and node cost, which can be dynamically configured according to application requirements for structural health and machine condition monitoring. This research investigates the improvement of node performance and reliability through the new design methodologies and the extension of node lifespan by interfacing energy harvesters and implementing node power management. The main contributions of the research are presented from the following aspects:1. Model development of node architecture for application diversityThe merits of model include: (1) The proposed node architecture can be dynamically configured in terms of application requirements for reducing system redundancy, power consumption and cost; (2) It supports multichannel signal measurement with the synchronous and asynchronous signal sampling modules and three interface circuits; (3)The model parameters can be calculated; (4) As the model is based on discrete electronic components, it can be implemented by using Components-Off-The-Shelf (COTS).2. A novel pipeline design of the built-in ADC inside a microprocessorThe merit of proposed pipeline solution lies in that the sampling time of the built-in ADCs is reduced to one third of the original value, when the ADC operates in sequence sampling mode based on multichannel signal measurement.3. Self-adjusting measurement of sampled signal amplitude This work provides a novel method to avoid the distortion of sampled signals even though the environmental signal changes randomly and over the sampling range of the node ADC. The proposed method can be implemented with four different solutions.4. Interface design to support energy harvesting The proposed interface will allow to: (1) collect the paroxysmal ambient energy as more as possible; (2) store energy to a distribution super-capacitor array; (3) harvest electrical energy at high voltage using piezoelectric materials without any transformer; (4) support the diversity of energy transducers; and (5) perform with high conversion efficiency.5. A new network task scheduling model for node wireless transceiver The model allows to: (1) calculate node power consumption according to network task scheduling; (2) obtain the optimal policy for scheduling network task.6. A new work-flow model for a WSN The model provides an easy way to (1) calculate node power consumption according to the work flow inside a WSN; (2) take fully advantage of the power modes of node electronic components rather than outside factors; (3) improve effectively node design.

The goal of this diploma work is to study the problems of wireless sensor networks. Describe elements of sensor network and discuss how the individual sensor nodes communicate with each other. Find the way how it would be possible to determine the possition of the new added sensor node or mobile sensor node in the sensor network. The selected one algorithm of determining the possition of the sensor node will be implemented in diploma thesis. Algorithms for determining the positions of sensor nodes are divided into groups by using the methods. Selected algorithm will be tested in simulation on chosen platform.

Nowadays, wireless sensor networks can be found in many new application areas. In these sensor networks there may exit a part of the network which are difficult to access or lie in a wide area, far apart. A change in the software (e.g., function update or bug fix) can entail reprogramming of all sensor nodes. This is very time consuming and labour intensive, if the patching has to be done manually for each individual sensor nodes. In the area of mobile phones, the over the air (OTA) update function has been established very well with good reliability. In embedded systems such as sensor nodes, where resources are severely restricted, an update cannot be stored but must be programmed directly with the transfer. For this to be possible, a lot of basic functionality is needed to be established to correct errors or to be able to resume a failed programming. Within the framework of this thesis a concept for the transmission and distribution of the firmware and programming the sensor node is established. Focus here is to optimize the use of resources and to provide basic functionality within the programming mode.

Although wireless sensor networks have been successfully used for environmental monitoring, one of the major challenges that this technology has been facing is supplying continuous and reliable electrical power during long-term field deployment. Batteries require repetitive visits to the deployment site to replace them once discharged; admittedly, they can be recharged from solar panels, but this only works in open areas where solar radiation is unrestricted. This dissertation introduces a novel approach to design and implement a reliable efficient solar energy harvester to continuously, and autonomously, provide power to wireless sensor nodes for long-term applications. The system uses supercapacitors charged by a solar panel and is designed to reduce power consumption to very low levels. Field tests were conducted for more than a year of continuous operation and under a variety of conditions, including areas under dense foliage. The resulting long-term field data demonstrates the feasibility and sustainability of the harvester system for challenging applications. In addition, we analyzed solar radiation data and supercapacitor charging behavior and showed that the harvester system can operate battery free, running on the power provided by supercapacitors. A battery is included only for backup in case the supercapacitor storage fails. The proposed approach provides continuous power supply to the system thereby significantly minimizing data loss by power failure and the frequency of visits to the deployment sites.

Sensorer kan användas för att uppmäta små partiklar som flyger omrking i luften och därmed skapa en bild av luftkvaliteten. Dessa sensorer sitter monterade på en så kallad sensornod. Sensornoder kan kopplas ihop för att skapa större sensornätverk. Problemet som tacklas i denna rapport är implementationen av stöd för en ny typ av sensor, Cubic PM2105, i en existerande sensornodsplatform. Utökat stöd för fler sensorer i ett sensornätverk breddar valmöjligheterna och möjliggör potentiellt att den bättre sensor kan användas. Vidare utvärderas även Cubic PM2105 i förhållande till en existerande sensor, Plantower PMS5003, i sensornodsplatformen. Detta görs genom korrelationsanalys baserat på mätdata de båda sensorerna samlat in vid samma tidpunkt och geografiska position. Resultatet visar på dålig korrelation mellan de två sensorerna. Dock kan detta resultat ifrågasattas då korrelationsanalysen baserades på relativt lite mätdata, samtidigt som endast en uppsättning sensorer användes. En teori för det dåliga resultatet är att fläkten på Cubic sensorn är svagare, och inte lyckas ta in tillräckligt med partiklar. Om detta beror på det specifika exemplaret eller andra orsaker är okänt. Med drivrutiner för Cubic PM2105 implementerat är det dock nu möjligt att utföra längre tester med fler uppsättningar sensorer för att på ett bättre sätt utvärdera korrelationen mellan sensorerna. / Sensors can be used to measure small particles in the air and hence create a picture of the air quality. These sensors are mounted on a so called sensor node. Sensor nodes can be connected to create a bigger sensor network. The problem being tackled in this report is the implementation of support for a new type of sensor, Cubic PM2105, in an existing sensor node platform. Extended support for more sensors in a sensor network widens the possibilities and enables the potential to use the better sensor. Further, Cubic PM2150 is evaluated in relation to a sensor already supported by the platform, Plantower PMS5003. This is done through correlation analysis based on the data collected from the both sensors simultaneously at the same location. The result shows poor correlation between the two sensors. However, this result can be questioned as the correlation analysis based on relatively little measurement data, while only one set of sensors was used. One theory for the poor result is that the fan in the Cubic sensor is weaker, and fails to take in a sufficient amount of particles. If this is a result of the specific pair of sensors used or due to other reasons is unknown. However, with drivers for Cubic PM2105 implemented, it is now possible to perform longer tests with more sets of sensors to better evaluate the correlation between the sensors.

Dedicated sensors are widely used throughout many industries to monitor everyday operations, maintain safety, and report performance characteristics. In order to adopt a more sustainable solution, much research is being applied to self-powered sensing, implementing solutions which harvest wasted ambient energy sources to power these dedicated sensors. The adoption of not only wireless sensor nodes, but also self-powered capabilities in the nuclear energy process is critical as it can address issues in the overall safety and longevity of nuclear power. The removal of wires for data and power transmission can greatly reduce the cost of both installation and upkeep of power plants, while self-powered capabilities can further reduce effort and money spent in replacing batteries, and importantly may enable sensors to work even in losses to power across the plant, increasing plant safety. This thesis outlines three harvesting opportunities in the nuclear energy process from: thermal, vibration, and radiation sources in the main structure of the power plant, and from thermal and radiation energy from spent fuel in dry cask storage. Thermal energy harvesters for the primary and secondary coolant loops are outlined, and experimental analysis done on their longevity in high-radiation environments is discussed. A vibrational energy harvester for large rotating plant machine vibration is designed, prototyped, and tested, and a model is produced to describe its motion and energy output. Finally, an introduction to the design of a gamma radiation and thermal energy harvester for spent nuclear fuel canisters is discussed, and further research steps are suggested. / Master of Science

Emerging low power, embedded, wireless sensor devices are useful for wide range of applications, yet have very limited processing storage and especially energy resources. Sensor networks have a wide variety of applications in medical monitoring, environmental sensing and military surveillance. Due to the large number of sensor nodes that may be deployed and the required long system lifetimes, replacing the battery is not an option. Sensor systems must utilize the minimal possible energy while operating over a wide range of operating scenarios. The most of the efforts in the energy management in sensor networks have concentrated on minimizing energy consumption in the communication subsystem. Some researchers have also dealt with the issue of minimizing the energy in computing subsystem of a sensor network node. Some proposals using energy aware software have also been made. Relatively little work has been done on compiler controlled energy management in sensor networks. In this thesis, we present our investigations on how compiler techniques can be used to minimize CPU energy consumption in sensor network nodes. One effectively used energy management technique in general purpose processors, is dynamic voltage scaling. In this thesis we implement and evaluate a compiler assisted DVS algorithm and show its usefulness for a small sensor node processor. We were able to achieve an energy saving of 29% with a little performance slowdown. Scratchpad memories have been widely used for improving performance. In this thesis we show that if the scratchpad size for the system is chosen carefully, then large energy savings can be achieved by using a compiler assisted scratchpad allocation policy. With a small size of 512 byte scratchpad memory we were able to achieve 50% of energy savings. We also studied the behavior of dynamic voltage scaling in presence of scratchpad memory. Our results show that in presence of scratchpad memory less opportunities are found for applying dynamic voltage scaling techniques. The sensor network community lacks a comprehensive benchmark suite, for our study we also implemented a set of applications, representative of computational workload on sensor network nodes. The techniques studied in this thesis can easily be integrated with existing energy management techniques in sensor networks, yielding in additional energy savings.

The wireless sensor network is a key technology in the 21st century because it has multitude applications and it becomes the new way of interaction between physical environment and computer system. Moreover, the wireless sensor network is a high resource constraint system. Consequently, the techniques used for the development of traditional embedded systems cannot be directly applied. Today wireless sensor nodes were implemented by using only one single processor architecture. This approach does not achieve a robust and efficient energy wireless sensor network for applications such as precision agriculture (outdoor) and telemedicine. The aim of this thesis is to develop a new approach for the realization of a wireless sensor network node using multicore architecture to enable to increase both its robustness and lifetime (reduce energy consumption).