A wireless sensor node (WSN) system, capable of sensing animal motion and transmitting motion data wirelessly, is an effective and efficient way to monitor pigs' activity. However, the raw sensor data sampling and transmission consumes lots of power such that WSNs' battery have to be frequently charged or replaced. The proposed work solves this issue through WSN edge computing solution, in which a Random Forest Classifier (RFC) is trained and implemented into WSNs. The implementation of RFC on WSNs does not save power, but the RFC predicts animal behavior such that WSNs can adaptively adjust the data sampling frequency to reduce power consumption. In addition, WSNs can transmit less data by sending RFC predictions instead of raw sensor data to save power. The proposed RFC classifies common animal activities: eating, drinking, laying, standing, and walking with a F-1 score of 93%. The WSN power consumption is reduced by 25% with edge computing intelligence, compare to WSN power that samples and transmits raw sensor data periodically at 10 Hz. / Master of Science / A wireless sensor node (WSN) system that detects animal movement and wirelessly transmits this data is a valuable tool for monitoring pigs' activity. However, the process of sampling and transmitting raw sensor data consumes a significant amount of power, leading to frequent recharging or replacement of WSN batteries. To address this issue, our proposed solution integrates edge computing into WSNs, utilizing a Random Forest Classifier (RFC). The RFC is trained and deployed within the WSNs to predict animal behavior, allowing for adaptive adjustment of data sampling frequency to reduce power consumption. Additionally, by transmitting RFC predictions instead of raw sensor data, WSNs can conserve power by transmitting less data. Our RFC can accurately classify common animal activities, such as eating, drinking, laying, standing, and walking, achieving an F-1 score of 93%. With the integration of edge computing intelligence, WSN power consumption is reduced by 25% compared to traditional WSNs that periodically sample and transmit raw sensor data at 10 Hz.

Embedded systems are so ubiquitous that they account for almost 90% of all the computing devices. They range from very small scale devices with an 8-bit microcontroller and few kilobytes of RAM to large-scale devices featuring PC-like performance with full-blown 32-bit or 64-bit processors, special-purpose acceleration hardware and several gigabytes of RAM. Each of these classes of embedded systems have unique set of challenges in terms of hardware utilization, performance and power consumption. As network connectivity becomes a standard feature in these devices, security becomes an important concern. Public Key Cryptography is an indispensable tool to implement various security features necessary on these embedded platforms. In this thesis, we provide optimized PKC solutions on platforms belonging to two extreme classes of the embedded system spectrum. First, we target high-end embedded platforms Qualcomm Snapdragon and Intel Atom. Each of these platforms features a dual-core processor, a GPU and a gigabyte of RAM. We use the SIMD coprocessor built into these processors to accelerate the modular arithmetic which accounts for the majority of execution time in Elliptic Curve Cryptography. We exploit the structure of NIST primes to perform the reduction step as we perform the multiplication. Our implementation runs over two times faster than OpenSSL implementations on the respective platforms. The second platform we targeted is an energy-harvested wireless sensor node which has a 16-bit MSP430 microcontroller and a low power RF interface. The system derives its power from a solar panel and is constrained in terms of available energy and computational power. We analyze the computation and communication energy requirements for different signature schemes, each with a different trade-off between computation and communication. We investigate the Elliptic Curve Digital Signature Algorithm (ECDSA), the Lamport-Diffie one-time hash-based signature scheme (LD-OTS) and the Winternitz one-time hash-based signature scheme (W-OTS). We demonstrate that there’s a trade-off between energy needs, security level and algorithm selection. However, when we consider the energy needs for the overall system, we show that all schemes are within one order of magnitude from each another. / Master of Science

The Internet of Things will include many resource-constrained lightweight wireless sensing devices, hungry for energy, bandwidth and compute cycles. The sheer amount of devices involved will require new solutions to handle issues such as identification and power provisioning. First, to simplify identity management, device identification is moving from symmetric-key solutions to public-key solutions. Second, to avoid the endless swapping of batteries, passively-powered energy harvesting solutions are preferred. In this contribution, we analyze some of the feasible solutions from this challenging design space. We have built an autonomous, energy-harvesting sensor node which includes a micro-controller, RF-unit, and energy harvester. We use it to analyze the computation and communication energy requirements for Elliptic Curve Digital Signature Algorithm (ECDSA) with different security levels. The implementation of Elliptic Curve Cryptography (ECC) on small microcontrollers is challenging. Most of the earlier literature has considered optimizing the performance of ECC (with respect to cycle count and software footprint) on a given architecture. This thesis addresses a different aspect of the resource-constrained ECC implementation wherein the most suitable architecture parameters are identified for any given application profile. At the high level, an application profile for an ECC-based lightweight device, such as wireless sensor node or RFID tag, is defined by the required security level, signature generation latency and the available energy/power budget. The target architecture parameters of interest include core-voltage, core-frequency, and/or the need for hardware acceleration. We present a methodology to derive and optimize the architecture parameters starting from the application requirements. We demonstrate our methodology on a MSP430F5438A microcontroller, and present the energy/architecture design space for 80-bit and 128-bit security-levels, for prime field curves secp160r1 and nistp256. Our results show that energy cost per authentication is minimized if a microcontroller is operated at the maximum possible frequency. This is because the energy consumed by leakage (i.e., static power dissipation) becomes proportionally less important as the runtime of the application decreases. Hence, in a given energy harvesting method, it is always better to wait as long as possible before initiating ECC computations which are completed at the highest frequency when sufficient energy is available. / Master of Science

Augmenter la durée de vie d'une pile, voire s'en passer est aujourd'hui devenu une obligation pour les microsystèmes. En effet, à cette échelle, le remplacement des piles et leur rejet dans l'environnement sont problématiques. La voie préconisée pour répondre à cet enjeu est d'utiliser des sources d'énergie renouvelables (solaire, thermique et mécanique). Pour cela, nous proposons de développer une plateforme de récupération d'énergie multi-sources/multi-charges (MANAGY) capable de s'adapter à son environnement pour en extraire le maximum d'énergie et répondre à des applications diverses. L'architecture est constituée de chemins directs et de chemins indirects où l'énergie provenant des sources est d'abord transférée dans une unité de stockage avant d'être réutilisée par les charges du microsystème. L'utilisation de cette nouvelle architecture permet d'optimiser le transfert d'énergie entre sources et charges et améliore le rendement du système de 33%. Avant de développer une architecture multi-sources, nous avons cherché à améliorer le rendement de la source photovoltaïque (PV) qui, au vu de l'état de l'art, a la densité de puissance la plus élevée. La recherche du rendement maximum de la source PV revient à la recherche du point de puissance maximum (MPPT). Il existe pour chaque condition d'irradiance, de température, et d'énergie extraites un couple tension-courant permettant à la source de fournir un maximum de puissance (MPP). Grâce à l'utilisation de deux chemins de puissance, nous arrivons simultanément à créer une boucle de régulation faible puissance agissant sur le rapport cyclique du système de gestion d'énergie (MPPT) et une boucle de régulation de la tension de sortie agissant sur le transfert de l'énergie. La modélisation du système nous a permis de spécifier ses performances. Pour atteindre les performances requises, des architectures innovantes ont été réalisées qui ont fait l'objet de trois brevets. De plus, des blocs ne sont activés qu'aux instants de changement d'état du système et sont conçus, quand cela a été possible, avec des transistors fonctionnant en mode faible inversion. Toutes ces optimisations permettent au système de fonctionner sur une large plage de variation de l'éclairement (de conditions intérieures supérieures à 500 lux à extérieures) avec un rendement proche de 90%. / Enhancing the life time of battery or being able to work without it is today mandatory for microsystems. Most of systems are nowadays limited by the capacity of the embedded battery. Moreover the replacement and waste of baterries is no more possible at this scale. One way to achieve longer life time is the use of renewable energy sources (solar, thermal, or kinetic). This work proposes to develop a new energy harvesting platform with numerous sources and loads (MANAGY) able to adapt itself to the surrounding environment in order to extract the maximum of energy while answering to various of applications. The architecture is composed of directs and indirects power paths where the extracted energy coming from renewable sources is firstly transferred to a storage unit before being used by loads. This novel architecture makes it possible to optimize the energy transfer between sources and loads and to achieve a 33% gain. Before developing this architecture with numerous sources, we have searched to enhance the efficiency of the photovoltaic source which has the best power density at the state of the art. Looking for improving the efficiency of the PV source is the same as tracking the maximum power point (MPPT). There is for each irradiance, temperature and quantity of energy extracted a couple of voltage and current enabling the PV source to deliver the maximum of power (MPP). Thanks to the two power paths used we are able to create a low power feedback loop adjusting the duty cycle from the power management unit (MPPT) while having a second feedback loop optimizing the power transfer and regulating the output voltage. Thanks to a high level model we have specified the system performances. To achieve the performances required we have realized novel architectures protected through three patents. Moreover, blocs are only activated when the system changes its state and furthermore there are designs, when achievable, with transistors working in weak inversion. All these optimizations make the system working for a large range of irradiance (from inside conditions higher than 500 lux to outdoor conditions) with an efficiency close to 90%.

Wireless Sensor Networks (WSNs), in addition to enabling monitoring solutions for numerous new applications areas, have gained huge popularity as a cost-effective, dynamically scalable, easy to deploy and maintainable alternatives to conventional infrastructure-based monitoring solutions. A WSN consists of spatially distributed autonomous wireless sensor nodes that measure desired physical phenomena and operate in a collaborative manner to relay the acquired information wirelessly to a central location. A wireless sensor node, integrating the required resources to enable infrastructure-less distributed monitoring, is constrained by its size, cost and energy. In order to address these constraints, a typical wireless sensor node is designed based on low-power and low-cost modules that in turn provide limited communication and processing performances. Data and computation intensive wireless monitoring applications, on the other hand, not only demand higher communication bandwidth and computational performance but also require practically feasible operational lifetimes so as to reduce the maintenance cost associated with the replacement of batteries. In relation to the communication and processing requirements of such applications and the constraints associated with a typical wireless sensor node, this thesis explores energy efficient wireless sensor node architecture that enables realization of data and computation intensive applications. Architectures enabling raw data transmission and in-sensor processing with various technological alternatives are explored. The potential architectural alternatives are evaluated both analytically and quantitatively with regards to different design parameters, in particular, the performance and the energy consumption. For quantitative evaluation purposes, the experiments are conducted on vibration and image-based industrial condition monitoring applications that are not only data and computation intensive but also are of practical importance. Regarding the choice of an appropriate wireless technology in an architecture enabling raw data transmission, standard based communication technologies including infrared, mobile broadband, WiMax, LAN, Bluetooth, and ZigBee are investigated. With regards to in-sensor processing, different architectures comprising of sequential processors and FPGAs are realized to evaluate different design parameters, especially the performance and energy efficiency. Afterwards, the architectures enabling raw data transmission only and those involving in-sensor processing are evaluated so as to find an energy efficient solution. The results of this investigation show that in-sensor processing architecture, comprising of an FPGA for computation purposes, is more energy efficient when compared with other alternatives in relation to the data and computation intensive applications. Based on the results obtained and the experiences learned in the architectural evaluation study, an FPGA-based high-performance wireless sensor platform, the SENTIOF, is designed and developed. In addition to performance, the SETNIOF is designed to enable dynamic optimization of energy consumption. This includes enabling integrated modules to be completely switched-off and providing a fast configuration support to the FPGA.  In order to validate the results of the evaluation studies, and to assess the performance and energy consumption of real implementations, both the vibration and image-based industrial monitoring applications are realized using the SENTIOF. In terms of computational performance for both of these applications, the real-time processing goals are achieved. For example, in the case of vibration-based monitoring, real-time processing performance for tri-axes (horizontal, vertical and axial) vibration data are achieved for sampling rates of more than 100 kHz. With regards to energy consumption, based on the measured power consumption that also includes the power consumed during the FPGA’s configuration process, the operational lifetimes are estimated using a single cell battery (similar to an AA battery in terms of shape and size) with a typical capacity of 2600 mA. In the case of vibration-based condition monitoring, an operational lifetime of more than two years can be achieved for duty-cycle interval of 10 minutes or more. The achievable operational lifetime of image-based monitoring is more than 3 years for a duty-cycle interval of 5 minutes or more.

This study is devoted to investigating and developing WSN based localisation approaches with high position accuracies indoors. The study initially summarises the design and implementation of localisation systems and WSN architecture together with the characteristics of LQI and RSSI values. A fingerprint localisation approach is utilised for indoor positioning applications. A k-nearest neighbourhood algorithm (k-NN) is deployed, using Euclidean distances between the fingerprint database and the object fingerprints, to estimate unknown object positions. Weighted LQI and RSSI values are calculated and the k-NN algorithm with different weights is utilised to improve the position detection accuracy. Different weight functions are investigated with the fingerprint localisation technique. A novel weight function which produced the maximum position accuracy is determined and employed in calculations. The study covered designing and developing the centroid localisation (CL) and weighted centroid localisation (WCL) approaches by using LQI values. A reference node localisation approach is proposed. A star topology of reference nodes are to be utilized and a 3-NN algorithm is employed to determine the nearest reference nodes to the object location. The closest reference nodes are employed to each nearest reference nodes and the object locations are calculated by using the differences between the closest and nearest reference nodes. A neighbourhood weighted localisation approach is proposed between the nearest reference nodes in star topology. Weights between nearest reference nodes are calculated by using Euclidean and physical distances. The physical distances between the object and the nearest reference nodes are calculated and the trigonometric techniques are employed to derive the object coordinates. An environmentally adaptive centroid localisation approach is proposed. Weighted standard deviation (STD) techniques are employed adaptively to estimate the unknown object positions. WSNs with minimum RSSI mean values are considered as reference nodes across the sensing area. The object localisation is carried out in two phases with respect to these reference nodes. Calculated object coordinates are later translated into the universal coordinate system to determine the actual object coordinates. Virtual fingerprint localisation technique is introduced to determine the object locations by using virtual fingerprint database. A physical fingerprint database is organised in the form of virtual database by using LQI distribution functions. Virtual database elements are generated among the physical database elements with linear and exponential distribution functions between the fingerprint points. Localisation procedures are repeated with virtual database and localisation accuracies are improved compared to the basic fingerprint approach. In order to reduce the computation time and effort, segmentation of the sensing area is introduced. Static and dynamic segmentation techniques are deployed. Segments are defined by RSS ranges and the unknown object is localised in one of these segments. Fingerprint techniques are applied only in the relevant segment to find the object location. Finally, graphical user interfaces (GUI) are utilised with application program interfaces (API), in all calculations to visualise unknown object locations indoors.

In Wireless Sensor Networks, designing a low overhead routing protocol is crucial for prolonging network lifetime. Wireless sensor nodes depend on limited batteries and if they run out of battery, they cannot contribute to the sensing. There are lots of studies aimed at prolonging network lifetime. One of the methods to extend life time of the wireless sensor networks is clustering. In clustering approaches main aim is to prevent unnecessary messaging and decrease number of messages exchanged by aggregating messages. Clustering also contributes to prolong network life time by ruling the child node communications and therefore it decreases message loss caused by transmission collisions. Cluster heads in clusters schedule nodes for sending and receiving messages. In this thesis, a clustering approach based on queries disseminated by sinks is proposed. Two methods to prolong lifetime of sensor network by forming appropriate clusters and selecting suitable cluster heads is developed. Performance of the proposed methods is also evaluated with computer simulations.

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.