Today, Internet of Things (IoT) is the driving force in making operations and processes smart. Indoor localization is such an application of IoT that has proven the potential of location awareness in countless scenarios, from mines to industries to even people. nanotron Technologies GmbH, based in Berlin, is one of the pioneers in low power location systems. nanotron's embedded location platform delivers location-awareness for safety and productivity solutions across industrial and consumer markets. The platform consists of chips, modules and software that enable precise real-time positioning and concurrent wireless communication. The ubiquitous proliferation of interoperable platforms is creating the locationaware Internet of Things. One of their product families is swarm. A swarm is a group of independent radios or nodes which facilitates the nodes to communicate with their immediate neighboring nodes to get each other’s positions. This position information is collected by one of the nodes (called gateway) and delivered to the host controller. However, the nodes need to be in range to communicate. The company wants to improve the range of communication and for that purpose; I am implementing a routing protocol with some additional changes for swarm, to allow out-of-range nodes to communicate via intermediate neighbors. This is called mesh networking which would result in so-called ‘mesh’ of nodes and would increase the range of swarm operation that could be beneficial in achieving uniform connectivity throughout large spaces without needing excessive number of gateways. This is of high importance because a node acting as gateway should be ‘awake’ all the time so that it can collect data efficiently, while the other nodes can beon power saving mode. Mesh networking will allow data collection even with fewer such gateways thereby being energy efficient while facilitating larger range of communication. This was made possible by adding the feature of allowing nodes to store messages for their neighbors in case they are asleep and wake up for the neighbors to transmit data. It is done using a schedule that is built and updated in addition to the routing protocol. The purpose of this thesis is to justify the implemented mesh routing protocol for swarm among all the other routing protocols available. It also focuses on the modifications and improvements that were devised to make the protocol tailored for how swarm works and to support Message Queuing Telemetry Transport (MQTT) on top of it, at a later stage. MQTT is a lightweight messaging protocol that provides resource-constrained network clients with a simple way to distribute information. It uses a publish/subscribe communication pattern and is used for machine-to-machine (M2M) communication and plays an important role in the Internet of Things. The implemented routing protocol also takes into consideration, the sleeping nodes, route maintenance through advertisements, hierarchical nature of mesh to make data collection more efficient, message formats keeping in mind the memory shortage, etc. The document gives a thorough overview of concepts, design implementation, improvements and tests to prove the importance of mesh networking in existing swarm.

Yes / Sensing coverage and network connectivity are two of the most fundamental issues to ensure that there are effective environmental sensing and robust data communication in a WSN application. Random positioning of nodes in a WSN may result in random connectivity, which can cause a large variety of key parameters within the WSN. For example, data latency and battery lifetime can lead to the isolation of nodes, which causes a disconnection between nodes within the network. These problems can be avoided by using mobile data sinks, which travel between nodes that have connection problems. This research aims to design, test and optimise a data collection system that addresses the isolated node problem, as well as to improve the connectivity between sensor nodes and base station, and to reduce the energy consumption simultaneously. In addition, this system will help to solve several problems such as the imbalance of delay and hotspot problems. The effort in this paper is focussed on the feasibility of using the proposed methodology in different applications. More ongoing experimental work will aim to provide a detailed study for advanced applications e.g. transport systems for civil purposes. / European Union’s Horizon 2020 research and innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424.

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.

[ES] Las redes de sensores inalámbricas (WSN) han experimentado un resurgimiento debido al desarrollo de la Internet de las Cosas (IoT). Una de las características de las aplicaciones de la IoT es la necesidad de hacer uso de dispositivos sensores y actuadores. En aplicaciones como automatización de edificios, de gestión energética, industriales o de salud, los nodos sensores que componen la WSN, transmiten información a un colector central o sink. La información es posteriormente procesada, analizada y utilizada para propósitos específicos. En cada una de estas aplicaciones, los dispositivos sensores pueden considerarse como parte de una WSN. En ese sentido el modelado y la evaluación de las prestaciones en las WSN es importante, ya que permite obtener una visión más clara de su comportamiento, facilitando un adecuado diseño y una exitosa puesta en operación. En el presente trabajo de tesis se han desarrollado modelos matemáticos para evaluar las prestaciones de WSN, los cuales están basados en Cadenas de Markov en Tiempo Discreto (DTMC). Los parámetros de prestaciones elegidos para la evaluación son: energía consumida promedio, eficiencia energética, caudal cursado y retardo promedio de los paquetes. Los resultados que se han obtenido han sido validados por medio de simulación basada en eventos discretos (DES). Existen estudios de WSN en escenarios homogéneos, donde los nodos que componen la red inalámbrica son del mismo tipo y tienen las mismas características de operación. En estos análisis se definen WSN homogéneas compuestas por un nodo central o sumidero (sink), que recibe la información de los nodos sensores localizados alrededor, formando una célula o cluster. Estos nodos realizan las transmisiones en SPT (Single Packet Transmission), enviando un solo paquete por ciclo de transmisión. Sin embargo, es posible encontrar, más ahora con el desarrollo de la IoT, escenarios donde coexisten distintos tipos de nodos, con características diferentes y, por tanto, con requerimientos de operación específicos. Esto da lugar a la formación de clusters cuyos nodos tienen aplicaciones distintas, desigual consumo de energía, diversas tasas de trasmisión de datos, e incluso diferentes prioridades de acceso al canal de transmisión. Este tipo de escenarios, que denominamos heterogéneos, forman parte de los escenarios estudiados en el presente trabajo de tesis. En una primera parte, se ha desarrollado un modelo para evaluar las prestaciones de una WSN heterogénea y con prioridades de acceso al medio. El modelado incluye un par de DTMC de dos dimensiones (2D-DTMC) cada una, cuya solución en términos de la distribución de probabilidad estacionaria, es utilizada para determinar los parámetros de prestaciones. Se desarrollan, por tanto, expresiones cerradas para los parámetros de prestaciones, en función de la distribución estacionaria que se ha obtenido a partir de la solución de las 2D-DTMC. En una segunda parte, se desarrolla un modelo analítico también pensado para escenarios heterogéneos y con prioridades, pero en el que los nodos de la WSN, cuando consiguen acceso al canal, transmiten un conjunto de paquetes en vez de uno solo como en el modelo de la primera parte. Estos dos modos de operación de los sensores los denominamos aggregated packet trans- mission (APT) y single packet transmission (SPT), respectivamente. El número de paquetes que un nodo funcionando en APT trasmite cuando accede al canal es el menor entre un parámetro configurable y el número de paquetes que tuviera en la cola en ese momento. Este modo de operación consigue una mayor eficiencia energética y un aumento en el caudal cursado, además de una disminución en el retardo promedio de los paquetes. En una tercera parte, se propone un nuevo procedimiento analítico para la determinación del consumo energético de los nodos que conforman una WSN. A diferencia de los métodos de cálculo anteriores, la nueva prop / [CA] Les xarxes de sensors sense fils (WSN) han experimentat un ressorgiment causa de al desenvolupament de la Internet de les Coses (IoT). Una de les característiques de IoT és la inclusió, en les seves aplicacions, de dispositius sensors i actuadors. En aplicacions com automatització d'edificis, de gestió energètica, industrials o de salut, els nodes sensors que componen la WSN, transmeten informació a un col·lector central o sink. La informació és posteriorment processada, analitzada i utilitzada per a propòsits específics. En cadascuna d'aquestes aplicacions, els dispositius sensors poden considerar com a part d'una WSN. En aquest sentit el modelitzat i l'avaluació de l'acompliment en les WSN és important, ja que permet obtenir una visió més clara del seu comportament, facilitant un adequat disseny i una exitosa posada en operació. En el present treball de tesi s'han desenvolupat models matemàtics per avaluar l'acompliment de WSN, els quals estan basats en Cadenes de Markov en Temps Discret (DTMC). Els paràmetres d'acompliment obtinguts per a l'avaluació són: energia consumida mitjana, eficiència energètica, cabal cursat i retard mitjà dels paquets. Els resultats que s'han obtingut, han estat validats per mitjà de simulació basada en esdeveniments discrets (DES). Existeixen estudis de WSN en escenaris homogenis, on els nodes que componen la xarxa sense fils són de el mateix tipus i tenen les mateixes característiques d'operació. En aquests anàlisis prèvies es defineixen WSN homogènies compostes per un node central o embornal (sink), que rep la informació dels nodes sensors localitzats al voltant, formant una cèl·lula o cluster. Aquests nodes realitzen les transmissió en SPT (Single Packet Transmission), és a dir, enviant un sol paquet cada vegada que transmeten. No obstant això, és possible trobar, més ara amb el desenvolupament de la IOT, escenaris on hi ha una coexistència de distints tipus de nodes, amb característiques diferents i, per tant, amb requeriments d'operació específics. Això dona lloc a formació de clusters els nodes tenen aplicacions diferents, desigual consum d'energia, diverses taxes de transmissió de dades, i fins i tot diferent prioritats d'accés a canal de transmissió. Aquest tipus d'escenaris, que anomenem heterogenis, formen part dels escenaris estudiats en el present treball de tesi. En una primera part, s'ha desenvolupat un model per avaluar l'acompliment d'una WSN heterogènia i amb prioritats d'accés al medi. El modelitzat inclou un parell DTMC de dues dimensions (2D-DTMC), la solució en termes de la distribució estacionària de probabilitat, és utilitzada per obtenir posteriorment els paràmetres d'acompliment. Es desenvolupen, per tant, expressions tancades per a la determinació dels paràmetres d'acompliment, on és substituïda la distribució estacionària que s'ha obtingut a partir de la solució de les 2D-DTMC. En una segona part, es desenvolupa un model, en el qual els nodes pertanyents a la WSN, poden transmetre els seus paquets en agregat (APT) en escenaris heterogenis i amb prioritats. A diferència del model anterior, on els nodes transmeten un paquet per cicle (SPT), en APT els nodes poden transmetre més d'un paquet. Això porta com a conseqüència una major eficiència energètica, a més d'un augment en el cabal cursat i disminució en el retard mitjana. En una tercera part, es proposa un nou desenvolupament analític per a la determinació del consum energètic dels nodes que conformen una WSN. A diferència de les expressions utilitzades anteriorment per al càlcul del consum energètic, aquesta proposta alternativa permet obtenir resultats més precisos a través del desenvolupament d'expressions més intuïtives i sistemàtiques. Amb aquest nou procediment, es realitzen estudis energètics per WSN en escenaris homogenis i heterogenis. / [EN] Wireless sensor networks (WSN) have experienced a resurgence due to the development of the Internet of Things (IoT). One of the characteristics of IoT is the deployment of applications that require sensor devices and actuators. In applications such as building automation, energy management, industrial or health, the sensor nodes that make up the WSN transmit information to a central collector or sink. The information is processed, analyzed, and used for specific purposes. In each of these applications, the sensor devices can be considered part of a WSN. In this sense, the modeling and performance evaluation of WSN is important, since it allows obtaining a clearer vision of their behavior, facilitating an adequate design and a successful operation. In the present thesis, analytical models based on Discrete Time Markov Chains (DTMC) have been developed to evaluate the performance of WSN. The parameters defined for the performance evaluation are: average consumed energy, energy efficiency, throughput and average packet delay. The obtained results have been validated by means of discrete event simulation (DES). There are studies of WSN in homogeneous scenarios, where the nodes that compose the WSN are of the same type and have the same operating characteristics. In these previous studies, homogeneous WSN are defined as a cell or cluster composed of a central node or sink, which receives the information from the sensor nodes located around it. These nodes operate in SPT (Single Packet Transmission), sending a single packet per transmission cycle. However, it is possible to find, especially now with the development of the IoT, scenarios where different types of nodes coexist, although they have different characteristics or specific operational requirements. This results in the formation of clusters whose nodes have different applications, uneven power consumption, different data transmission rates, and even different priorities for access to the transmission channel. These types of scenarios, which we call heterogeneous, are part of the scenarios studied in this thesis work. In the first part, a model has been developed to evaluate the performance of a heterogeneous WSN and with priorities to access a common channel. The model includes a two-dimensional DTMC pair (2D-DTMC), whose solution in terms of the stationary probability distribution is used to obtain the performance parameters. Closed expressions are provided for the determination of performance parameters of interest, given in terms of the stationary distribution of the 2D-DTMC. In a second part, an analytical model is developed to evaluate the performance of a heterogeneous WSN, where nodes operate in aggregate packet transmission (APT) mode and deploy different channel access priorities. Un like the previous model, where the nodes transmit one packet per cycle (SPT) when they gain access to the channel, in APT the nodes can transmit a number of packets larger than one, that is the minimum between a configurable parameter and the number of packets in the packet queue of the node. This results in greater energy efficiency and throughput, while decreases the average packet delay. In a third part, a new analytical model is proposed to determine the energy consumption of the nodes that make up a WSN. Unlike previous computation procedures, this alternative proposal is based on more intuitive and systematic expressions and allows to obtain more accurate results. With this new procedure, energy studies are performed for WSN in homogeneous and heterogeneous scenarios. / Este trabajo se ha desarrollado en el marco de los siguientes proyectos de investigación: Platform of Services for Smart Cities with Dense Machine to Machine Networks, PLASMA, TIN2013-47272-C2-1-R and New Paradigms of Elastic Networks for a World Radically Based on Cloud and Fog Computing, Elastic Networks, TEC2015-71932-REDT. También quisiera agradecer el apoyo recibido por parte de the European Union under the program Erasmus Mundus Partnerships, project EuroinkaNet, GRANT AGREEMENT NUMBER - 2014-0870/001/001 y La Secretaria de Educación Pública (México), bajo el Programa para el Desarrollo Profesional Docente: SEP-SES (DSA/103.5/15/6629). / Portillo Jiménez, C. (2021). Modelado y evaluación de prestaciones de redes de sensores inalámbricos heterogéneos con ciclo de trabajo síncrono [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/171275 / TESIS

Au cours des dernières années, différents travaux de recherche ont été consacrés à l’étude et au développement des solutions de type réseau de capteurs sans fil. Ces travaux sont une réponse à l’augmentation du nombre d’objets connectés dans le monde avec le développement de l’internet des objets. La consommation d’énergie dans les réseaux de capteurs représente un des domaines les plus étudiés. Les communications dans les réseaux de capteurs représentent une part importante de leur consommation. Afin de réduire la consommation des communications dans les réseaux de capteurs, différents niveaux d’optimisation sont possibles. Dans ce contexte, différents travaux de recherches visant à réduire la consommation des émetteurs-récepteurs, grâce à des architectures innovantes, ont été menés à l’IM2NP. Beaucoup de ces travaux ont été consacrés aux radios impulsionnelles Ultra-Large Bande (ULB). En outre, les protocoles d’accès aux canaux de communications dans les réseaux de capteurs sont également importants quant à l’optimisation de leurs consommations. Les travaux de recherches proposés dans ce manuscrit, basés sur les travaux sur les radios impulsionnelles ULB réalisés au sein de l’IM2NP, proposent une optimisation de la consommation des réseaux de capteurs sur deux niveaux. Tout d’abord, un protocole asynchrone à base de radio de réveil d’accès au canal de communication adapté aux communications ULB est proposé ainsi que son étude énergétique. Suite à l'étude du protocole asynchrone proposé, la conception d’un récepteur de réveil semi-passif et d’un générateur d’impulsion ULB sous-GHz est abordée, et leurs performances en termes d’efficacité énergétique discutées. / In recent years, research has been devoted to the study and development of Wireless Sensor Network (WSN). These research are a response to the increase of the connected objet number in the world with development of smartphones and Internet of things (IoT). Energy consumption in sensor networks is one of the most studied areas. In fact, the optimization of the consumption of the elements making up the sensor networks allows a reduction in the costs associated with their installation, operation and maintenance. Communications in sensor networks represent an important part of their power consumption. In order to reduce the consumption of communications in sensor networks, different levels of optimization are possible. In this context, various IM2NP research projects aimed at reducing transceiver consumption through innovative design were carried out. Much of this work has been devoted to Impulsionnal Radio Ultra-Wide Band (IR-UWB). Moreover, MAC protocols used to manage the communication channel access in wireless sensor networks are also important in optimizing their consumption. The research work proposed in this manuscript, based on the work on impulse radios UWB carried out within the IM2NP, propose an optimization of the consumption of sensor networks on two levels. Firstly, an asynchronous MAC protocol based on radio wake-up radio suitable for UWB communications is proposed as well as its energy study. Following the study of the proposed asynchronous protocol, the design of a low power semi-passive wake-up receiver (WuRx) and a UWB sub-GHz impulse generator is presented and their performance in terms of energy efficiency discussed.

Les Réseaux de capteurs sans fil (WSN) sont une technologie émergente avec des applications potentielles dans divers domaines de la vie quotidienne, tels que la surveillance structurelle et environnementale, la médecine, la surveillance militaire, les explorations robotisées, etc. Les nœuds de capteurs doivent fonctionner pendant une longue période avec des batteries capacité limitée, par conséquent le facteur plus important dans les WSN est la consommation d'énergie. Dans cette thèse, nous proposons des techniques d'optimisation algorithmiques dynamiques, et adaptative pour la réduction de l'énergie. Tout d'abord, un modèle énergétique précis est présenté. Ce modèle repose sur des mesures réelles de courant consommé pour différents scénarios qui peuvent se produire lors de la communication entre les nœud. Il en est conclu que la couche MAC joue un rôle essentiel dans la réduction de l'énergie consommée. Ensuite, un protocole MAC dynamique est présenté. Il adapte de manière dynamique l’intervalle de réveil des nœuds de capteurs à partir d’une estimation du trafic. L’algorithme adaptatif modélisé de façon heuristique pour comprendre le comportement de convergence des paramètres algorithmiques. Le protocole est appliqué sur des réseaux de capteurs corporels et il surclasse les autres protocoles MAC en termes de latence ainsi que de consommation d'énergie ce qui permet donc d'augmenter la durée de vie de trois à six fois. Enfin, une technique basée sur l’optimisation adaptative de la puissance d'émission radio est appliquée sur des canaux variant dans le temps. La puissance de sortie est réglée dynamiquement au meilleur niveau de puissance selon l’état du canal, ce qui diminue la consommation d’un facteur deux. / Wireless Sensor Networks (WSN) are a fast emerging technology with potential applications in various domains of daily-life, such as structural and environmental monitoring, medicine, military surveillance, robotic explorations etc. WSN devices are required to operate for a long time with limited battery capacity, therefore, the most important constraint in WSN is energy consumption. In this thesis, we propose algorithmic-level dynamic and adaptive optimization techniques for energy reduction in WSN. First, an accurate energy model is presented. This model relies on real-time power measurements of various scenarios that can occur during communication between sensor nodes. It is concluded that MAC layer plays a pivotal role for energy reduction. Then, a traffic-aware dynamic MAC protocol is presented which dynamically adapts the wake-up schedule of sensor nodes through traffic estimation. An adaptive algorithm is designed for this purpose that is heuristically modeled to understand the convergence behavior of algorithmic parameters. The proposed protocol is applied to body area networks and it outperforms other low-power MAC protocols in terms of latency as well as energy consumption and consequently increases the lifetime from three to six times. Finally, an SNR-based adaptive transmit power optimization technique is applied under time-varying channels. The output power is dynamically tuned to best power level under slow varying channel, which results in an average gain by two times.

In ultra-low power Wireless Sensor Networks (WSNs) sensor nodes need to interact, depending on the application, even at a rapid pace while preserving battery life. Wireless communication brings thereby quite the burden as the radio transceiver requires a relative huge amount of power during both transmission or reception phases. In WSNs with on demand communication, the sensor nodes are required to maintain responsiveness and to act the sooner they receive a request, reducing the overall latency of the network. The aspect is more challenging in asynchronous WSN as the receiver possesses no information about the packet arrival time. In a purely on-demand communication, duty-cycling shows little to almost no improvement. The receiving node, in such scheme, is expected to last for years while also being accessible to other peers. Here arises the utility of an external ultra-low power radio receiver known as Wake-up Receiver (WuRx). Its essential task is to remain as the only part of the system running while the rest of the systems enters the lowest power mode (i.e., sleep state). Once a request signal is received, it notifies the host processor and other peripherals for an incoming communication. With the sensor node being in sleep state (WuRx active only), substantial power levels can be achieved. If the WuRx is able to interact rapidly, the added latency remains negligible. As crucial performance figures, the sensitivity and bit rate are immediately affected by the extreme low-power budget at diifferent magnitudes, depending mainly on the incorporated architecture. This thesis focuses on the design of a feature-balanced WuRx. The passive radio frequency architecture (PRF) relies on passive detection while consuming zero power to extract On-Off-Keying (OOK) modulated envelopes. The featured sensitivity, however, is reduced compared to more complex architectures. A WuRx based on PRF architecture can effectively enable short-range applications. The sensitivity can vary with respect to several parameters including the total generated noise, circuit technology and topology. Two variants of the PRF WuRxs are introduced with the baseband amplifier being the main change. The first revision employs a high performance amplifier with reduced average energy consumption, thanks to a novel power gating control. The second variant focuses on employing an ultra-low power baseband amplifier as it is expected to be in a continuous active state. This thesis also brings the necessary analysis on the passive front-end with the intention to enhance the overall WuRx sensitivity. Proof of concepts are embedded in sensor node boards and feature -61 dBm and -64 dBm of sensitivity for the first and the second variant, respectively, at a packet-error-rate (PER) of 1% whilst demanding a similar power of 7.2 µW during packet listening. During packet decoding, the first variant demands a 150 µW of power, caused greatly by the baseband amplifier. The achieved latency is less than 30 ms and the bit rate is 4 kbit/s, Manchester encoding. For long-range applications, a higher sensitivityWuRx is proposed based on Tuned-RF (TRF) architecture. By embedding a low-noise amplifier (LNA) in the receiver chain, very weak radio signal can be detected. TheWuRx emphasizes higher sensitivity of -90 dBm. The design of the LNA prioritized the highest gain and lowest bias current by sacrifcing the linearity that poses little impact on signal integrity for the OOK modulated signals. The total active power consumption of the TRF WuRx is 1.38 mW. In this work, a fast sampling approach based on power gating protocol allows a drastic reduction in energy consumption on average. By being able to sample in matter of few microseconds, the WuRx is able to detect the presence of a packet and return to sleep state right after packet decoding. Being power-gated dropped the average power consumption to 2.8 µW at a packet detection latency of 32 ms for less than 2 s of interval time between communication requests. The proposed solutions are able to decode a minimum length of 16-bit pattern and operate in the license-free ISM band 868 MHz. This thesis also includes the analysis and implementation of low-power front-end building blocks that are employed by the proposed WuRx.:1 Introduction 1.1 Motivation 1.2 Wake-up Receiver Design Requirements 1.2.1 Energy Consumption 1.2.2 Network Coverage and Robustness 1.2.3 Wake-up Packet Addressing 1.2.4 WuPt Detection Latency 1.2.5 Hosting System, Form-factor and Fabrication Technology 1.3 Thesis Organisation 2 Wireless Sensor Networks 2.1 Radio Communication 2.1.1 Electromagnetic Spectrum 2.1.2 Link Budget Analysis 2.2 Asynchronous Radio Receiver Duty-cycle Control 2.2.1 B-MAC and X-MAC Protocols 2.2.2 Energy and Latency Analysis 2.3 Power Supply Requirements 2.3.1 Low Self-discharge Battery 2.3.2 Energy Harvester 2.4 Summary 3 State-of-the-Art of Wake-up Receivers 3.1 Wake-up Receiver Architectural Analysis 3.1.1 Passive RF Detector 3.1.2 Classical Radio Architectures 3.2 Wake-up Receiver Back-end Stages 3.2.1 Baseband Amplifiers 3.2.2 Analog to Digital Conversion 3.2.3 Wake-up Packet Decoder 3.3 Power Consumption Reduction at Circuit Level 3.3.1 Power Gating 3.3.2 Interference Rejection and Filtering 3.4 Summary 4 Proposal of Novel Wake-up Receivers 4.1 Ultra-low Power On-demand Communication in Wireless Sensor Networks: Challenges and Requirements 4.2 Passive RF Wake-up Receiver 4.3 Power-gated Tuned-RF Wake-up Receiver 5 Low-power RF Front-end 5.1 Narrow-band Low-noise Amplifier (LNA) 5.1.1 Topology 5.1.2 Voltage Gain 5.1.3 Stability 5.1.4 Noise Figure 5.1.5 Linearity 5.2 Envelope Detector 5.2.1 Theory of Square-law Detection and Sensitivity Analysis 5.2.2 Single-Diode Envelope Detector 5.2.3 Voltage Multiplier Envelope Detector 5.3 Hardware Assessment 5.3.1 LNA 5.3.2 Envelope Detector 5.4 Summary 6 Passive RF Wake-up Receiver 6.1 Circuit Implementation 6.1.1 Address Decoder 6.1.2 Envelope Detector 6.1.3 Power-gated Baseband Amplifier 6.1.4 Ultra Low-power Baseband Amplifier 6.2 Experimental Results 6.2.1 Wireless Sensor Node 6.2.2 Measurements 6.3 Summary 7 Power-gated Tuned-RF Wake-up Receiver 7.1 Power-gating Protocol 7.2 Circuit Design 7.2.1 Radio Front-end 7.2.2 Data Slicer 7.2.3 Digital Baseband 7.3 Performance Evaluation 7.4 Summary 8 Conclusion 8.1 Performance Summary 8.2 Future Perspective 8.3 Applications A Two-tone Simulation Setup B Diode Models and Simulation Setup C Preamble Detection C Code Implementation Bibliography Publications / In drahtlosen Sensornetzwerken (WSNs) mit extrem geringem Stromverbrauch müssen Sensorknoten je nach Anwendung kurze Latenzzeiten erreichen ohne die Batterielebensdauer zu beeinträchtigen. Die drahtlose Kommunikation bringt dabei eine ziemliche Belastung mit sich, da der Funktransceiver sowohl während der Sende- als auch der Empfangsphase relativ viel Strom benötigt. Einige marktfähige Funktransceiver benötigen durchschnittlich ca. 10 mA im Empfangsmodus sowie 30 mA im Sendemodus. Deshalb wird heutzutage das sogenannte Duty-Cycling mit bestimmten Sende-, Empfangs- und langen Schlafzeitintervallen eingeführt. Während der Schlafphase ist der Empfänger nicht ansprechbar. Was wiederum zu einer massiven Erhöhung der Latenzzeit führen kann. In vielen Anwendungen und insbesondere im Rahmen der Digitalisierung von Prozessen wird mittlerweile die Fähigkeit On-Demand mit sehr kurzen Latenzzeiten zu kommunizieren verlangt. Diese Anforderung steht in einem Wiederspruch zum genannten Duty-cycle Betrieb. Um dieses Dilemma zu lösen wird im Rahmen dieser Doktorarbeit ein Funkempfänger mit extrem geringen Stromverbrauch untersucht und entwickelt. Mit Hilfe des extrem niedrigen Stromverbrauches kann der Funkempfänger ständig empfangsbereit sein. Er wird zum Hauptempfänger mit dem hohen Stromverbrauch zugeschaltet, so dass nur nach Aufforderung der Hauptempfänger aktiv sein wird. Dieser Empfänger wird Wake-up Empfänger (WuRx) genannt. Seine wesentliche Aufgabe besteht darin, als einziger Teil des Gesamtknotens aktiv zu sein, während der Rest in den Modus mit dem niedrigsten Stromverbrauch versetzt wird. Sobald ein Anforderungssignal empfangen wird, weckt er den Haupt-Prozessor und andere Peripheriegeräte über eine eingehende Kommunikation. Somit ist der Aufweckempfänger essenziell für die Zuverlässigkeit der drahtlosen Kommunikation. Sein Stromverbrauch sollte im µA Bereich sein. Seine Empfangsbereitschaft hängt entscheidend von seiner Empfindlichkeit sowie Bitrate ab. Eine Verbesserung der Empfindlichkeit und Erhöhung der Bitrate würden zwangsläufig zu einer Erhöhung des Stromverbrauches führen. Im Rahmen dieser Doktorarbeit werden unterschiedliche Architekturen von Aufweckempfängern untersucht und umgesetzt. Zusammenhänge zwischen Empfindlichkeit, Bitrate und Stromverbrauch wurden analysiert und mögliche Grenzen gezeigt. Ein wesentliches Augenmerk war dabei, Off-the-Shelf Komponenten zu verwenden. Im Rahmen dieser Doktorabeit wurden in Abhängigkeit von der zu erreichenden Reichweite und Häufigkeit der Kommunikation zwei wesentliche Architekturen mit geeigneten Empfindlichkeiten und extrem geringem Stromverbrauch entwickelt. Für kurze Reichweiten wurde eine passive Hochfrequenzarchitektur (PRF Architektur) basierend auf einer passiven Erkennung von OOK-modulierten (On-Off-Keying) Signalen mittels Hüllkurvenbildung entwickelt. Die erreichte Empfindlichkeit von ca. -64 dBm stellt eine wesentliche Verbesserung gegenüber dem Stand der Technik und Forschung mit einer Empfindlichkeit von ca. -52 dBm dar. Die Empfindlichkeit kann in Bezug auf verschiedene Parameter variieren, einschließlich des insgesamt erzeugten Rauschens, der Schaltungstechnologie und der Topologie. Zwei Varianten der PRF WuRxs wurden realisiert, wobei der Basisbandverstärker die Hauptänderung darstellt. Die erste Version verwendet einen Hochleistungsverstärker mit reduziertem durchschnittlichen Energieverbrauch dank einer neuartigen Leistungssteuerung. Die zweite Variante konzentriert sich auf die Verwendung eines Basisbandverstärkers mit extrem geringer Leistung, da erwartet wird, dass er sich in einem kontinuierlichen aktiven Zustand befindet. Diese Arbeit bringt auch die notwendige Analyse des passiven Front-Ends mit der Absicht, die allgemeine WuRx-Empfindlichkeit zu verbessern. Nachweise der Wirksamkeit sind in Sensorknotenmodulen eingebettet und verfügen über -61 dBm und -64 dBm Empfindlichkeit für die erste bzw. die zweite Variante bei einer Paketfehlerrate (PER) von 1 %, während beim Abhören von Paketen eine ähnliche Leistung von 7.2 µW gefordert wird. Während der Paketdecodierung erfordert die erste Variante eine Leistung von 150 µW, die stark durch den Basisbandverstärker verursacht wird. Die erreichte Latenz beträgt weniger als 30 ms und die Bitrate beträgt 4 kbit/s mit einer Manchester-Codierung. Für Anwendungen mit großer Reichweite wird ein WuRx mit höherer Empfindlichkeit vorgeschlagen. Dieser basiert auf einer TunedRF (TRF) -Architektur. Dabei werden sehr schwache Funksignale durch einen rauscharmen Verstärker (LNA) erkannt und verstärkt. Der WuRx erreicht eine bessere Empfindlichkeit von ca. –90 dBm. Dabei wurde das Augenmerk auf die höchste Verstärkung verbunden mit dem niedrigsten Vorspannungsstrom gelegt. Der LNA wird dann im nicht-linearen Bereich betrieben. Dieser Betriebsmodus beeinflusst nur im geringeren Maße die Signalintegrität der OOK-modulierten Signale. Der gesamte Leistungsverbrauch des TRF WuRx beträgt 1.38 mW. Um den Gesamtleistungsverbrauch im µW Bereich zu reduzieren, wird im Rahmen dieser Arbeit das sogenannte Power-Gating-Protokoll eingeführt. Dabei wird das Funkkanal zyklisch abgetastet. Der WuRx kann innerhalb von wenigen Mikrosekunden das Vorhandensein eines Pakets erkennen und direkt nach der Paketdecodierung in den Ruhezustand zurückkehren. Durch diesen Ansatz konnte der durchschnittliche Stromverbrauch bei einer Paketerkennungslatenz von ca. 32 ms innerhalb einer Abtastrate von 2 s auf 2.8 µW reduziert werden. Die vorgeschlagenen Lösungen können eine Mindestlänge von 16-Bit-Mustern decodieren und im lizenzfreien ISM-Band 868 MHz arbeiten.:1 Introduction 1.1 Motivation 1.2 Wake-up Receiver Design Requirements 1.2.1 Energy Consumption 1.2.2 Network Coverage and Robustness 1.2.3 Wake-up Packet Addressing 1.2.4 WuPt Detection Latency 1.2.5 Hosting System, Form-factor and Fabrication Technology 1.3 Thesis Organisation 2 Wireless Sensor Networks 2.1 Radio Communication 2.1.1 Electromagnetic Spectrum 2.1.2 Link Budget Analysis 2.2 Asynchronous Radio Receiver Duty-cycle Control 2.2.1 B-MAC and X-MAC Protocols 2.2.2 Energy and Latency Analysis 2.3 Power Supply Requirements 2.3.1 Low Self-discharge Battery 2.3.2 Energy Harvester 2.4 Summary 3 State-of-the-Art of Wake-up Receivers 3.1 Wake-up Receiver Architectural Analysis 3.1.1 Passive RF Detector 3.1.2 Classical Radio Architectures 3.2 Wake-up Receiver Back-end Stages 3.2.1 Baseband Amplifiers 3.2.2 Analog to Digital Conversion 3.2.3 Wake-up Packet Decoder 3.3 Power Consumption Reduction at Circuit Level 3.3.1 Power Gating 3.3.2 Interference Rejection and Filtering 3.4 Summary 4 Proposal of Novel Wake-up Receivers 4.1 Ultra-low Power On-demand Communication in Wireless Sensor Networks: Challenges and Requirements 4.2 Passive RF Wake-up Receiver 4.3 Power-gated Tuned-RF Wake-up Receiver 5 Low-power RF Front-end 5.1 Narrow-band Low-noise Amplifier (LNA) 5.1.1 Topology 5.1.2 Voltage Gain 5.1.3 Stability 5.1.4 Noise Figure 5.1.5 Linearity 5.2 Envelope Detector 5.2.1 Theory of Square-law Detection and Sensitivity Analysis 5.2.2 Single-Diode Envelope Detector 5.2.3 Voltage Multiplier Envelope Detector 5.3 Hardware Assessment 5.3.1 LNA 5.3.2 Envelope Detector 5.4 Summary 6 Passive RF Wake-up Receiver 6.1 Circuit Implementation 6.1.1 Address Decoder 6.1.2 Envelope Detector 6.1.3 Power-gated Baseband Amplifier 6.1.4 Ultra Low-power Baseband Amplifier 6.2 Experimental Results 6.2.1 Wireless Sensor Node 6.2.2 Measurements 6.3 Summary 7 Power-gated Tuned-RF Wake-up Receiver 7.1 Power-gating Protocol 7.2 Circuit Design 7.2.1 Radio Front-end 7.2.2 Data Slicer 7.2.3 Digital Baseband 7.3 Performance Evaluation 7.4 Summary 8 Conclusion 8.1 Performance Summary 8.2 Future Perspective 8.3 Applications A Two-tone Simulation Setup B Diode Models and Simulation Setup C Preamble Detection C Code Implementation Bibliography Publications

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

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

Nas últimas décadas, as enchentes vêm causando muitos problemas nas cidades, principalmente em grandes centros urbanos devido à alteração da paisagem natural e à impermeabilização do terreno. Geralmente esses eventos estão relacionados a eventos extremos de chuva, junto a um insuficiente sistema de drenagem para dar vazão ao escoamento gerado. Um ponto agravante - que colabora com o aumento da magnitude das enchentes - é o crescimento populacional desordenado. Assim, faltam políticas públicas, como um estudo prévio da região para alocação de pessoas de maneira eficiente. Na literatura, existem algumas soluções, como o uso da tecnologia de Redes de Sensores Sem Fio (RSSF), que podem ser implantadas no cenário urbano como forma de monitoramento de enchentes. Nesse cenário, um dos principais desafios para elaboração desses sistemas é emitir alertas para que desastres maiores sejam evitados. Porém, a utilização de uma única fonte de dados, unida a possíveis falhas que as RSSFs podem sofrer, acaba comprometendo o monitoramento e o alerta de enchentes. Uma outra abordagem é a utilização de modelos hidrológicos criados a partir de um estudos prévios do solo e da estrutura da bacia, pois eles são capazes de reproduzir o comportamento do escoamento da bacia a partir de séries temporais como entrada. Existem muitos modelos hidrológicos com diversas estruturas de dados e detalhamento da bacia hidrográfica, dos mais complexos - capazes de reproduzir a física dos processos de infiltração e o escoamento de água - até os mais simplificados, que utilizam parâmetros de ajustes que não são necessariamente relacionados aos fenômenos físicos envolvidos nesses processos. Porém, muitos desses modelos precisam de uma grande quantidade de dados para o seu desenvolvimento, tornando-os muito complexos e custosos. Dessa forma, esta dissertação de mestrado apresenta um modelo de identificação de enchentes baseado na mineração de dados e aprendizado de máquina, com o intuito de diminuir a complexidade e o custo dos modelos hidrológicos e a dependabilidade de uma única variável de sistemas de RSSF, além da vantagem de ser facilmente generalizável sem perder a eficiência na identificação de enchente. As variáveis utilizadas para o desenvolvimento do modelo são os dados de estações meteorológicas e o nível de água do canal. Assim, é utilizada a metodologia do Cross Industry Standard Process for Data Mining (CRISP-DM) para a mineração dos dados, por ser uma técnica objetiva que contém as melhores práticas para a exploração dos dados. Os resultados revelam que o modelo desenvolvido obteve uma acurácia de aproximadamente 87:8%, com o algoritmo Random_Forest. Além disso, nos testes de adaptabilidade e comparação com o Storm Water Management Model (SWMM)-um modelo hidrológico amplamente conhecido na literatura-, em uma mesma região de estudo, o modelo desenvolvido obteve resultados relevantes no contexto de identificação de enchente. Isso mostra que o modelo desenvolvido possui grande potencial de aplicação, principalmente por sua simplicidade de implementação e replicação sem comprometer a qualidade de identificação da ocorrência de enchentes. Consequentemente, algumas das principais contribuições deste trabalho são: (i) o modelo multivariável de identificação de enchente diminui a complexidade, custos e tempo de desenvolvimento em relação aos modelos hidrológicos e; (ii) o avanço do estado da arte em comparação aos trabalhos computacionais, por não depender de variáveis fixas e utilizar multivariáveis para identificar o padrão de enchentes. / In recent decades, floods have caused many problems in cities, especially in large urban centers due to the alteration of the natural landscape and the waterproofing of the terrain. Generally, these events are related to extreme rainfall events, together with an insufficient drainage system to give flow to the flow generated. An aggravating point - which contributes to the increase in flood magnitude - is disordered population growth. Thus, public policies are lacking, such as a prior study of the region for the efficient allocation of people. In the literature, there are some solutions, such as the use of the Wireless Sensor Networks (WSN) technology, which can be implemented in the urban scene as a form of flood monitoring. In this scenario, one of the major challenges in designing these systems is to issue alerts so that major disasters are avoided. However, the use of a single data source, coupled with the possible flaws that WSNs may suffer, endangers flood monitoring and alertness. Another approach is the use of hydrological models created from previous soil studies and basin structure, as they are able to reproduce basin flow behavior from time series as input. There are many hydrological models with diverse data structures and details of the hydrographic basin, of the most complex - capable of reproducing the physics of the infiltration processes and the water flow - to the more simplified, that use parameters of adjustments that are not necessarily related to the phenomena involved in these processes. However, many of these models need a lot of data for their development, making them very complex and costly. This dissertation presents a flood identification model based on data mining and machine learning in order to reduce the complexity and cost of hydrological models and the dependability of a single variable of WSN systems. of the advantage of being easily generalizable without losing efficiency in the identification of flood. The variables used for the development of the model are the data of meteorological stations and the water level of the channel. Thus, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology for data mining is used, since it is an objective technique that contains the best practices for data mining. The results show that the developed model obtained an accuracy of approximately 87.8%, with the algorithm Random_Forest. In addition, in the adaptive and comparative tests with the Storm Water Management Model (SWMM), a hydrological model widely known in the literature, in the same region of study, the developed model obtained relevant results in the context of flood identification. This shows that the developed model has great application potential, mainly for its simplicity of implementation and replication without compromising the quality of the identification of the occurrence of floods. Consequently, some of the main contributions of this work are: (i) the multivariate model of flood identification decreases the complexity, costs and development time in relation to the hydrological models; (ii) the advance of the state of the art in comparison to the computational works, because it does not depend on fixed variables and use multivariable to identify the flood pattern.