On the impact of mobility on battery-less RF energy harvesting system performance

The future of Internet of Things (IoT) envisions billions of sensors integrated with the physical environment. At the same time, recharging and replacing batteries on this infrastructure could result not only in high maintenance costs, but also large amounts of toxic waste due to the need to dispose of old batteries. Recently, battery-free sensor platforms have been developed that use supercapacitors as energy storage, promising maintenance-free and perpetual sensor operation. While prior work focused on supercapacitor characterization, modelling and supercapacitor-aware scheduling, the impact of mobility on capacitor charging and overall sensor application performance has been largely ignored. We show that supercapacitor size is critical for mobile system performance and that selecting an optimal value is not trivial: small capacitors charge quickly and enable the node to operate in low energy environments, but cannot support intensive tasks such as communication or reprogramming; increasing the capacitor size, on the other hand, enables the support for energy-intensive tasks, but may prevent the node from booting at all if the node navigates in a low energy area. The paper investigates this problem and proposes a hybrid storage solution that uses an adaptive learning algorithm to predict the amount of available ambient energy and dynamically switch between two capacitors depending on the environment. The evaluation based on extensive simulations and prototype measurements showed up to 40% and 80% improvement compared to a fixed-capacitor approach in terms of the amount of harvested energy and sensor coverage

Overlay virtualized wireless sensor networks for application in industrial internet of things : a review

Abstract: In recent times, Wireless Sensor Networks (WSNs) are broadly applied in the Industrial Internet of Things (IIoT) in order to enhance the productivity and efficiency of existing and prospective manufacturing industries. In particular, an area of interest that concerns the use of WSNs in IIoT is the concept of sensor network virtualization and overlay networks. Both network virtualization and overlay networks are considered contemporary because they provide the capacity to create services and applications at the edge of existing virtual networks without changing the underlying infrastructure. This capability makes both network virtualization and overlay network services highly beneficial, particularly for the dynamic needs of IIoT based applications such as in smart industry applications, smart city, and smart home applications. Consequently, the study of both WSN virtualization and overlay networks has become highly patronized in the literature, leading to the growth and maturity of the research area. In line with this growth, this paper provides a review of the development made thus far concerning virtualized sensor networks, with emphasis on the application of overlay networks in IIoT. Principally, the process of virtualization in WSN is discussed along with its importance in IIoT applications. Different challenges in WSN are also presented along with possible solutions given by the use of virtualized WSNs. Further details are also presented concerning the use of overlay networks as the next step to supporting virtualization in shared sensor networks. Our discussion closes with an exposition of the existing challenges in the use of virtualized WSN for IIoT applications. In general, because overlay networks will be contributory to the future development and advancement of smart industrial and smart city applications, this review may be considered by researchers as a reference point for those particularly interested in the study of this growing field

DisKnow: a social-driven disaster support knowledge extraction system

This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings.info:eu-repo/semantics/publishedVersio

Energy harvesting towards self-powered iot devices

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role is played by power management integrated circuits (PMICs), which help to enhance the system's life span. Moreover, PMICs from different manufacturers that provide power management to IoT devices have been discussed in this paper. Furthermore, the energy harvesting networks can expose themselves to prominent security issues putting the secrecy of the system to risk. These possible attacks are also discussed in this review article

Collaborative Networking: The Integration of Collaborative Communication into WSN-routing

According to the Collaborative Communication (CC) techniques, a group of sensor nodes modify their carrier phases, so that their signals are received by the destination synchronously to gain higher level of reliability and flexibility. In this research, CC is fused into networking approaches to extend its scalability as well

Keilanohjaukseen soveltuvan litteän dielektrisen linssiantennin suunnittelu ja mittaus

In this thesis, flat hemi-elliptic dielectric lens antennas are studied at millimeter wavelengths. The used lens materials are teflon and a commercial plastic called preperm450, developed specifically for high frequency antenna applications. The main focus of this work is in the beam steering properties of the antennas. Proposed antenna structure is suitable for, e.g., automotive radar applications. Two different lens configurations are studied, one based on a dielectric slab waveguide and another based on a parallel plate waveguide. The design process for both antenna types is presented in detail and the antenna structures are simulated using commercial simulation software. Both antennas are fed with a WR-10 waveguide. Four prototype antennas (one of each type, and of both materials) are manufactured using water jet cutting. Manufactured antennas are measured using a planar near-field scanner and the results are compared with the simulated results. In the measurements and simulations beam steering is realized by changing the positioning of the waveguide feed. The measurement results follow the simulation results to a large extent and confirm the suitability of the proposed antenna structure for beam steering applications at millimeter wavelengths. The low relative permittivity of teflon lenses limits the maximum beam steering angle, especially with the dielectric slab extended lens. Preperm450 proves to be a viable option when choosing materials for dielectric lenses and beam steering angles up to 15 degrees can be achieved with small feed offsets.Teknologian nopea kehittyminen on mahdollistanut millimetriaaltoalueen käyttöönoton mm. tiedonsiirrossa ja tutkasovelluksissa, mikä on myös kasvattanut mielenkiintoa dielektrisiä linssiantenneja kohtaan. Millimetriaaltoalueella linssiantennien fyysiset mitat ovat pieniä, mikä mahdollistaa niiden käytön myös liikuteltavissa sovelluksissa. Tässä diplomityössä tutkitaan litteitä dielektrisiä linssiantenneja Etaajuuskaistan(71 – 86 GHz) sovelluksiin. Tutkimuksen suurin mielenkiinnon kohde on antennien keilanohjausominaisuudet, joita tutkitaan syöttöpistettä muuttamalla. Litteä linssiantenni tarjoaa viuhkamaisen keilan, jota keilaamalla voidaan kattaa laajoja alueita. Tämä mahdollistaa tutkitun antennityypin käytön esimerkiksi autotutkissa. Työssä käsitellään kahdenlaisia antennikonfiguraatioita. Ensimmäinen koostuu linssistä, syöttöantennista ja tukirakenteista, kun taas jälkimmäisessä linssi on suljettu kahden metallilevyn väliin. Käytetyt linssimateriaalit ovat teflon ja preperm450, joka on varta vasten korkean taajuuden antennisovelluksiin suunniteltu kaupallinen muovimateriaali. Linssien suunnitteluprosessi on kuvailtu yksityiskohtaisesti ja fyysiset mitat optimoitiin tietokoneohjelmiston avulla. Suunnitelluista antenneista valmistettiin neljä erilaista antenniprototyyppiä, jotka mitattiin lähikenttäskannerin avulla. Mittaustulosten ja tietokonesimulaatioiden vertailu osoittaa, että antenniprototyyppien mitattu toiminta mukailee hyvin simuloitujen linssien toimintaa. Teflonlinsseillä keilanohjausta rajoittaa matala suhteellinen permittiivisyys, mutta preperm450 osoittautuu hyvin soveltuvaksi dielektristen linssien valmistusmateriaaliksi

A Platform for Indoor Localisation, Mapping, and Data Collection using an Autonomous Vehicle

Everyone who has worked with research knows how rewarding experimenting and developing new algorithms can be. However in some cases, the hard part is not the invention of these algorithms, but their evaluation. To try and make that evaluation easier, this thesis focuses on the collection of data that can be used as positional ground truths using an autonomous measurement platform. This should assist Combain Mobile AB in the evaluation and improvement of their Wi-Fi based indoor positioning service. How and which parts of the open-source community’s work in the Robot Operating System (ROS) project to utilise is not obvious. This thesis therefore sets out to build a Minimum Viable Product (MVP) which is capable of supporting two different use cases: measure and explore inside an unknown environment, and measure inside a known environment given a map. This effectively leaves Combain with a viable product, and indirectly helps the community by aiding it in comparing and recommending the best tools and software libraries for the task. The result of this thesis ends up recommending the following for measuring inside an unknown environment: the Simultaneous Localisation And Mapping (SLAM) algorithm Google Cartographer for navigation, and the exploration algorithm Hector Exploration for planning the exploration. To measure inside a known environment the following is recommended: the Adaptive Monte Carlo Localisation (AMCL) positioning algorithm and the Spanning Tree Covering algorithm.Data har många användningsområden inom både forskning och industri. I detta examensarbete skapades en platform som självgående kan användas för att samla in stora mängder data från omgivningen

New Secure IoT Architectures, Communication Protocols and User Interaction Technologies for Home Automation, Industrial and Smart Environments

Programa Oficial de Doutoramento en Tecnoloxías da Información e das Comunicacións en Redes Móbiles. 5029V01Tese por compendio de publicacións[Abstract] The Internet of Things (IoT) presents a communication network where heterogeneous physical devices such as vehicles, homes, urban infrastructures or industrial machinery are interconnected and share data. For these communications to be successful, it is necessary to integrate and embed electronic devices that allow for obtaining environmental information (sensors), for performing physical actuations (actuators) as well as for sending and receiving data (network interfaces). This integration of embedded systems poses several challenges. It is needed for these devices to present very low power consumption. In many cases IoT nodes are powered by batteries or constrained power supplies. Moreover, the great amount of devices needed in an IoT network makes power e ciency one of the major concerns of these deployments, due to the cost and environmental impact of the energy consumption. This need for low energy consumption is demanded by resource constrained devices, con icting with the second major concern of IoT: security and data privacy. There are critical urban and industrial systems, such as tra c management, water supply, maritime control, railway control or high risk industrial manufacturing systems such as oil re neries that will obtain great bene ts from IoT deployments, for which non-authorized access can posse severe risks for public safety. On the other hand, both these public systems and the ones deployed on private environments (homes, working places, malls) present a risk for the privacy and security of their users. These IoT deployments need advanced security mechanisms, both to prevent access to the devices and to protect the data exchanged by them. As a consequence, it is needed to improve two main aspects: energy e ciency of IoT devices and the use of lightweight security mechanisms that can be implemented by these resource constrained devices but at the same time guarantee a fair degree of security. The huge amount of data transmitted by this type of networks also presents another challenge. There are big data systems capable of processing large amounts of data, but with IoT the granularity and dispersion of the generated information presents a new scenario very di erent from the one existing nowadays. Forecasts anticipate that there will be a growth from the 15 billion installed devices in 2015 to more than 75 billion devices in 2025. Moreover, there will be much more services exploiting the data produced by these networks, meaning the resulting tra c will be even higher. The information must not only be processed in real time, but data mining processes will have to be performed to historical data. The main goal of this Ph.D. thesis is to analyze each one of the previously described challenges and to provide solutions that allow for an adequate adoption of IoT in Industrial, domestic and, in general, any scenario that can obtain any bene t from the interconnection and exibility that IoT brings.[Resumen] La internet de las cosas (IoT o Internet of Things) representa una red de intercomunicaciones en la que participan dispositivos físicos de toda índole, como vehículos, viviendas, electrodomésticos, infraestructuras urbanas o maquinaria y dispositivos industriales. Para que esta comunicación se pueda llevar a cabo es necesario integrar elementos electr onicos que permitan obtener informaci on del entorno (sensores), realizar acciones f sicas (actuadores) y enviar y recibir la informaci on necesaria (interfaces de comunicaciones de red). La integración y uso de estos sistemas electrónicos embebidos supone varios retos. Es necesario que dichos dispositivos presenten un consumo reducido. En muchos casos deberían ser alimentados por baterías o fuentes de alimentación limitadas. Además, la gran cantidad de dispositivos que involucra la IoT hace necesario que la e ciencia energética de los mismos sea una de las principales preocupaciones, por el coste e implicaciones medioambientales que supone el consumo de electricidad de los mismos. Esta necesidad de limitar el consumo provoca que dichos dispositivos tengan unas prestaciones muy limitadas, lo que entra en conflicto con la segunda mayor preocupación de la IoT: la seguridad y privacidad de los datos. Por un lado existen sistemas críticos urbanos e industriales, como puede ser la regulación del tráfi co, el control del suministro de agua, el control marítimo, el control ferroviario o los sistemas de producción industrial de alto riesgo, como refi nerías, que son claros candidatos a benefi ciarse de la IoT, pero cuyo acceso no autorizado supone graves problemas de seguridad ciudadana. Por otro lado, tanto estos sistemas de naturaleza publica, como los que se desplieguen en entornos privados (viviendas, entornos de trabajo o centros comerciales, entre otros) suponen un riesgo para la privacidad y también para la seguridad de los usuarios. Todo esto hace que sean necesarios mecanismos de seguridad avanzados, tanto de acceso a los dispositivos como de protección de los datos que estos intercambian. En consecuencia, es necesario avanzar en dos aspectos principales: la e ciencia energética de los dispositivos y el uso de mecanismos de seguridad e ficientes, tanto computacional como energéticamente, que permitan la implantación de la IoT sin comprometer la seguridad y la privacidad de los usuarios. Por otro lado, la ingente cantidad de información que estos sistemas puede llegar a producir presenta otros dos retos que deben ser afrontados. En primer lugar, el tratamiento y análisis de datos toma una nueva dimensión. Existen sistemas de big data capaces de procesar cantidades enormes de información, pero con la internet de las cosas la granularidad y dispersión de los datos plantean un escenario muy distinto al actual. La previsión es pasar de 15.000.000.000 de dispositivos instalados en 2015 a más de 75.000.000.000 en 2025. Además existirán multitud de servicios que harán un uso intensivo de estos dispositivos y de los datos que estos intercambian, por lo que el volumen de tráfico será todavía mayor. Asimismo, la información debe ser procesada tanto en tiempo real como a posteriori sobre históricos, lo que permite obtener información estadística muy relevante en diferentes entornos. El principal objetivo de la presente tesis doctoral es analizar cada uno de estos retos (e ciencia energética, seguridad, procesamiento de datos e interacción con el usuario) y plantear soluciones que permitan una correcta adopción de la internet de las cosas en ámbitos industriales, domésticos y en general en cualquier escenario que se pueda bene ciar de la interconexión y flexibilidad de acceso que proporciona el IoT.[Resumo] O internet das cousas (IoT ou Internet of Things) representa unha rede de intercomunicaci óns na que participan dispositivos físicos moi diversos, coma vehículos, vivendas, electrodomésticos, infraestruturas urbanas ou maquinaria e dispositivos industriais. Para que estas comunicacións se poidan levar a cabo é necesario integrar elementos electrónicos que permitan obter información da contorna (sensores), realizar accións físicas (actuadores) e enviar e recibir a información necesaria (interfaces de comunicacións de rede). A integración e uso destes sistemas electrónicos integrados supón varios retos. En primeiro lugar, é necesario que estes dispositivos teñan un consumo reducido. En moitos casos deberían ser alimentados por baterías ou fontes de alimentación limitadas. Ademais, a gran cantidade de dispositivos que se empregan na IoT fai necesario que a e ciencia enerxética dos mesmos sexa unha das principais preocupacións, polo custo e implicacións medioambientais que supón o consumo de electricidade dos mesmos. Esta necesidade de limitar o consumo provoca que estes dispositivos teñan unhas prestacións moi limitadas, o que entra en con ito coa segunda maior preocupación da IoT: a seguridade e privacidade dos datos. Por un lado existen sistemas críticos urbanos e industriais, como pode ser a regulación do tráfi co, o control de augas, o control marítimo, o control ferroviario ou os sistemas de produción industrial de alto risco, como refinerías, que son claros candidatos a obter benefi cios da IoT, pero cuxo acceso non autorizado supón graves problemas de seguridade cidadá. Por outra parte tanto estes sistemas de natureza pública como os que se despreguen en contornas privadas (vivendas, contornas de traballo ou centros comerciais entre outros) supoñen un risco para a privacidade e tamén para a seguridade dos usuarios. Todo isto fai que sexan necesarios mecanismos de seguridade avanzados, tanto de acceso aos dispositivos como de protección dos datos que estes intercambian. En consecuencia, é necesario avanzar en dous aspectos principais: a e ciencia enerxética dos dispositivos e o uso de mecanismos de seguridade re cientes, tanto computacional como enerxéticamente, que permitan o despregue da IoT sen comprometer a seguridade e a privacidade dos usuarios. Por outro lado, a inxente cantidade de información que estes sistemas poden chegar a xerar presenta outros retos que deben ser tratados. O tratamento e a análise de datos toma unha nova dimensión. Existen sistemas de big data capaces de procesar cantidades enormes de información, pero coa internet das cousas a granularidade e dispersión dos datos supón un escenario moi distinto ao actual. A previsión e pasar de 15.000.000.000 de dispositivos instalados no ano 2015 a m ais de 75.000.000.000 de dispositivos no ano 2025. Ademais existirían multitude de servizos que farían un uso intensivo destes dispositivos e dos datos que intercambian, polo que o volume de tráfico sería aínda maior. Do mesmo xeito a información debe ser procesada tanto en tempo real como posteriormente sobre históricos, o que permite obter información estatística moi relevante en diferentes contornas. O principal obxectivo da presente tese doutoral é analizar cada un destes retos (e ciencia enerxética, seguridade, procesamento de datos e interacción co usuario) e propor solucións que permitan unha correcta adopción da internet das cousas en ámbitos industriais, domésticos e en xeral en todo aquel escenario que se poda bene ciar da interconexión e flexibilidade de acceso que proporciona a IoT