Anledningen till studien är för att avgöra om det svenska lantbruket är en lämplig sektor för att implementera LPWAN-enheter (datasändande lågenergienheter) på. Det anses intressant att veta om det finns ett behov för denna teknik på det nya området. Syftet med arbetet är hitta nya områden inom lantbruk som kan effektiviseras och göras mer hållbart med hjälp av IoT. Syftet är att göra en jämförelse på lantbruk för och efter implementering. Arbetet ska gå till grunden för verkliga behov där IoT kan fungera som en hjälpande hand samt utvärdera vilka områden inom svenskt lantbruk som har störst innovationspotential, på vilka sätt IoT-enheter kan göra svenskt lantbruk mer hållbart samt hur svenska lantbrukare vill att arbetslivet i en uppkopplad miljö ska vara uppbyggd. Att genom besök, intervjuer, en enkät samt idégenerering skapa en klar bild på vilka områden som är mest av behov av detta. Arbetet grundar sig på aktionsforskning och design thinking. Arbetet kommer även eftersöka likande forskning och utveckling inom området för att skapa en bild vad som håller på att hända inom sektorn. Förutom detta behöver sensorer testas i verklig miljö för att avgöra skillnader och möjliga nya innovativa arbetsprocesser. Ett test har gjorts där ett nuvarande arbetssätt av att mäta temperaturer testats mot tekniken. Både lantbrukare, forskare samt personer som arbetar inom branschen har blivit kontaktade för att ge sin syn på området. Resultatet visar att det det finns stor innovationspotential inom området och att stora förändringar kan göras genom implementering av IoT. Bevisen för att dessa enheter kommer att påverka ur ett hållbarhetsperspektiv har dock inte varit lika framhävande. Resultatet visar även att arbetssättet för framtida lantbrukare kan komma att förändras genom att manuella kontroller nu kan ske på distans samt att klimatmätningar nära gården med hjälp av de fokuserade IoT-enheterna både är mer noggranna och mer uppskattade av lantbrukaren. Tekniken är behövd inom området och mer forskning och utveckling borde göras inom området. Enheterna som ska användas borde utvecklas efter lantbrukarnas behov och kan därmed skilja sig markant på grund av att behoven är olika.

Background. The rapid growth of IoT devices in homes put people at risk of cyberattacks and the low power and computing capabilities in IoT devices make it difficultto design a security solution for them. One method of preventing cyber attacks isan Intrusion Detection System (IDS) that can identify incoming attacks so that anappropriate action can be taken. Previous attempts have been made using machinelearning and deep learning however these attempts have struggled at detecting newattacks.Objectives. In this work we use a convolutional neural network IoTNet designed forIoT devices to classify network attacks. In order to evaluate the use of deep learningin intrusion detection systems on IoT.Methods. The neural network was trained on the NF-UNSW-NB15-v2 datasetwhich contains 9 different types of attacks. We used a method that transformedthe network flow data into RGB images which were fed to the neural network forclassification. We compared IoTNet to a basic convolutional neural network as abaseline.Results. The results show that IoTNet did not perform better at classifying networkattacks when compared to a basic convolutional neural network. It also showed thatboth network had low precision for most classes.Conclusions. We found that IoTNet is unfit to be used as an intrusion detectionsystem in the general case and that further research must be done in order to improvethe precision of the neural network.

A suitable environment for the growth of plants is the Greenhouse, that needs to be monitored by a continuous collection of data related to temperature, carbon dioxide concentration, humidity, illumination intensity using sensors, preferably in a wireless sensor network (WSN). Demand initiates various challenges for diversified applications of WSN in the field of IoT (Internet of Things). Network design in IoT based WSN faces challenges like limited energy capacity, hardware resources, and unreliable environment. Issues like cost and complexity can be limited by using sensors that are heterogeneous in nature. Since replacing or recharging of nodes in action is not possible, heterogeneity in terms of energy can overcome crucial issues like energy and lifetime. In this paper, an energy efficient routing process is discussed that considers three different sensor node categories namely normal, intermediate and advanced nodes. Also, the basic cluster head (CH) selection threshold value is modified considering important parameters like initial and residual energy with an optimum number of CHs in the network. When compared with routing algorithms like LEACH (Low Energy Adaptive Clustering Hierarchy) and SEP (Stable Election Protocol), the proposed model performs better for metrics like throughput, network stability and network lifetime for various scenarios.

Internet of Things (IoT) is on the verge of experiencing a paradigm shift, the focus of which is the integration of people, services, context information, and things in the Connected Society, thus enabling Internet of Everything (IoE). Hundreds of billions of things will be connected to IoT/IoE by 2020. This massive immersion of things paves the way for sensing and analysing anything, anytime and anywhere. This everywhere computing coupled with Internet or web-enabled services have allowed access to a vast amount of distributed context information from heterogeneous sources. This enormous amount of context information will remain under-utilized if not properly managed. Therefore, this thesis proposes a new approach of logical-clustering as opposed to physical clustering aimed at enabling efficient context information management. However, applying this new approach requires many research challenges to be met. By adhering to a design science research method, this thesis addresses these challenges and proposes solutions to them. The thesis first outlines the architecture for realizing logical-clustering topology for which a two-tier hierarchical-distributed hash table (DHT) based system architecture and a Software Defined Networking (SDN)-like approach are utilized whereby the clustering identifications are managed on the top-level overlay (as context storage) and heterogeneous context information sources are controlled via the bottom level. The feasibility of the architecture has been proven with an ns-3 simulation tool. The next challenge is to enable scalable clustering identification dissemination, for which a distributed Publish/Subscribe (PubSub) model is developed. The massive number of immersed nodes further necessitates a dynamic self-organized system. The thesis concludes by proposing new algorithms with regard to autonomic management of IoT to bring about the self-organization. These algorithms enable to structure the logical-clustering topology in an organized way with minimal intervention from outside sources and further ensure that it evolves correctly. A distributed IoT context information-sharing platform, MediaSense, is employed and extended to prove the feasibility of the dynamic PubSub model and the correctness of self-organized algorithms and to utilize them as context storage. Promising results have provided a high number of PubSub messages per second and fast subscription matching. Self-organization further enabled logical-clustering to evolve correctly and provided results on a par with the existing MediaSense for entity joining and high discovery rates for non-concurrent entity joining. The increase in context information requires its proper management. Being able to cluster (i.e. filter) heterogeneous context information based on context similarity can help to avoid under-utilization of resources. This thesis presents an accumulation of work which can be comprehended as a step towards realizing the vision of logical-clustering topology.

The Internet of Things (IoT) is now permeating our daily lives, providing critical data for every decision. IoT architecture consists of multiple layers with unique functions and independent components. Each layer of IoT architecture requires different power sources and power delivery schemes. Therefore, different types of power management architectures are required for individual IoT components. Fortunately, advances in metal oxide semiconductor (MOS) technology have made it possible to implement a variety of high-performance power management architectures. These power management architectures should not only create the power rails required for IoT components but also serve additional functions depending on the application. The power management architecture of IoT devices needs to support sub-mW- or mW-scale power consumption. In addition, the power management architecture should be either fully integrated on a chip or miniaturized with few passive components to minimize the size of IoT devices. Building-scale data centers, on the other hand, need various power conversion stages. In this scenario, power conversion from an intermediate DC bus to many point of loads (PoL) requires a high conversion ratio DC-DC converter. Because each PoL draws enormous amounts of power, the power management architecture should withstand high currents and include protection circuitry to prevent damage. This thesis presents research on the design of power management architectures required by IoT devices and data centers. Chapter 2 presents the design and circuit techniques of power management architectures for IoT devices. Chapter 2 outlines a new methodology for co-designing an integrated switched-capacitor (SC) DC-DC converter and a load circuit in ultra-low-power IoT devices. This methodology enables the implementation of an area-efficient fully integrated IoT system-on-chip (SoC) while maintaining high power conversion efficiency (PCE). Chapter 3 presents a 10-output ultra-low-power single-inductor-multiple-output (SIMO) DC-DC buck converter with integrated output capacitors for sub-mW IoT SoCs. Featuring a continuous comparator-based output switch controller and a digital pulse-width modulation (PWM) controller for ultra-low feedback latency, this SIMO converter produces ten independent output voltages with high PCE. Lastly, in Chapter 4, an integrated programmable gate timing control and gate driver chip for an active-clamp forward converter (ACFC) Power Block for data center applications is developed. While the ACFC Power Block converts 12-48 V intermediate DC bus voltage to a digital PoL voltage, the gate timing control and driver chip can optimize PCE and reduce the system form factor.

, / El presente trabajo ofrece una propuesta de solución tecnológica al problema asociado a la violencia contra la mujer en el Perú. El proyecto realizo un diagnóstico del tiempo promedio de atención, en base a un estudio, de los principales canales de prevención y denuncia existentes. Del estudio realizado se pudo determinar que existen elevados tiempos de atención y asimetrías de información entre los diferentes actores del sistema de prevención y protección a la mujer. La solución propuesta, propone reducir al tiempo mínimo necesario para la atención y detención de un acto de violencia hacia la mujer brindando una reacción inmediata al evento. Complementando el proceso de proceso del proyecto hemos usamos componentes electrónicos de bajo costo y sistemas acordes y existentes en el mercado actual. La solución agrupa componentes tecnológicos propiamente configurados tanto en hardware como en software para realizar el seguimiento de la violencia, el cual se compone principalmente de la siguiente configuración: 1) Un dispositivo ‘wearable’, alertando a un grupo determinado de personas previamente agregadas, familiares, conocidos o personas dispuestas a ayudar, 2) Un sistema de comunicación, la alerta en tiempo real la cual que por medio de señales a una plataforma Cloud son distribuidos a una aplicación móvil y pagina web. La solución fue validada en un CEM ubicada en una comisaría de la policía nacional en la provincia del Callao, Distrito de Ventanilla. El proyecto busca contribuir con la disminución del tiempo de respuesta de ayuda a las mujeres víctimas y la asimetría de información en las organizaciones públicas que se ven involucradas. / This work offers a proposal for a technological solution to the problem associated with violence against women in Peru. The project made a diagnosis of the average attention time, based on a study, of the main existing prevention and reporting channels. From the study carried out, it was possible to determine that there are high attention times and information asymmetries between the different actors in the prevention and protection system for women. The proposed solution proposes to reduce to the minimum time necessary for the attention and arrest of an act of violence against women, providing an immediate reaction to the event. Complementing the process of the project process we have used low-cost electronic components and systems that are consistent and existing in the current market. The solution groups properly configured technological components in both hardware and software to track violence, which mainly consists of the following configuration: 1) A 'wearable' device, alerting a specific group of previously added people, family members , acquaintances or people willing to help, 2) A communication system, the alert in real time which through signals to a Cloud platform are distributed to a mobile application and website. The solution was validated at a CEM located in a national police station in the Callao province, Ventanilla District. The project seeks to contribute to reducing the response time to help women victims and the asymmetry of information in the public organizations that are involved. / Tesis

Indiana University-Purdue University Indianapolis (IUPUI) / The Internet of Things (IoT) is a natural evolution of the Internet and is becoming more and more ubiquitous in our everyday home, enterprise, healthcare, education, and many other aspects. The data gathered and processed by IoT networks might be sensitive and that calls for feasible and adequate security measures. The work in this thesis describes the use of the Wi-Fi technology in the IoT connectivity, then proposes a new approach, the Proactive Wireless Protected Access (PWPA), to protect the access networks. Then a new end to end (e2e) IoT security model is suggested to include the PWPA scheme. To evaluate the solutions security and performance, rstly, the cybersecurity triad: con dentiality, integrity, and availability aspects were discussed, secondly, the solutions performance was compared to a counterpart e2e security solution, the Secure Socket Layer security. A small e2e IoT network was set up to simulate a real environment that uses HTTP protocol. Packets were then collected and analyzed. Data analysis showed a bandwidth e ciency increase by 2% (Internet links) and 12% (access network), and by 344% (Internet links) and 373% (access network) when using persistent and non-persistent HTTP respectively. On the other hand, the analysis showed a reduction in the average request-response delay of 25% and 53% when using persistent and non-persistent HTTP respectively. This scheme is possibly a simple and feasible solution that improves the IoT network security performance by reducing the redundancy in the TCP/IP layers security implementation.

The Industrial Internet of Things (IIoT) plays a critical role in modern industrial systems, contributing to increased efficiency, productivity, and innovation. However,its rapid evolution and the complexity of devices pose significant challenges to digital forensics readiness (DFR). This thesis aims to provide a set of guidelines forimplementing DFR within IIoT environments, addressing challenges such as datacollection and logging, device and data identification, verification, security, analysis,and reporting. The framework was developed through rigorous research processesand guided by expert interviews and a final survey, adhering to design science principles. Although the study’s outcomes are subject to some limitations, such as a smallnumber of experts for evaluation, the research contributes to a significant gap in theexisting literature by providing a robust, adaptable, and comprehensive guide to DFRin IIoT. Offering a foundation for future research to build upon, enhance DFR, andaddressing emerging IIoT technologies and scenarios.

A rising level of industrialization and advances in Industry 4.0 have resulted in Industrial Internet of Things (IIoT) gaining immense significance in today’s industrial automation systems. IIoT promises to achieve improved productivity, reliability, and revenues by connecting time-constrained embedded systems to “the Internet”. New opportunities bring with them challenges, and in particular for industrial networks, massively interconnected IIoT devices communicating in real-time,  require synchronized operation of devices for the ordering of information collected throughout a  network. Thus,   a   time or clock synchronization service that aligns the devices’ clocks in the network to ensure accurate timestamping and orderly event executions, has gained great importance. Achieving adequate clock synchronization in the industrial domain is challenging due to heterogeneous communication networks and exposure to harsh environmental conditions bringing interference to the communication networks. The investigative study based on existing literature and the envisioned architecture of the future industrial automation system unveils that the key requirements for future industrial networks are to have a cost-effective, accurate, scalable, secured, easy to deploy and maintain clock synchronization solution. Today’s industrial automation systems employ clock synchronization solutions from a wide plethora of hardware and software based solutions. The most economical, highly scalable, maintainable software-based clock synchronization means are best candidates for the identified future requirements as their lack in accuracy compared to hardware solutions could be compensated by predictive software strategies.  Thus, the thesis’s overall goal is to enhance the accuracy of software-based clock synchronization in heterogeneous industrial networks using predictable software strategies. The first step towards developing an accurate clock synchronization for heterogeneous industrial networks with real-time requirements is to investigate communication parameters affecting time synchronization accuracy. Towards this goal, we investigated actual industrial network data for packet delay profiles and their impact on clock synchronization performance.  We further analyzed wired and wireless local area networks to identify key network parameters for clock synchronization and proposed an enhanced clock synchronization algorithm CoSiNeT for field IoT devices in industrial networks. CoSiNeT matches well with state-of-the-practice SNTP and state-of-the-art method SPoT in good network conditions in terms of accuracy and precision;  however,  it outperforms them in scenarios with degrading network conditions.

The Internet of Things is expanding, and with the increasing numbers of connected devices,exploitation of those devices also becomes more common. Since IoT devices and IoT networksare used in many crucial areas in modern societies, ranging from everything between securityand militrary applications to healthcare monitoring and production efficiency, the need to securethese devices is of great importance for researchers and businesses. This project explores howan intrusion detection system called DETONAR can be used on border router logs, instead of itsoriginal use of sniffer devices. Using DETONAR in this way allows us to detect many differentattacks, without contributing to the additional cost of deploying sniffer devices and the additionalrisk of the sniffer devices themselves becoming the target of attack