This work comprises an approximation of the energy consumption of the transceiver circuit in a single board computer. Single board computers, such as the Raspberry Pi 4 Model B that is used here, are usually cheap and therefore more accessible. This method of estimation does not use any other hardware which gives it an advantage compared to many other methods that use expensive measurement equipment, but it unfortunately comes with certain trade-offs, like accuracy, to name one example. One area where this approximation method could be applied is for optimizing the energy efficiency of wireless sensor networks. The method can be divided into two main parts, firstly the transceiver’s active transmission and reception states are profiled and then a power model is chosen and adapted to suit the transceiver as well as possible. These two steps are then combined and results in an energy consumption approximation. The evaluation of the results showed that the estimations are reasonable according to the most relevant findings on measuring a similar transceiver circuit, but there are also limitations that brings uncertainty to the results. More relevant studies are needed to properly assess the method of estimation and some further improvements are suggested. / Olika typer av elektroniska enheter utgör idag en stor del av många människors vardag och samhället i stort. Mobiltelefoner, laptops och olika sensorer är bara några exempel på dessa enheter som fyller viktiga funktioner i både vardag och arbete. En stor del av dem använder ett protokoll som heter IEEE 802.11ac för att kommunicera och de bör gärna göra det så energi-effektivt som möjligt. Det här arbetet undersöker energikonsumtionen hos en transceiverkrets som använder det nämnda protokollet för att skicka och ta emot datapaket. Målet med arbetet är uppskatta energikonsumtionen så väl som möjligt, med hjälp av billig och lättillgänglig hårdvara. Av den anledningen används en enkortsdator för att göra uppskattningen, mer specifikt en Raspberry Pi 4 Model B (RPi). Eftersom energiåtgången för transceiverkretsen inte kan mätas direkt från strömmen som dras av datorn, måste mjukvara skrivas för att göra uppskattningen. På det sättet undviker man behovet av dyr mätutrustning, men man måste göra avkall på till exempel noggrannhet i utbyte. Ett område där metoden eventuellt kan appliceras är för att göra trådlösa sensornätverk mer energi-effektiva. Metoden som användes för energiuppskattningen kan delas upp i två huvuddelar, förutom litteraturstudien som gjordes för att få en djupare förståelse för ämnet. Först profilerades transceiverkretsens aktiva tillstånd för transmission (TX) och mottagning (RX), som ligger i fokus för det här arbetet. Till detta användes mjukvaran perf som är ett prestandaanalyseringsverktyg som finns tillgängligt för Linuxsystem. Med hjälp av perf fick man fram längden av varje TX och RX operation i millisekunder. Sedan valdes en passande kraftmodell som anpassades för att efterlikna egenskaperna i RPi datorns transceiver så noga som möjligt. Modellen gav två olika formler för att beräkna kraftåtgången för TX respektive RX, vilket sedan multiplicerades med tidsåtgången för varje operation för att få fram energikonsumtionen. Metoden testades genom att skicka och ta emot datapaket med en storlek på 256 byte, mäta tidsåtgången, och sist räkna ut hur mycket energi som gick åt för varje enskilt paket. Resultaten presenterades med olika grafer samt en rimlighetsanalys. Slutsatsen var att resultaten verkar rimliga utgående från de mest relevanta fynden som gjordes inom ramen för litteraturstudien, men även att fler relevanta studier och mätningar behövs för att kunna göra en bättre bedömning av metodens tillförlitlighet. Slutligen framfördes förslag på eventuella förbättringar av arbetet samt områden för vidareutveckling.

With the development of intelligent services and applications enabled by Artificial Intelligence (AI), the Internet of Things (IoT) is infiltrating many aspects of our everyday lives. The usability of phones and tablets is largely increasing as the primary computing device, since the powerful sensors allow these devices to have access to an unprecedented amount of data. However, there are risks and responsibilities to collect the data in a centralized location due to privacy issues. To overcome this challenge, Federated Learning (FL) allows users to collectively taking the benefits of shared models trained from this big data, without the need to centrally store it. In this research, we present and evaluate the implementation of federated learning on Raspberry Pi boards using the FedAvg method. In addition, the compression method such as quantization and sparsification was applied to the baseline implementation to improve communication efficiency. We accomplished the implementation by comparing the baseline implementation and the compressed Federated-Averaging (FedAvg) on Raspberry Pi boards in order to achieve the smallest cost and higher accuracy to fit IoT environment. / Med utvecklingen av intelligenta tjänster och applikationer möjliggjord av AI infiltrerar IoT många aspekter av vår vardag. Användbarheten för telefoner och surfplattor ökar till stor del som den primära datorenheten, eftersom de kraftfulla sensorerna tillåter dessa enheter att få tillgång till en oöverträffad mängd data. Det finns dock risker och ansvar för att lagra data på en central plats på grund av integritetsfrågor. För att övervinna denna utmaning tillåter Federated Learning (FL) användare att kollektivt ta fördelarna av delade modeller utbildade från denna stora data utan att behöva lagra den centralt. I denna forskning presenterar och utvärderar vi implementeringen av federerat lärande på Raspberry Pi-kort med FedAVG-metoden. Dessutom hade komprimeringsmetoden som kvantisering och versifiering tillämpats på basimplementeringen för att förbättra kommunikationseffektiviteten. Vi slutför implementeringen genom att jämföra baslinjeimplementeringen och den komprimerade FedAVG på Raspberry-Pi-kort för att uppnå lägsta kostnad och högre noggrannhet för att passa IoT-miljö

This thesis investigates different methods that can be used for analyzing network performance and,ultimately, can be used for measuring the convergence time of ring coupled networks. As of today,many networks are often run with extra links, serving as backup links in case any that of the mainlinks would go down. To operate networks with backup links in layer 2 and layer 3, specific re-routing protocols such as RIP and OSPF are used in order to calculate a feasible path through anetwork when a network state changes. Depending on different implementations of the protocolsand the hardware used, the convergence times can vary substantially, which means measuring thenetwork performance is a very important part when developing a network solution. To executenetwork tests, a packet engine suite is used consisting of a network traffic generator that is used forcreating a packet stream, as well as a traffic receiver that fetches the packets sent. Various types ofengines can be used including Linux based, real-time operating systems based and bare-metal basedsolutions. From these different types of engines, a few tools are chosen and investigated on differentproperties including performance and usability. It was found that Tshark (Linux, RT-Linux based),USPI (Raspberry Pi bare metal), FreeRTOS (Raspberry Pi based), Arduino and PKTgen (Linuxkernel based) were the most suitable approaches to be used for testing. The test parameters includetesting the gaps between packets, maximum jitter, average jitter and packets sent per second. Thesetests revealed that an IXIA solution was slightly more accurate when used as a receiving end sinceit produced less jitter, however this difference could only be noticed in a micro second range. Itwas also revealed that it produced slightly less jitter than the other packet generators, also here onlynoticeable in a microsecond range. Thus it can be concluded that IXIA is not much superior any ofthe close to hardware solutions. The executed network tests revealed that the Westermo developedlayer 2 protocol FRNT generated less network convergence time and less packet losses than thecommonly used RSTP protocol. Similar tests against the layer 3 protocols revealed that RIP wasmuch faster than OSPF and it also lost less packets. Finally it is concluded that there is no needto buy an expensive network testing suite to test the convergence time of a network. Instead, anetwork testing suite can be developed with minimal funding.

Ingeniero Civil Químico / En los últimos años, la masificación de sistemas embebidos y de computadores de placa reducida (SBC) han permitido el diseño, desarrollo y automatización de hardware de bajo costo para aplicaciones multidisciplinarias tales como impresoras 3D, sistemas de alarmas y climatización. Sin embargo, a nivel de laboratorios y pequeñas industrias su uso se limita a la creación de sensores, es por ello que esta memoria explora el diseño de un sistema de control enfocado en estos segmentos. Este sistema de control está compuesto por un servidor de control que posee una base de datos, un servidor web que actúa como interfaz humano-máquina (HMI), y un elemento de control, conectados mediante una red inalámbrica. El elemento de control corresponde al dispositivo encargado de obtener desde los sensores, datos sobre las variables de entrada, manipular los actuadores a través de los puertos de salida y posee además, la capacidad de implementar una ley de control a través de un controlador en modo de supervisión o como controlador digital directo. Por otro lado, el servidor de control tiene la función de registrar las mediciones de los sensores del equipo conectados al sistema, además, también puede registrar modificaciones hechas al sistema desde el HMI. El sistema de control diseñado se implementó en el equipo HL630, equipo que posee un circuito de calefacción de agua que incluye un radiador con ventilador, calefactor, una bomba de potencia regulable y un sensor de flujo. Para esto, se utilizó como servidor de control el SBC Raspberry Pi B+, y como elemento de control el sistema embebido Arduino Yún. Para conectar el equipo al elemento de control, se utilizó circuitos y dispositivos electrónicos con el fin de enlazar los actuadores y sensores. Asimismo, se observó la presencia de interferencias electromagnéticas (EMI), problema que se solucionó utilizando una jaula de Faraday. Además, se implementó un controlador digital directo de tipo PID con PWM debido a que no es posible utilizar el elemento de control en modo de supervisión. Finalmente, para la sintonización del controlador, se utilizó un modelo empírico basado en la respuesta del sistema a un pulso de 15 seg., y con ello, mediante el ajuste de parámetros de simulaciones para un sistema con una función de transferencia de cierto orden, se determinó que la función de transferencia que mejor representa el sistema es de orden-(3,2). Así, se sintonizó el controlador utilizando algoritmos basados en la minimización de overshoot en función del tiempo de estabilización del sistema para problemas de regulación y servo-control, en base a una simulación del sistema con controlador PID continuo, para obtener parámetros utilizados como base de la ley de control implementada y mediante un análisis de sensibilidad se obtuvo un valor definitivo. Posteriormente, se probó de forma experimental que al aumentar 10 veces el valor destinado a eliminar el windup reset aumenta la amplitud de oscilaciones y el sistema converge a estado estacionario oscilando alrededor del valor del setpoint. De igual manera, también se experimentó aumentar al doble el periodo de la señal de referencia del PWM y se observó que el controlador no cambia la amplitud, ni el tiempo de estabilización, sin embargo, se genera una oscilación de alta frecuencia de amplitud constante. Así, fue posible diseñar una infraestructura de un sistema de control distribuido con las caracteristicas ya mencionadas, que se implementó en un equipo de laboratorio y de forma exitosa fue posible monitorear y controlar el equipo de forma remota a través del HMI. A su vez, este proyecto permitió ver la factibilidad técnica de implementar sistemas de control de bajo costo en algunos procesos de pequeñas escala, a modo de reemplazar la utilización de costosos sistemas industriales.

Nowadays, it is of crucial importance for the manufacturing industry to be prepared for the application and understanding of autonomous mobile robots. Given this fact, educational institutions have to provide knowledge and experience to students. These autonomous mobile robots are made and controlled using different platforms and programming languages. Currently, the University of Skövde wishes to expand the range of tools to be available for building and experimenting with autonomous robots. For this purpose, this thesis project has two main goals. The first goal is finding the best available robotic platform for small scale, self-built, programmable robots. Such a platform has to include all the hardware necessary for later implementation with the software. The platform is evaluated in this thesis following different criteria. The second goal is to build a robot using the chosen platform. The robot has to perform a certain task taking advantage of its specific hardware. The development of the task has been achieved using the Robot Operative System (ROS). This thesis provides step by step instructions of how to build the platform and perform the task.

More and more devices around us are connected to the internet and communicate to each other. This includes devices such as radon sensors. Radon is a radio active gas and is the cause of several hundred cases of lung cancer. Smart connected radon sensors can be helpful to reduce the levels of radon as they provide remote access to the user. This study examines the opportunity to connect an already existing radon sensor to the “Internet of Things”. The aim of this study has been to answer the problem “find a better solution for the IoT system and develop it”. The study was performed with a literature study of three Internet of Things platforms. This resulted in one Internet of Thing platform being used throughout the study. A database system and a system with the chosen platform was implemented and a time measurement of the different systems was performed. The study has shown that a less secured system is faster and it is also shown that the Amazon Web Service IoT Core is fast with respect to the many features offered. The study concludes that the choice of system depends on where and how the system is supposed to be implement. If the system just needs to send and store data, a regular MySQL database is enough. If the system in the future is supposed to be able to communicate with other devices, a IoT platform should be used.

Today at various locations and factories we have a lot of sensors and actuators that interact with each other and a control-unit. The control-unit is in most cases a cloud-based solution. This is in most cases a good solution. However, there is a rise in expected devices and sensors which will most likely be too much data for the existing network to handle. This paper researches if a fog-unit might be the solution to this problem. The setup of the fog-unit in the network is a unit between the cloud and the sensors and actuators. In this paper the fog-unit and sensors/actuators have been emulated on Raspberry Pi’s. The sensors are emulated using python-threads and communicate with the fog-unit using the UDP-based protocol CoAP and the fog communicates to the cloud using the TCP- based protocol MQTT. After a prototype was built it using said Raspberry Pi’s it was sent through a few measurements in the fields of bandwidth, cloud-utilization and response times. This was later compared to another setup without the fog-unit as the control setup. The result with this kind of setup was that a fog-unit lowers the cloud-utilization and use of bandwidth, however it increases the round trip time of a request from the cloud by a large amount. Which leads to the conclusion that a fog-unit in this kind of setup might be a good network solution if the response time to the cloud isn’t important.

The goal of this thesis was to develop, deploy and evaluate a lightweight portable intrusion detection system (LPIDS) over wireless networks. The LPIDS was developed by adopting two different string matching algorithms: Aho-Corasick algorithm and Knuth–Morris–Pratt algorithm (KMP). The LPIDS was implemented and tested on the hardware platforms Wi-Fi Pineapple and Raspberry Pi. To evaluate and test the LPIDS as well as the algorithms, performance metrics such as throughput, response time and power consumption are considered. The experimental results reveal that Aho-Corasick performed better than KMP throughout the majority of the process, but KMP was typically faster in the beginning with fewer rules. Similarly, Raspberry Pi shows remarkably higher performance than Wi-Fi Pineapple in all of the measurements. Moreover, we compared the throughput between LPIDS and Snort. It was concluded that the throughput was significantly higher for LPIDS when most of the rules do not include content parameters. This thesis concludes that due to computational complexity and slow hardware processing capabilities of Wi-Fi Pineapple, it could not become suitable IDS in the presence of different pattern matching strategies. Finally, we propose a modification of Snort to increase the throughput of the system.

Nowadays, a growing number of startups, who used to produce non- intelligent devices, are seeking transformation and hope to achieve their Internet of Things (IoT) deployment. In other words, they begin to focus on producing smarter devices to meet user’s needs. At present, various IoT cloud platforms are emerging one after another, but using these resources can be costly for small companies. Since the entire IoT system is complex, it involves many links, the purpose of this project is to create a suitable IoT platform for small companies. The system applies JavaWeb technology with the framework of Spring MVC + Spring + Hibernate (SSH), uses open source User Interface (UI) solution and MySQL database management system (DBMS). At the same time, the system adopts Hypertext Transfer Protocol (HTTP) as the communication protocol to complete the data transmission between devices and the platform. Finally, the system is deployed in the server built on the Raspberry Pi. The system is measured from multiple aspects on the established scenario. The results show that companies and users can use the platform as expected, and companies can expand the system to further realize their IoT deployment in the future.

This thesis is concerned with the usability of Raspberry Pi as the access point in the mobilebroadband network environment. The first part of the thesis is dedicated to Raspberry Pi itself;hardware required to set up WLAN and WAN; and to the analysis of suitable solutions forbandwidth aggregation, particularly the load balancing of mobile broadband connections andtheir aggregation into one logical link. The second part deals with the implementation of thesesolutions and subsequently with their testing and verification. The evaluation of results gives aninteresting outcome. Load balancing has proven to be resilient and feasible solution forbandwidth aggregation in the mobile broadband network environment where the speed, packetloss and jitter are of main concern. The second scenario, where the connections are bundled intoone logical link, has turned out to give variable results. Its performance is susceptible to thechanges in the mobile broadband network as the packets across the links in the bundle alternatein the round-robin fashion.