The work is about developing an existing product in a company. The productis AnyBus Communicator used to connect two serial devices with differentindustrial network interfaces. The development involves combining theexisting product with a BLE-module and an antenna. Wireless technologyopens up various possibilities and plays a significant role in complexenvironments. Today, communication occurs through an Ethernet cable. Theproject's goal is to design a circuit for the BLE-module integrated into theproduct's PCB. The goal also includes presenting a choice of antenna and aplastic-type for antenna enclosure that can be used in future development ofthe product. The work began with the evaluation of the BLE-module, wherea communication test was performed to test the BLE-module's properties.Several tests were performed using Network Analyzer to select a suitableantenna from three different antennas. The antennas were tested with twodifferent types of plastic designed using Solidworks, to present a choice ofthe type of plastic to be used during all tests in the development process.Presenting an electrical schematic and PCB for the wireless AnyBusCommunicator was a goal of the project. Since it was impossible to combinethe BLE-module with the product in the same PCB, it was decided to designa separate circuit that illustrates how the BLE-module will be connected tothe product in the future. The project resulted in a proposal for both an antennaand a plastic-type. A prototype circuit has also been designed for the BLEmodule. The choice of antenna and plastic-type was based on the best valuewhen measuring return loss values. The type of plastic chosen will not be usedin the finished product but is a way to test antenna functionality against 3Dprinted plastics. This is considered to be a cheaper solution that gives a similarresult compared to the enclosure used in the product. A finished design of thecircuit board has been implemented. However, it could not be tested due tothe company having a difficult situation to produce ordinary circuit.Therefore, it can be concluded that the work had relevant proposals and wasa forward step in the development process. / Arbetet handlar om att utveckla en befintlig produkt på ett företag. Produktenär en AnyBus Communicator som används för att koppla upp två seriellaenheter som har olika industriella nätverksgränssnitt. Utvecklingen innebäratt kombinera befintliga produkten med en BLE-modul och en antenn. Idag sker kommunikationen med en Ethernet-kabel. Målet med projektet äratt designa en krets för BLE-modulen som skall integreras i produktens PCB.Målet omfattar också att presentera ett val av antenn och en plasttyp förantennkapsling som kan användas i framtida utvecklingen för produkten. Arbetet inleddes med utvärdering av BLE-modulen, där ettkommunikationstest utfördes för att testa BLE-modulens egenskaper. Ettantal tester genomfördes med hjälp av nätverksanalysator för att kunna väljaen lämplig antenn utav tre olika antenner. Antennerna testades med två olikaplasttyper som är designade med hjälp av Solidworks, för att senarepresentera ett val av plasttypen som skall användas under alla tester iutvecklingsprocessen. Att presentera ett elschema och PCB för den trådlösaAnyBus Communicator var ett mål för projektet. Eftersom det inte var möjligtatt kombinera BLE-modulen med produkten i samma PCB, bestämdes det attdesigna egen krets för BLE-modulen som illustrerar hur den skall kopplas tillprodukten i framtiden. Projektet resulterade i ett förslag både på en antenn och plasttyp. En prototypkrets har även designats för BLE-modulen. Antennens och plasttypens val baserades på bästa värde vid mätning avreturförlustvärden. Plasttypen som valdes kommer inte att användas i denfärdiga produkten, utan det är ett sätt att testa antennfunktionalitet mot 3Dprintade plast. Det anses vara en billigare lösning som ger ett liknande resultatjämfört med kapslingen som används i produkten. En färdig design påkretskortet har genomförts men kunde inte testats på grund av att företagethar en besvärlig situation att få in vanliga produktionskort i dagsläget. Därförkan slutsatsen dras att arbetet hade relevanta förslag och var ett steg iutvecklingsprocessen.

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Internet of Things (IoT) är ett område under omfattande utveckling, både vad det gäller hårdvara och mjukvara. När det gäller hårdvaruplattformar för IoT enheter finns det platt-formar som är kraftfulla nog att exekvera ett reguljärt OS som t.ex. Linux. Andra hårdvaru-plattformar är inte tillräckligt kraftfulla för att exekvera reguljära OS och för dessa plattformar finns ett behov av resurseffektiva små IoT OS. Dessa resurssnåla OS behöver kunna hantera många av de funktioner som reguljära OS erbjuder, men på ett betydligt mer effektivt sätt.Det har under de senaste åren släppts en uppsjö av olika IoT OS för resurssnåla enheter och därför är syftet med denna rapport en utvärdering av IoT OS för strömsnåla resurssvaga IoT enheter. Utvärdering genomförs på IoT OS:en Contiki, mbed, RIOT och Zephyr. Målet med utvärderingen är att fastställa viktiga egenskaper för ett IoT OS för strömsnåla resurssvaga IoT enheter, och att belysa svårigheter och erfarenheter relaterade till konstruktionsprocessen av en prototyp för IoT enheter. Utvärderingen genomfördes genom att samla in fyra olika typer av data relaterade till IoT OS:en, och sedan utvärdera denna data med hjälp av en kriteriebaserad utvärderingsmetod.Utvärderingen resulterade i en lista av sex viktiga egenskaper för små resurs snåla IoT operativsystem. Dess resultat belyser även svårigheter och erfarenheter som framkommit under byggprocessen av prototyperna baserade på IoT OS:en.Slutsatsen av denna rapport bidrar med erfarenheter från byggning av prototyper IoT OS för resurssnåla enheter, samt ett utvärderingsresultat för IoT OS:en med hänsyn till de sex viktiga IoT OS egenskaperna. / The Internet of Things (IoT) is a large and rapidly expanding area with regards to both hardware platforms and software. When it comes to hardware platforms for the IoT some are more powerful and able to run a traditional OS like Linux, while other platforms are too constraint to do so. To ease the development within the IoT area an appropriate IoT OS is needed for these constrained hardware platforms, which can handle most of the functionality a traditional OS offer.Therefore, we evaluate IoT OSs targeted for low performance battery powered devices. In this thesis Contiki, mbed, RIOT and Zephyr are evaluated. The aim of this evaluation is to determine important IoT OS characteristics for resource constrained devices, and to highlight difficulties and experiences related to the building process of prototypes for such IoT devices.The evaluation of the IoT OSs were conducted on four types of data with regards to several measurable OS characteristics according to a criteria based evaluation method.The evaluation resulted in a list of six IoT OS characteristics important for wireless, resource constrained and battery powered devices. Furthermore the evaluation highlights potential setbacks during the building process of a prototype system for such devices and it also explains what experiences that can be gained.The conclusion of this thesis contributes with experience related to IoT OS prototype construction and also an evaluation result with respect to the six IoT OS characteristics for constraint battery driven devices.

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.

Beekeeping is an ancient activity that has been practised for thousands of years. Bees and other pollinators are important to food security. Sources indicate that bee-hive theft is on the rise in Sweden. In this report, different alternatives to beehive theft detection are explored. Possible solutions are found by looking at theft detec-tion in general and for beehives in particular. This work describes the different types of theft that beehives are subjected to. Suggested solutions for theft detection are based on activities that might be related to the different types of theft. One of the solutions is implemented and tested. An anti-theft system for cars inspires the solution, and it is partially chosen because it seems novel to the field of beehive theft detection. In the implemented solution, one external unit is keeping track of all the hives using regular check-ins via Bluetooth. Absent check-ins could indicate that a hive is missing. Through testing, it is shown that there is room for improvement inthe implementation, both when it comes to energy consumption and when it detects theft. Deployment costs could be low for situations with a large enough number of beehives at the same place, if the hives are assumed to be smart, this solution only requires one external unit to be added, whereas other solutions might require extra sensors in every hive. For a smaller number of hives, it should be more cost-effectiveto add some sensor that can detect that the hive is manipulated.

This thesis compares and evaluates the accuracy of two RSSI-based tri-lateration methods in an indoor setting, implementing either Wi-Fi andBluetooth Low Energy (BLE) while using commercially available hardware.The purpose of evaluation is part of the long-term vision of improving thesafety of workers in adverse environments such as factories, by providing awearable Indoor Positioning System where other systems like GPS are notsuitable due to signal obstruction. Within a confined space replicating in-tended real-world conditions in terms of signal attenuation and adversity,30 consecutive measurements of signal strength readings (RSSI) to threereference nodes were collected at 10 randomized sample positions, andwas repeated across 5 tests. The accuracy of trilateration was evaluatedusing an averaged Root Mean Square Error (RMSE) over the five tests. Itwas observed that RSSI using Wi-Fi achieved better accuracy of predictingthe actual position within the testing environment than signal-strength us-ing BLE, with Wi-Fi and BLE achieving an accuracy of 0.88 and 1.85 metersrespectively. However, because of the power efficiency of BLE it is a viablecandidate for a future low-cost and device-based Indoor Localization Sys-tem to potentially be used and worn by workers. The results while alignedwith similar existing literature, infer what a low-cost indoor positioningsystem might achieve. Future research with the goal of developing suchsolutions could benefit from implementing both Wi-Fi and BLE as the basisof signal strength trilateration.

Modern indoor positioning systems encounter challenges inherent to indoor environments. Signal changes can stem from various factors like object movement, signal propagation, or obstructed line of sight. This thesis explores a supervised machine learning approach that integrates Bluetooth Low Energy (BLE) and inertial sensor data to achieve consistent angle and distance estimations. The method relies on BLE angle estimations and signal strength alongside additional sensor data from an Inertial Measurement Unit (IMU). Relevant features are extracted and a supervised learning model is trained and then validated on familiar environment tests. The model is then gradually introduced to more unfamiliar test environments, and its performance is evaluated and compared accordingly. This thesis project was conducted at the u-blox office and presents a comprehensive methodology utilizing their existing hardware. Several extensive experiments were conducted, refining both data collection procedures and experimental setups. This iterative approach facilitated the improvement of the supervised learning model, resulting in a proposed model architecture based on transformers and convolutional layers. The provided methodology encompasses the entire process, from data collection to the evaluation of the proposed supervised learning model, enabling direct comparisons with existing angle estimation solutions employed at u-blox. The results of these comparisons demonstrate more accurate outcomes compared to existing solutions when validated in familiar environments. However, performance gradually declines when introduced to a new environment, encountering a wider range of signal conditions than the supervised model had trained on. Distance estimations are then compared with the path loss propagation equation, showing an overall improvement. / Moderna inomhuspositioneringssystem möter utmaningar som förekommer i inomhusmiljöer. Signalförändringar kan bero på olika faktorer som objektets rörelse, signalutbredning eller blockerad siktlinje. Denna kandidat avhandling undersöker ett övervakat maskininlärningssätt som integrerar Bluetooth Low Energy (BLE) och tröghetssensorer för att uppnå konsekventa vinkel- och avståndsberäkningar. Metoden bygger på BLE-vinkelberäkningar och signalstyrka tillsammans med ytterligare sensordata från en Inertial Measurment Unit (IMU). Relevanta funktioner extraheras och en övervakad inlärningsmodell tränas och valideras sedan på tester i bekanta miljöer. Modellen introduceras sedan gradvis till mer obekanta testmiljöer, och dess prestanda utvärderas och jämförs därefter. Detta examensarbete genomfördes på u-blox kontor och presenterar en omfattande metodik som utnyttjar deras befintliga hårdvara. Flera omfattande experiment genomfördes, vilket förfinade både datainsamlingsprocedurer och experimentuppsättningar. Detta iterativa tillvägagångssätt underlättade förbättringen av den övervakade inlärningsmodellen, vilket resulterade i en föreslagen modellarkitektur baserad på transformatorer och konvolutionella lager. Den tillhandahållna metodiken omfattar hela processen, från datainsamling till utvärdering av den föreslagna övervakade inlärningsmodellen, vilket möjliggör direkta jämförelser med befintliga vinkelberäkningslösningar som används på u-blox. Resultaten av dessa jämförelser visar mer exakta resultat jämfört med befintliga lösningar när de valideras i bekanta miljöer. Dock minskar prestandan gradvis när den introduceras till en ny miljö, där den möter ett bredare spektrum av signalförhållanden än vad inlärningsmodellen har tränats på. Avståndsberäkningar jämförs sedan med en matematisk formel, kallat path loss propagation ekvationen, som ger distans som en funktion av uppmätt signalstyrka.

Genom att studera olika kommunikationsprotokoll kunna svara på vad det är som gör att ett visst protokoll är bäst anpassat för att användas mellan mobila enheter och IoT-enheter. I arbetet användes en kvalitativ litteraturstudie för att ge en grundlig teoretisk bakgrund samt en experimentell studie där ett par teorier undersökts ifall de stämmer med resultaten ifrån verkligheten. De fem faktorerna kompatibilitet, batteritid, frekvens, räckvidd och tillförlitlighet undersöktes hos kommunikationsprotokollen Bluetooth Low Energy (BLE), Närfältskommunikation (NFC) och Wi-Fi. Dessa tre valdes eftersom de stöds av nyare mobila plattformar idag. Kommunikations-protokollen analyserades sedan gentemot olika användningsområden inom IoT, eftersom påståendet vad som är bäst anpassat beror på vad situationen kräver för egenskaper. En systemutvecklare som ska välja kommunikationsprotokoll till en IoT-tillämpning och läser denna rapport bör själv jämföra de olika protokollen mot varandra inom de fem faktorerna för att kunna avgöra vilket protokoll som passar bäst inom dennes situation. I arbetet utfördes endast experimentella studier på BLE på grund av begränsningar inom utrustningen. Ytterligare experiment inom NFC och Wi-Fi skulle ge ett bredare perspektiv med fler infallsvinklar. / By studying different communication protocols respond to what it is that makes a certain protocol best suited for use between mobile devices and IoT devices. This study used a qualitative literature study to create a proper theoretical background and an experimental study where two theories were investigated in whether they matched wih the results from the reality. The five factors compatibility, battery loss, frequency, range and reliability were investigated in the communication protocols Bluetooth Low Energy (BLE), Near field communication (NFC) and Wi-Fi, these three because they are supported by newer mobile platforms today. The communication protocols were then analysed against various uses in the IoT, since the claim what it is that makes it best suited depends on what the situation requires. A system developer that is about to select the communication protocol to use in an IoT application and reads this study should compare the different protocols to each other within the five factors to determine which protocol is best suited for his situation. This study only performed experimental studies on BLE because of limitations in the equipment. Additional experiments on NFC and Wi-Fi would provide a wider perspective.

Ce travail vise la modélisation au niveau système, en langage SystemC-AMS, et la simulation d'un émetteur-récepteur au standard Bluetooth Low Energy (BLE). L'objectif est d'analyser la relation entre les performances, en termes de BER et la consommation d'énergie du transceiver. Le temps de simulation d’un tel système, à partir de cas d’étude (use case) réaliste, est un facteur clé pour le développement d’une telle plateforme. De plus, afin d’obtenir des résultats de simulation le plus précis possible, les modèles « haut niveau » doivent être raffinés à partir de modèles plus bas niveau où de mesure. L'approche dite Meet-in-the-Middle, associée à la méthode de modélisation équivalente en Bande Base (BBE, BaseBand Equivalent), a été choisie pour atteindre les deux conditions requises, à savoir temps de simulation « faible » et précision des résultats. Une simulation globale d'un système de BLE est obtenue en intégrant le modèle de l'émetteur-récepteur dans une plateforme existante développée en SystemC-TLM. La simulation est basée sur un système de communication de deux dispositifs BLE, en utilisant différents scénarios (différents cas d'utilisation de BLE). Dans un premier temps nous avons modélisé et validé chaque bloc d’un transceiver BT. Devant le temps de simulation prohibitif, les blocs RF sont réécrits en utilisant la méthodologie BB, puis raffinés afin de prendre en compte les non-linéarités qui vont impacter le couple consommation, BER. Chaque circuit (chaque modèle) est vérifié séparément, puis une première simulation système (point à point entre un émetteur et un récepteur) est effectuée / This work aims at system-level modelling a defined transceiver for Bluetooth Low energy (BLE) system using SystemC-AMS. The goal is to analyze the relationship between the transceiver performance and the accurate energy consumption. This requires the transceiver model contains system-level simulation speed and the low-level design block power consumption and other RF specifications. The Meet-in-the-Middle approach and the Baseband Equivalent method are chosen to achieve the two requirements above. A global simulation of a complete BLE system is achieved by integrating the transceiver model into a SystemC-TLM described BLE system model which contains the higher-than-PHY levels. The simulation is based on a two BLE devices communication system and is run with different BLE use cases. The transceiver Bit-Error-Rate and the energy estimation are obtained at the end of the simulation. First, we modelled and validated each block of a BT transceiver. In front of the prohibitive simulation time, the RF blocks are rewritten by using the BBE methodology, and then refined in order to take into account the non-linearities, which are going to impact the couple consumption, BER. Each circuit (each model) is separately verified, and then a first BLE system simulation (point-to-point between a transmitter and a receiver) has been executed. Finally, the BER is finally estimated. This platform fulfills our expectations, the simulation time is suitable and the results have been validated with the circuit measurement offered by Riviera Waves Company. Finally, two versions of the same transceiver architecture are modelled, simulated and compared

This thesis aims to develop an e-health embedded system with a real-time operating system (RTOS), which allows users to monitor their body condition, including heart rate and breath, through Bluetooth Low Energy (BLE). Meanwhile, the device is also able to provide guidance for breathing by simulating breathing according to given parameters. In practice, the system samples the heart rate every two milliseconds. To ensure reliability and validity, results are expected to be sent in realtime. However, numerous data cannot be transmitted directly without being processed. Otherwise, the system will crash, and hard faults will occur. A general idea to solve this problem is to classify messages into two categories based on the priority. One is urgent, and the other is unimportant. Two solutions are proposed, one using a unidirectional linked list, and the second using queues. Based on an ARM micro-controller, the e-health embedded system is designed and implemented successfully. The evaluation results show that the solution using a linked list is suitable for the system, while the solution using queues is unable to solve the problem. With the help of the message classification, the urgent messages can be timely transmitted with continuous data. / Avhandlingen syftar till att utveckla ett e-hälso-inbyggt system med ett realtidsoperativsystem (RTOS), som gör det möjligt för användare att övervaka sitt kroppstillstånd, inklusive hjärtfrekvens och andetag, genom Bluetooth Low Energy (BLE). Samtidigt kan enheten också ge vägledning för andning genom att simulera andning enligt givna parametrar. I praktiken samplar systemet hjärtfrekvensen varannan millisekund. För att säkerställa tillförlitlighet och giltighet bör resultaten skickas i realtid. Annars kraschar systemet och allvarliga fel uppstår. En allmän idé för att lösa detta problem är att klassificera meddelanden i två kategorier baserade på prioritering, en är brådskande och den andra är obetydlig. Två lösningar föreslås, en med hjälp av riktad länkad lista och en annan implementerad med hjälp av köer. Resultatmässigt, baserat på en ARM-mikrokontroller, är det inbyggda e-hälsosystemet framgångsrikt designat och konfigurerat. Lösningen med en länkad lista är lämplig för systemet, medan lösningen som implementeras med köer fortfarande inte kan lösa problemet. Med hjälp av meddelandeklassificeringen är de brådskande meddelandena inte ens försenade med kontinuerlig data.