M. Tech. (Department of Process Control and Computer Systems, Faculty of Engineering and Technology), Vaal University of Technology. / Radio Frequency Identification Technology (RFID) technology is increasingly being used in multiple applications due to its low cost and ability to provide a high quality of identification. The cost benefit of RFID system is seen in the reduction in labor required to perform routine tasks such as inventory. With RFID, inventory-related tasks can be done in substantially less time compared to other commonly used auto-identification systems. Recent research has illustrated the application of RFID in multiple application scenarios. RFID can be used for real-time patient identification and monitoring in hospitals, but also for product expiration-date management in retail industries. Some enterprises in South Africa uses a combination of RFID technology and Internet of Things (IoT) to detect misplaced products and to detect low stock levels. Furthermore, RFID is also used for inventory management in libraries as discussed in this dissertation. In this dissertation, a combination of RFID and ZigBee technologies was used to reduce the time spent to perform inventory in libraries. An inventory management system was designed, simulated and built in order to count and locate books inside a library hence improving inventory process time in libraries. The overall results were satisfactory which lead to the achieving of the objectives set in this study.

Low-power wireless technology is a part and parcel of our daily life, shaping the way in which we behave, interact, and more generally live. The ubiquity of cheap, tiny, battery-powered devices augmented with sensing, actuation, and wireless communication capabilities has given rise to a ``smart" society, where people, machines, and objects are seamlessly interconnected, among themselves and with the environment. Behind the scenes, low-power wireless protocols are what enables and rules all interactions, organising these embedded devices into wireless networks, and orchestrating their communications. The recent years have witnessed a persistent increase in the pervasiveness and impact of low-power wireless. After having spawned a wide spectrum of powerful applications in the consumer domain, low-power wireless solutions are extending their influence over the industrial context, where their adoption as part of feedback control loops is envisioned to revolutionise the production process, paving the way for the Fourth Industrial Revolution. However, as the scale and relevance of low-power wireless systems continue to grow, so do the challenges posed to the communication substrates, required to satisfy ever more strict requirements in terms of reliability, responsiveness, and energy consumption. Harmonising these conflicting demands is far beyond what is enabled by current network stacks and control architectures; the need to timely bridge this gap has spurred a new wave of interest in low-power wireless networking, and directly motivated our work. In this thesis, we take on this challenge with a main conceptual and technical tool: concurrent transmissions (CTX), a technique that, by enforcing nodes to transmit concurrently, has been shown to unlock unprecedented fast, reliable, and energy efficient multi-hop communications in low-power wireless networks, opening new opportunities for protocol design. We first direct our research endeavour towards industrial applications, focusing on the popular IEEE 802.15.4 narrowband PHY layer, and advance the state of the art along two different directions: interference resilience and aperiodic wireless control. We tackle radio-frequency noise by extensively analysing, for the first time, the dependability of CTX under different types, intensities, and distributions of reproducible interference patterns, and by devising techniques to push it further. Specifically, we concentrate on CRYSTAL, a recently proposed communication protocol that relies on CTX to rapidly and dependably collect aperiodic traffic. By integrating channel hopping and noise detection in the protocol operation, we provide a novel communication stack capable of supporting aperiodic transmissions with near-perfect reliability and a per-mille radio duty cycle despite harsh external interference. These results lay the ground towards the exploitation of CTX for aperiodic wireless control; we explore this research direction by co-designing the Wireless Control Bus (WCB), our second contribution. WCB is a clean-slate CTX-based communication stack tailored to event-triggered control (ETC), an aperiodic control strategy holding the capability to significantly improve the efficiency of wireless control systems, but whose real-world impact has been hampered by the lack of appropriate networking support. Operating in conjunction with ETC, WCB timely and dynamically adapts the network operation to the control demands, unlocking an order-of-magnitude reduction in energy costs w.r.t. traditional periodic approaches while retaining the same control performance, therefore unleashing and concretely demonstrating the true ETC potential for the first time. Nevertheless, low-power wireless communications are rapidly evolving, and new radios striking novel trade-offs are emerging. Among these, in the second part of the thesis we focus on ultra-wideband (UWB). By providing hitherto missing networking primitives for multi-hop dissemination and collection over UWB, we shed light on the communication potentialities opened up by the high data throughput, clock precision, and noise resilience offered by this technology. Specifically, as a third contribution, we demonstrate that CTX not only can be successfully exploited for multi-hop UWB communications but, once embodied in a full-fledged system, provide reliability and energy performance akin to narrowband. Furthermore, the higher data rate and clock resolution of UWB chips unlock up to 80% latency reduction w.r.t. narrowband CTX, along with orders-of-magnitude improvements in network-wide time synchronization. These results showcase how UWB CTX could significantly benefit a multitude of applications, notably including low-power wireless control. With WEAVER, our last contribution, we make an additional step towards this direction, by supporting the key functionality of data collection with an ultra-fast convergecast stack for UWB. Challenging the internal mechanics of CTX, WEAVER interleaves data and acknowledgements flows in a single, self-terminating network-wide flood, enabling the concurrent collection of different packets from multiple senders with unprecedented latency, reliability, and energy efficiency. Overall, this thesis pushes forward the applicability and performance of low-power wireless, by contributing techniques and protocols to enhance the dependability, timeliness, energy efficiency, and interference resilience of this technology. Our research is characterized by a strong experimental slant, where the design of the systems we propose meets the reality of testbed experiments and evaluation. Via our open-source implementations, researchers and practitioners can directly use, extend, and build upon our contributions, fostering future work and research on the topic.

Internet of Things (IoT) är en växande teknologi som spelar en allt större roll i samhället. Den innefattar ett nätverk av internetanslutna enheter som samlar in och utbyter data. Samtidigt som IoT växer uppstår utmaningar kring hantering av stora datamängder och säkerhetsaspekter. Företaget Softhouse står inför utmaningen att välja en effektiv tidsseriedatabas för hantering av temperatur- och geopositionsdata från värmesystem i privata bostäder, där både prestanda och dataintegritet via kryptering är av stor vikt. Detta examensarbete har därför utfört en prestandajämförelse mellan AWSTimestream och InfluxDB, där olika tester har använts för att mäta exekveringstiden för inskrivning av sensordata och databasfrågor. Jämförelsen inkluderar AWS Timestream i krypterad form mot InfluxDB i dess AWS-molnversion i krypterad form, samt InfluxDB AWS i krypterad form mot InfluxDB i okrypterad form. Syftet med studien var att ge riktlinjer för valet av tidsseriedatabaser med fokus på prestanda och säkerhetsaspekter, inklusivekryptering. Studien undersökte även hur valet av rätt databas påverkar företag som Softhouse, både i termer av kvantitativa och kvalitativa fördelar, samt att ge en bedömning av kostnaderna. Resultatet visade att InfluxDB i dess AWS-molnversion generellt presterade bättre än AWS Timestream och InfluxDB i dess standardversion. Det fanns tydliga skillnader i prestanda mellan AWS Timestream och InfluxDB i dess AWS-molnversion, men inte lika tydliga skillnader i prestanda mellan InfluxDB i dess AWS-molnversion och standardversionen. Med hänsyn till både prestanda och säkerhet framstår InfluxDB i dess AWS-molnversion som det mest lämpliga alternativet. Det är emellertid av stor vikt att ta kostnadaspekten i beaktande, då AWS Timestream visar sig vara avsevärt mer kostnadseffektivt än InfluxDB. / The Internet of Things (IoT) is a growing technology that plays an increasingly significant role in society. It encompasses a network of internet-connected devices that collect and exchange data. As IoT continues to expand, challenges arise regarding the management of large volumes of data and security aspects. The company Softhouse faces the challenge of choosing an efficient time-series database for handling temperature and geoposition data from heating systems in homes, where both performance and data integrity through encryption are of great importance. Therefore, this thesis has conducted a performance comparison between AWS Timestream and InfluxDB, using various tests to measure the execution times for data ingestion of sensor data and database queries. The comparison includes AWS Timestream in encrypted form versus InfluxDB in its AWS cloud version in encrypted form, as well as InfluxDB AWS in encrypted form versus InfluxDB in unencrypted form. The aim of the study was to provide guidelines for the selection of time-series databases with a focus on performance and security aspects, including encryption. The study also explored how the choice of the right database affects companies like Softhouse, both in terms of quantitative and qualitative benefits, and provided an assessment of costs. The results showed that InfluxDB in its AWS cloud version generally outperformed AWS Timestream and InfluxDB in its standard version. There were clear performance differences between AWS Timestream and InfluxDB in its AWS cloud version, but not as pronounced differences in performance between InfluxDB in itsAWS cloud version and the standard version. Considering both performance and security, InfluxDB in its AWS cloud version appears to be the most suitable option. However, it is crucial to consider the cost aspect, as AWS Timestream proves to be significantly more cost-effective than InfluxDB.

The privacy and surveillance issues that are consequences of the Internet of Things are the motivation and grounding for this thesis project. The Internet of Things (IoT) is a scenarioin which physical objects are able to communicate to each other and the environment, by transferring data over communication networks. The IoT allows technology to become smaller and more ubiquitous, and by being integrated in the environment around us, the world is becoming increasingly connected. Even though these developments will generally make our lives easier and more enjoyable, the Internet of Things also faces some challenges. One of these are the aforementioned privacy and surveillance issues that are the results of transferring sensitive data over communication networks. The aim of this thesis project is therefore to answer, both in a theoretical, as well as in a practical way, the following research question: How can the Internet of Things be more accessible and safe for the everyday user? Accordingly, the Auster online platform, the Auster app and the Data Obfuscation Kit were developed to provide people with the tools and knowledge to construct home automation projects themselves, as an alternative for using applications from governments and corporations alike. The aim is to create a way to endow people with the capability to exploit their talents, realise their visions and share this with a community joining forces. By enabling people to create their own home automation projects, personal data is kept in the user’s possession and the collection of data by governments and companies alike is prevented. Moreover, by giving the control over technology back to the user, creativity and innovation in the field of the Internet of Things in domestic environments are expected to increase.

En gymnasielärare i teknik i den svenska skolan påverkar och påverkas av samhället utanför skolans väggar. Samhällets digitalisering kan påverka tekniklärarens relativt stora möjligheter att välja det tekniska innehållet i kurserna, i olika grad. För att vara konkurrenskraftig i samhället behöver framtida tekniker ha goda kunskaper om de just för stunden aktuella teknikområdena och tidigare studier har visat att skolans resultat i hög grad beror av vilka kunskaper läraren har. I den här studien undersöktes tre tekniklärare på olika gymnasieskolor i Sverige, med avseende på synen på deras kunskaper i att undervisa om artificiell intelligens (AI), sakernas internet (Internet of Things - IoT) och robotteknik. Vidare studerades vilka undervisningsmetoder de avsåg att använda, samt vilka begränsande ramar de kunde se i detta uppdrag. Via enkät och intervjuer samlades data om frågeställningarna in. Rådata transkriberades och analyserades med utgångspunkt i Shulmans teori om Pedagogical Content Knowledge (PCK – ibland kallat ämnesdidaktisk kunskap på svenska) och även med stöd av ramfaktorteori och läroplansteori. Resultatet visar att de deltagande lärarna har behov av kompetenshöjning inom dessa tre teknikområden, samt att valet av undervisningsmetoder är beroende av de ramar som bland annat i form av tid och ekonomi påverkar undervisningen. Resultatet skiljer sig inte från liknande tidigare studier genomförda på lärare i grundskolan. / A technology teacher in the Swedish upper secondary school acts and is influenced by society outside the school walls. The digitalisation of society more or less influences how the technology teacher will choose the ways of implementing the curriculum, with respect to the technicalcontent of the courses. To be competitive in society, future technicians must have goodknowledge of the current technical areas, and previous studies have shown that the school's results largely depend on what knowledge the teacher has. In this study, three technology teachers at various upper secondary schools in Sweden were examined, regarding their view of their knowledge in teaching about artificial intelligence (AI), the Internet of Things (IoT) and robotics. The study also investigated their intended teaching methods and the framing factors they perceived when trying to perform this task. Through a survey and interviews, data on the issues were collected. Raw data were transcribed and analysed based on the theory of Pedagogical Content Knowledge (PCK), by Shulman and with the support of frame factor theory and curriculum theory. The results show that the participating teachers need more competence in these three technology areas, and that the choice of teaching methods depends on the resources provided, for instance in the form of time and finances. The results do not differ from similar previous studies conducted on primary school teachers.

I detta examensarbete analyseras Purduemodellen och dess tillämplighet inomnätverkssäkerhet för industriella styrsystem inom ramarna för Industri 4.0. Genomen litteraturstudie granskas modellens struktur och funktion i relation till de nyautmaningarna som uppkommit genom ökad digitalisering och integrering av IIoTteknologier. Studien identifierar både styrkor och svagheter i den traditionellaPurduemodellen. I resultatavsnittet introduceras en modifierad version avPurduemodellen, utformad för att förstärka nätverkssäkerheten och öka systemensförmåga att hantera cyberhot samt anpassa sig till teknologiska förändringar i denindustriella sektorn. Denna anpassning har genomförts genom införandet avytterligare säkerhetsstandarder och verktyg i syfte att förbättra modellenseffektivitet och relevans. / In this thesis, the Purdue model and its applicability within network security forindustrial control systems under the framework of Industry 4.0 are analyzed.Through a literature review, the model's structure and function are examined inrelation to the new challenges that have emerged due to increased digitization andintegration of IIoT technologies. The study identifies both strengths and weaknessesin the traditional Purdue model. In the results section, a modified version of thePurdue model is introduced, designed to enhance network security and increase thesystems' ability to handle cyber threats and adapt to technological changes in theindustrial sector. This adaptation has been achieved by incorporating additionalsecurity standards and tools aimed at improving the model's efficiency andrelevance.

InsurTech är en ny gren inom försäkringsbranschen som använder innovativa informationsteknologier för att effektivisera processer. Trots att försäkringsbranschen historiskt sett varit trögrörlig och inte förändrats mycket, har intresset för InsurTech ökat markant de senaste åren, vilket har skapat en betydande hype. På grund av detta syftar denna uppsats till att analysera och värdera om InsurTech kan få någon större effekt på den svenska försäkringsbranschen. Genom att fokusera på teknologierna Big data, Artificiell Intelligens, Telematik och Internet of Things undersöker uppsatsen om InsurTech kan effektivisera försäkringsprocessen och påverka marknaden och dess aktörer. Studien tillämpar en kvalitativ metod och inleds med en litteraturstudie i syfte att ge en helhetsbild av forskarvärldens bild av InsurTechs potential i dagsläget. Därefter följer en intervjustudie med experter inom försäkringsbranschen i syfte att framhäva deras bild av potentialen och vad som i dagsläget går att implementera i branschen. Studien tar avstamp i en teoretisk analysmodell baserad på ett transaktionskostnadsperspektiv. Modellen byggs upp i tre faser; Ex-ante, Avtal och Ex-post och belyser de transaktionskostnader som uppstår under försäkringsprocessen. Litteraturstudien visar på en stark hype från forskningsvärlden där potentialen framhävs starkt. Även intervjustudien visar att det finns mycket potential för InsurTech, samtidigt som den även lyfter flera hinder och utmaningar för InsurTech i dagsläget. Sammantaget kommer uppsatsen fram till att InsurTechs potential i dagsläget främst finns i AI och Big data för att effektivisera datahantering och skadereglering. Samt att utvecklingen förmodligen kommer att ske från samarbete mellan etablerade försäkringsbolag och flera nya underleverantörer. / InsurTech is a new branch within the insurance industry that leverages innovative information technologies to streamline processes. Although the insurance industry has historically been slow-moving and resistant to change, interest in InsurTech has significantly increased in recent years, creating a considerable hype. Consequently, this thesis aims to analyse and assess whether InsurTech can have a substantial impact on the Swedish insurance market. By focusing on technologies such as Big Data, Artificial Intelligence, Telematics, and the Internet of Things, this thesis explores whether InsurTech can increase the efficiency of insurance processes and influence the market and its players. The study employs a qualitative methodology, beginning with a literature review to provide a comprehensive overview of the current academic perspective on Insurtech’s potential. This is followed by an interview study with industry experts to highlight their views on the potential and current implementable aspects of InsurTech within the industry. This study is grounded in a theoretical analysis model based on a transaction cost perspective. The model is structured into three phases: Ex-ante, Contract, and Ex- post, highlighting the transaction costs that arise during the insurance process. The literature review reveals significant hype from the academic community, emphasising the strong potential of InsurTech. While the interview study indicates considerable potential for InsurTech it also points out several current obstacles and challenges. Overall, the thesis concluded that the greatest potential currently lies in AI and Big Data to enhance data management and claims processing. Furthermore, the development is likely to occur through collaborations between established insurance companies and various new suppliers.

In the future, international Lunar missions will include both surface and lava tunnel EVA explorations, together with the collection of soil composition and ground data. Some issues with the realization of these activities are the communication constraints between the astronauts and the ground base on the Moon’s surface (especially in the first phases of Lunar exploration, when the satellite communication network will be under-supplied), and the limited area that a classical ground analyzing scientific instrument can cover. A solution to those issues has already been explored by previous interns at Spaceship EAC, resulting in a set of hardware prototypes communicating via LoRa protocol in an Internet of Things network configuration. The main idea behind these devices is to act both as signal transmitters and receivers, bridging the astronaut’s EVA suit to the ground base, and as a broad sensor network, capable of collecting a large amount of ground data from a vast area (crucial, for example, because of the proven heterogeneity of lunar soil chemical composition between different zones).This thesis explores the feasibility of miniaturizing these prototypes and creating a new set of smaller units with enhanced functionalities and performance. The designed device is called CRUMB (Compact Radio Unit for Moon data Broadcasting), and each unit is capable of communicating to other CRUMBs via LoRa frequencies (868 MHz – standard for European applications) while answering to an IoT mesh protocol. Via an accelerometer sensor, the CRUMB units are also able to send gravimetry data to the rest of the mesh, and to send an emergency communication whenever a moonquake is detected. Moreover, CRUMB’s volume is 92% smaller than its predecessor’s, and it nominally operates with a low power consumption (less than 1 W). / I framtiden kommer internationella månuppdrag att omfatta EVA-utforskning av både ytan och lavatunnlar, tillsammans med insamling av jordsammansättning och markdata. Några problem med att genomföra dessa aktiviteter är kommunikationsbegränsningarna mellan astronauterna och markbasen på månens yta (särskilt under de första faserna av månutforskningen, när satellitkommunikationsnätverket kommer att vara underförsörjt) och det begränsade område som ett klassiskt markanalyserande vetenskapligt instrument kan täcka. En lösning på dessa problem har redan utforskats av tidigare praktikanter vid Spaceship EAC, vilket har resulterat i en uppsättning hårdvaruprototyper som kommunicerar via LoRa-protokollet i en Internet of Things-nätverkskonfiguration. Huvudidén bakom dessa enheter är att fungera både som sändare och mottagare av signaler, som en brygga mellan astronautens EVA-dräkt och markbasen, och som ett brett sensornätverk som kan samla in en stor mängd markdata från ett stort område (avgörande, till exempel på grund av den bevisade heterogeniteten i månjordens kemiska sammansättning mellan olika zoner).I denna avhandling undersöks möjligheten att miniatyrisera dessa prototyper och skapa en ny uppsättning mindre enheter med förbättrade funktioner och prestanda. Den designade enheten kallas CRUMB (Kompakt Radioenhet för Utsändning av Måndata), och varje enhet kan kommunicera med andra CRUMB-enheter via LoRa-frekvenser (868 MHz - standard för europeiska tillämpningar) och samtidigt svara på ett IoT mesh-protokoll. Via en accelerometersensor kan CRUMB-enheterna också skicka gravimetridata till resten av nätet och skicka ett nödmeddelande när en månbävning upptäcks. CRUMB:s volym är dessutom 92% mindre än föregångarens och den nominella energiförbrukningen är låg (mindre än 1 W).

The concept of a digital twin was originated by Nasa who used advanced simulation techniques during their first moon landing but has since evolved and the areas of application have broadened considerably. In recent years, the phenomenon has received a lot of attention in relation to the real estate industry in particular, which have been followed by plenty of research into digital twins within the informatics field. However, there is still a great lack of studies that focus on the supplier’s perspective of the implementation. Therefore, the aim of this study is to identify the root causes of perceived challenges with digital twins from a supplier perspective by identifying what gives rise to problems and difficulties with the implementation of digital twins. This research contributes empirically by delving into the supplier's viewpoint, enhancing theoretical understanding through the identification of underlying causes, and practically by proposing ways to manage these foundational challenges effectively. The findings underscore the importance of addressing the knowledge gap between suppliers and clients early in the implementation process, recommending organizational and technical strategies to optimize digital twin utilization and management.

The IoT concept has revolutionised the vision of the future Internet with the advent of standards such as 6LoWPAN making it feasible to extend the Internet into previously isolated environments, e.g., WSNs. The abstraction of resources as services, has opened these environments to a new plethora of potential applications. Moreover, the web service paradigm can be used to provide interoperability by offering a standard interface to interact with these services to enable WoT paradigm. However, these networks pose many challenges, in terms of limited resources, that make the adaptability of existing IP-based solutions infeasible. As traditional service discovery and selection solutions demand heavy communication and use bulky formats, which are unsuitable for these resource-constrained devices incorporating sleep cycles to save energy. Even a registry based approach exhibits burdensome traffic in maintaining the availability status of the devices. The feasible solution for service discovery and selection is instrumental to enable the wide application coverage of these networks in the future. This research project proposes, TRENDY, a new compact and adaptive registry-based SDP with context awareness for the IoT, with more emphasis given to constrained networks, e.g., 6LoWPAN It uses CoAP-based light-weight and RESTful web services to provide standard interoperable interfaces, which can be easily translated from HTTP. TRENDY's service selection mechanism collects and intelligently uses the context information to select appropriate services for user applications based on the available context information of users and services. In addition, TRENDY introduces an adaptive timer algorithm to minimise control overhead for status maintenance, which also reduces energy consumption. Its context-aware grouping technique divides the network at the application layer, by creating location-based groups. This grouping of nodes localises the control overhead and provides the base for service composition, localised aggregation and processing of data. Different grouping roles enable the resource-awareness by offering profiles with varied responsibilities, where high capability devices can implement powerful profiles to share the load of other low capability devices. Thus, it allows the productive usage of network resources. Furthermore, this research project proposes APPUB, an adaptive caching technique, that has the following benefits: it allows service hosts to share their load with the resource directory and also decreases the service invocation delay. The performance of TRENDY and its mechanisms is evaluated using an extensive number of experiments performed using emulated Tmote sky nodes in the COOJA environment. The analysis of the results validates the benefit of performance gain for all techniques. The service selection and APPUB mechanisms improve the service invocation delay considerably that, consequently, reduces the traffic in the network. The timer technique consistently achieved the lowest control overhead, which eventually decreased the energy consumption of the nodes to prolong the network lifetime. Moreover, the low traffic in dense networks decreases the service invocations delay, and makes the solution more scalable. The grouping mechanism localises the traffic, which increases the energy efficiency while improving the scalability. In summary, the experiments demonstrate the benefit of using TRENDY and its techniques in terms of increased energy efficiency and network lifetime, reduced control overhead, better scalability and optimised service invocation time.