The United States Federal Communications Commission (FCC) in its recent report and order has prescribed the creation of Citizens Broadband Radio Service (CRBS) in the 3.5 GHz band to enable sharing between wireless broadband devices and incumbent radar systems. This sharing will be enabled by use of geolocation database with supporting infrastructure termed as Spectrum Access System (SAS). Although using SAS for spectrum sharing has many pragmatic advantages, it also raises potentially serious operational security (OPSEC) issues. In this thesis, we explore OPSEC, location privacy in particular, of incumbent radars in the 3.5 GHz band. First, we show that adversarial secondary users can easily infer the locations of incumbent radars by making seemingly innocuous queries to the database. Then, we propose several obfuscation techniques that can be implemented by the SAS for countering such inference attacks. We also investigate obfuscation techniques' efficacy in minimizing spectral efficiency loss while preserving incumbent privacy. Recently, the 3GPP Rel.13 has specified a new standard to provide wide-area connectivity for IoT, termed as Narrowband IoT (NB-IoT). NB-IoT achieves excellent coexistence with legacy mobile standards, and can be deployed in any of the 2G/3G/4G spectrum (450 MHz to 3.5 GHz). Recent industry efforts show deployment of IoT networks in unlicensed spectrum, including shared bands (e.g., 3.5 GHz band). However, operating NB-IoT systems in the 3.5 GHz band can result in significant BLER and coverage loss. In this thesis, we analyse results from extensive experimental studies on the coexistence of NB-IoT and radar systems, and demonstrate the coverage loss of NB-IoT in shared spectrum. / Master of Science / Spectrum sharing has been viewed by spectrum regulators and industry stakeholders as the most viable solution to overcome the spectrum congestion and to enable next generation wireless networks. Towards this end, the Federal Communications Commission in the United States has prescribed rules to enable sharing between incumbent radars and broadband wireless networks in the 3.5 GHz band. This sharing however will be enabled geolocation databases and supporting infrastructure known as Spectrum Access System, which are prone to privacy attacks by malicious secondary users. Preserving privacy of incumbent systems is vital as they are mostly military radars. In this thesis, we demonstrate such attacks and later propose efficient techniques to preserve the privacy of the incumbent systems while enabling better spectrum utilization. The phenomenal growth in smarter end-user devices and machine-to-machine (M2M) connections is a clear indicator of the growth of Internet of Things (IoT), and growing importance of wide area IoT networks. Recently, the telecommunications standard development body, 3GPP, has defined Narrowband IoT (NB-IoT) optimized for IoT. Also, NB-IoT has many features common to LTE, and it is likely that NB-IoT will also be deployed in bands where LTE will be deployed, including shared bands (e.g., 3.5 GHz band). However, NB-IoT systems that operate in the 3.5 can be prone to harmful radar interference and directly impact coverage of the NB-IoT basestation. In this thesis, we analyse results from extensive experimental studies on the coexistence of NB-IoT and radar systems. We believe this study can be leveraged by future studies to mititage the impact of radar on IoT networks.

Yes / Welcome to this special issue of the Future Generation Computer Systems (FGCS) journal. The special issue compiles seven technical contributions that significantly advance the state-of-the-art in exploration of Internet of Things (IoT) generated big data using semantic web techniques and technologies.

Yes / The exponential growth of the Internet of Things (IoT) has paved the way for safety-critical cyber-physical systems to enter our everyday activities. While such systems have changed the way of our life, they brought new challenges that can adversely affect our life and the environment. Safety and security are two such challenges that can hamper the widespread adoption of new IoT applications. Due to a large number of connected devices and their ability to control critical physical assets, intended attacks on them and/or unintended failure events such as mechanical failure of devices, communication failure and unforeseen bad interactions between connected devices may cause an IoT-based system to enter into unsafe and dangerous physical states. By considering the importance of safety and security of IoT systems, in this article, we present a security-enabled safety monitoring framework for IoT-based systems. In the proposed framework, we utilise design-time system analysis to create an executable monitoring model that enables run-time safety assurance provision for a system via collecting and analysing operational data and evidence to determine the safety status of the system and then taking appropriate actions and securely communicating the safety status and recommended actions to the system users to minimise the risk of the system entering into an unsafe state.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第23547号 / 情博第777号 / 新制||情||132(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 大木 英司, 教授 原田 博司, 教授 黒橋 禎夫 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Smart home appliances have been argued to have a transformative impact on our daily lives in the future. Through the technology Internet of Things, smart home appliances are able to collect data from our surroundings and offer customs services. They have the possibility to automate daily tasks and contribute to energy saving, security, and more. Though smart home appliances can offer several benefits, concerns exist about data collection and research gaps as previous research has mainly been applied from a technical standpoint and less on a societal one. Research on different target groups and contexts is needed as it is important when creating digital services. One of these target groups that needs further research is students and their perspective on smart home appliances. As such, this study has focused on students' expectations of smart home appliances in future student housing, thereby shifting focus from a technical perspective to a societal one by using group- and follow-up interviews. The outcome contributes to an increased understanding of students’ aspects and expectations when creating smart home appliances in student homes. These insights can assist developers, researchers and designers in creating future smart home services, custom for students.

This report contributes to the ArtEmis project, a multidisciplinary initiative designed to enhance earthquake forecasting through sensor technology. By utilizing a sensor unit that measures radon levels—a potential precursor to seismic activity—the project seeks to develop predictive capabilities. Central to this report is the evaluation and enhancement of the acquisition electronics critical to sensor functionality. The study involves testing and monitoring of the initial set of sensor systems deployed across various locations in Southern Europe, with specific attention given to electronic components like the gateway and its connectivity options. The findings reveal that the D-Link DWR-932 router, originally used for network connectivity, is unsuitable due to poor performance. Consequently, this report recommends replacing the D-Link router with more reliable alternatives such as the SIM7600G-H modem and the Rut241 router, either individually or in combination, to enhance the system’s reliability and overall performance.

Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Gebäudeoptimierung. Grundlage für eine ganzheitliche Gebäudeüberwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplinäre Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgebäude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Gebäudezwilling entsteht. Dieser kann zur Optimierung des Gebäudebetriebs herangezogen werden, sowie als Basis für eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und künstlicher Intelligenz kann so ein präzises Monitoring wichtiger Gebäudedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Gebäudezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Gebäuden untersucht und konkrete Lösungen für die Gebäudeoptimierung entwickelt.

Den tekniska utvecklingen har möjliggjort ett mer uppkopplat samhälle genom enklare informationstillgång och mer avancerad informationshantering. Den här framfarten har legat till grund för utveckling av samlingsbegreppet Internet of Things, där automatiserade datainsamlingssystem är betydande för insamling av mer kvantitativa datamängder. Detta har lett till att företag inom flera olika industrier har integrerat tekniken i delar av verksamheten för att samla in en betydande datamängd i syfte att utveckla och förbättra de egna processerna. Intresset och framförallt behovet av den här typen av teknologi finns inom byggindustrin. För ett byggföretag som vill arbeta med digitala lösningar i deras arbete gäller att skapa förståelse för varför den typen av lösning ska användas och hur den kan nyttjas på bästa sätt. Vid implementering och anpassning av en ny teknik är det nödvändigt för företag att identifiera vilka möjligheter och hinder som kan uppstå. Därav är syftet med studien att undersöka möjligheten att samla in realtidsdata genom en automatiserad insamlingsprocess i produktionsfasen hos ett byggföretag. Vidare undersöks hur processen bidrar till kvalitetssäkring och ständiga förbättringar i byggprojekten. Detta för att skapa medvetenhet hos byggföretag om en ny teknik som kan underlätta deras arbete och hindra uppkomst av problem. En fallstudie har genomförts hos byggföretaget JM AB som har en lång erfarenhet av byggprocesser och byggprojekt. För att skapa förståelse kring studiens ämne och slutsatser har en en teoretisk referensram innehållandes teorier om bland annat kvalitetssäkring och datainsamling byggts upp. Genom tio intervjuer med anställda av olika befattningar, två observationer på ett av fallföretagets byggprojekt och en intervju med ett externt företag sammanställdes en empirisk undersökning. På så sätt erhölls insikt i hur fallföretaget arbetar med datainsamlingsprocesser och vilka tekniker som finns på marknaden. Genom analys av fallstudien framkom det tydligt att fallföretaget inte har välutarbetade datainsamlingsprocesser inom flera områden i byggproduktionen. En viktig slutsats i studien är att användandet av ett processinnovationsramverk kan skapa förutsättningar för en effektiv och automatiserad datainsamlingsprocess. Ramverket ger stöd till huruvida en automatisk datainsamlingsprocess är lönsamt samt skapar förståelse kring processen innan den är redo att implementeras. Dessutom möjliggör en automatiserad datainsamlingsprocess kvalitetsförbättringar med hjälp av ett kvalitetskontrollramverk som kan öka kvaliteten genom att reducera problem och lösa dem fortare. Kvalitetskontrollerna blir systematiska och utifrån genererad data kan jämförelser göras för att identifiera defekter så att arbete mot snabbare handlingsåtgärder kan skapas. Utifrån slutsatserna har fyra rekommendationer tagits fram, den första är att använda processinnovationsramverk vid undersökning av en ny automateringsprocess. Den andra är att testa automatiserade datainsamlingsprocesser i mindre projekt för att erhålla ökad förståelse. Den tredje är att systematiskt arbeta med ett kvalitetskontrollramverk utifrån genererad data. Den sista rekommendationen är att använda insamlad data till faktabaserade beslut och sträva mot ständiga förbättringar. / Technological developments have enabled a more connected society with easier access to information that creates opportunities for more advanced information management. This has been the basis for development of the generic term Internet of Things, where automated data collection systems are significant for the collection of quantitative data set. Companies in various industries are embracing the integration of this type of technology in their businesses to generate data that is possessed to improve their processes. The interest and especially the need for this type of technology is huge in the construction industry.   For construction companies that wants to work with digital solutions, it is important to create an understanding of why this type of solution is to be used and how it best can be utilized. In implementation and adaption of a new technology, it is necessary for companies to identify the opportunities and obstacles that may arise. Hence, the purpose of this study is to examine the feasibility of collecting real-time data through an automated collection process in the production phase at a construction company, and how it contributes to quality assurance and continuous improvement in construction projects. In this way, awareness among construction companies of a new technique can facilitate their work and prevent upcoming problems. A case study has been carried out at the construction company JM AB who has a long experience of construction processes. To create an understanding about the study topic and conclusions, a theoretical framework was compiled including theories about quality assurance and data collection. Through ten interviews with employees of different positions, two observations at one of the case company’s construction projects and one interview with an external company, an empirical study was compiled. In this way, insights were obtained into how the case company is working with data collection processes and what techniques that are available on the market. Through analysis of the case study, it crearly appeared that the case company does not have well-developed data collection processes in several areas of the building production. One important conclusion of the study is that the use of a process innovation framework can create conditions for an efficient and automated data collection process. The framework supports whether an automated data collection process is profitable and it creates an understanding of the process prior of its implementation. Another important conclusion is that an automated data collection process allows quality improvements through the help of a quality control framework that can increase the quality by reducing problems and solving them faster. Hence, quality controls become systematic and based on generated data, comparisons can be made to identify defects in order to work systematically toward faster action measures. Based on the findings, four recommendations were developed. The first one is to use process innovation framework for the examination of a new automatic process. The second is to test automated data collection processes into smaller projects to obtain greater understanding. The third is to work systematically on a quality control framework based on generated data. The last recommendation is to use the collected data for fact-based decisions and to strive for continuous improvement.

The need of smart devices that uses sensors have never been higher and by the year 2020 it will be over 50 billion devices connected to the internet. All these devices that uses a sensor and are connected to the internet are a part of something called Internet of Things. The purpose of this study has therefore been to implement a stripped IoT platform that doesn’t use any external libraries to lower the cost for minor companies that doesn’t need the more advanced and expensive platforms. After the implementation various stress test will be performed to see the performance of the platform. The study has been done through web- based sources and as a programming language Java has been used in the development environment NetBeans, the database has been made with MySQL workbench. The result of the study has been a platform that uses REST to post and get data from the database. The external library mysql- connector-java-5.1.45 was essential for a connection to the database and therefore had to be used. The result of the stress test was that the platform performed well and could handle at least 500 REST calls per second with a small increase in response time, but the standard deviation was considerably higher. The conclusion was that the platform performed stable at 50 – 250 calls per second and because of it being stripped several platforms could be used in a company to divide the work load between them resulting in a both stable and scalable solution. / Behovet för smarta enheter som använder sensorer har aldrig varit högre och det är trott att vid år 2020 kommer mer än 50 miljarder enheter vara uppkopplad mot internet. Alla dessa enheter med sensorer som är anslutna mot internet går under namnet Internet of Things. Syftet med denna studie har därför varit att skapa en avskalad IoT plattform som inte använder externa bibliotek för att hålla ned kostnaderna för de mindre företagen som inte behöver de mer avancerade och dyrare plattformarna. Efter att plattformen blivit implementerad skulle stresstester utförs för att avgöra hur bra den presterar. Studien har genomförts med hjälp av webbaserade källor och programmeringen av plattformen har utförts i programmeringsmiljön NetBeans i språket Java och databasen är skapad i MySQL workbench. Resultatet av studien har gett en plattform som använder REST för att skicka till och hämta data från databasen. Att göra implementeringen utan att använda externa bibliotek gick inte då biblioteket mysql-connector-java-5.1.45 var essentiellt för uppkoppling mot databasen. Stresstesterna gav att plattformen presterade stabilt och kunde hantera åtminstone 500 REST förfrågningar per sekund med endast en liten ökning i svarstiden, dock blev standardavvikelsen för svarstiden betydligt högre. Slutsatsen av studien blev att eftersom plattformen fungerar stabilt för 50 – 250 förfrågningar per sekund och då den tar upp lite processorkraft kan flera plattformar användas i ett företag för att då fördela arbetskraften emellan dem vilket resulterar i en lösning som både är skalbar samt stabil.

A Internet das Coisas, ou Internet of Things (IoT), representa um novo paradigma de integração de várias tecnologias e soluções de comunicação e encontra aplicações em muitos domínios diferentes, tais como ambientes inteligentes (residencial e comercial), automação industrial, saúde, agricultura de alta precisão, gerenciamento inteligente de energia (smart grids, conservação de energia em edifícios), transporte e logística, setor automotivo em geral, cidades inteligentes e muitas outras áreas. A realização da visão de IoT ainda necessita de mais investimentos em pesquisa e desenvolvimento devido à sua novidade e complexidade. Além das questões técnicas, a adoção em larga escala também é dificultada pela falta de clareza dos fatores determinantes na decisão de adoção destas tecnologias. A questão- problema que esse trabalho de pesquisa busca elucidar é o desafio da adoção de inovações baseadas na Internet das Coisas, mais especificamente fatores que afetam a decisão de adoção. O tema adoção de inovação é relevante para quem desenvolve a inovação e deseja que ela seja adotada e para quem tem que decidir se adota ou não uma inovação. Como a taxa de adoção é influenciada por fatores e decisões tanto do lado de quem fornece quando do lado de quem adota uma determinada inovação tecnológica, o trabalho se baseia em estudos que buscam integrar as diversas variáveis afim de refletir a natureza sistêmica deste processo. O modelo proposto pode ser aplicado tanto para quem adota quanto para quem fornece a inovação, integrando questões externas e internas à empresa, bem como questões da tecnologia IoT em si e do fornecedor. A pesquisa utiliza o modelo proposto em três estudos de caso com o objetivo de identificar e analisar os fatores de decisão de adoção da Internet das Coisas nas respectivas empresas, e apresenta sugestões de como aplicar o modelo na avaliação e eventual seleção de inovações tecnológicas, tanto do ponto de vista de quem fornece quanto de quem adota a inovação. / The Internet of things (IoT) represents a new paradigm of integration of various technologies and communication solutions, and finds applications in many different domains, such as intelligent environments (residential and commercial), industrial automation, health, high precision agriculture, intelligent power management (smart grids, energy conservation in buildings), transport and logistics, the automotive industry in general, smart cities and many other areas. The realization of the vision of IoT still requires more investment in research and development because of its novelty and complexity. Beyond the technical issues, large-scale adoption is also hampered by the lack of clarity of the determining factors in the decision of adoption of these technologies. The problem this research seeks to elucidate is the challenge of adopting innovations based on the Internet of things, more specifically factors that affect the adoption decision. The theme adoption of innovation is relevant to those who develop an innovation and want it to be adopted as well as for those who have to decide whether to adopt an innovation or not. As the adoption rate is influenced by factors and decisions that lie both on the side of the supplier as well as the adopter of a particular technological innovation, this work is based on studies that seek to integrate variables from both sides in order to reflect the systemic nature of this process. The proposed model can be applied to both suppliers and adopters of the technological innovation, integrating factors that are external and internal to the company, as well as factors of the IoT technology and factors of the supplier. This research used the proposed model in three case studies in order to identify and analyze the factors of decision of adoption of the Internet of things in each company, and offers suggestions of how to apply the model in the evaluation and eventual selection of technological innovations, both from the point of view of suppliers as well as adopters of the innovation.