With the Internet of Things becoming more and more popular, and a prediction that there will be more than 50 million devices connected to the Internet in 2020, the quantity of IoT platforms on the market is rapidly growing. Facing so many platforms to choose, the object of this thesis is to give some suggestions for reference by performing a quantitative comparison between two platforms: SensibleThings and Kaa. These two platforms have difference architectures so may suitable in different scenes. The comparison includes some measurement and evaluation under two designed scenarios and a general contrast in theory. Two scenarios cover cases of message delivery between two endpoints at different rates and multiple endpoints pushing log data continually. The result of measurement together with the theoretical analysis draw out the following conclusion. SensibleThings platform is more suitable for simple and small-scale message delivery between endpoints, like home environment with few devices. And Kaa platform is more suitable for large-scale and complicated application for data collection and processing, like meteorology field with huge amount of sensors and data.

Internet of Things (IoT) platforms enable users to connect heterogeneous resource-constrained wireless devices and deploy semantics-rich home automation applications in smart homes. With the proliferation and fragmentation of IoT products, it even becomes a status quo that many smart IoT devices in a smart home are bounded or delegated to multiple IoT platforms, demonstrating the following characteristics. First, an IoT device may interact with more than one IoT platform. Second, a device can be accessed via multiple communication channels (e.g., Zigbee and Bluetooth). Third, automation applications or rules in a smart home may scatter on different platforms, mainly because each platform has its own strengths and restrictions on the supported IoT devices (e.g., many Google Nest devices are not compatible to work with the Amazon platform) and programming features. Despite the convenience brought by the modern platform-backed systems, a variety of attacks targeting the devices, applications and their interactions arise, which can put the smart home devices to insecure, unsafe, or unexpected states, or can breach users' private information in the daily life. In this dissertation, several semantics-aware security and privacy issues are discussed, analyzed and handled. In one way, we systematically categorized a family of cross-app interference threats and designed a Satisfiability modulo theories (SMT)-based solution to detect them. In another work, we revealed a family of delay-based automation interference attacks that cause cross-rule interference problems in multi-platform multi-path systems. We also studied privacy protection of IoT systems and proposed a semantics-aware customizable data flow control system to protect IoT data from being exploited by third parties and attackers. We also established a command sanitizer solution for detecting cross-app interference problems in multi-platform systems and enforce security and safety policies against various IoT threats. All the works were evaluated in real-world smart home testbeds. / Computer and Information Science

The Industrial Internet of Things (IIoT) holds great potential for fostering innovation across various industries. This study explores the role of boundary resources (BR) in catalyzing this potential, specifically focusing on the experiences and challenges faced by data scientists within IIoT platforms. In a qualitative research approach, semi- structured interviews were conducted with eight data scientists that uncovered how specific BR related to metadata management, tool integration, business models, and API design might impact their work and the innovative environment. The analysis reveals that these BR are essential in shaping the effectiveness of IIoT platforms but often fall short in meeting the unique needs of data scientists, thereby inhibiting innovation. The findings suggest that an actor-centric redesign of BR, emphasizing the specialized workflows and technical demands of data scientists, might enhance the flexibility and functionality of IIoT platforms. Platform owners are encouraged to adopt adaptable and dynamic BR designs to leverage data scientists' diverse capabilities and insights, especially in business-to-business (B2B) environments.

Teknologi påverkar alla delar av samhället, inte minst företag och organisationer somtvingas till digitalisering för att förbli relevanta. Internet of Things (IoT) är en populärteknologi för effektivisering och automation av processer.Den teknologiska utvecklingen sker i en takt som gör att det kan vara svår att integrerateknologi i kulturella och sociala sammanhang. För att hantera de utmaningar somdigitalisering medför behöver variabler som samarbete utvecklas för att man ska kunnadra nytta av teknologins utveckling i miljöer som arbetsplatser och städer.Denna studie har därför tagit ansats i ett kommunalt samarbete rörandeimplementeringen av en verksamhetsgemensam IoT-plattform. Studien har ämnatundersöka de omständigheter som ligger till grund för interkommunala samarbetenmellan förvaltningar och bolag vars gemensamma mål är att utgöra en smart stad (eng.smart city) med hjälp av Internet of Things.Detta arbete har bedrivits som en fallstudie vars föremål för undersökning har varitJönköpings kommun. Undersökningen har tagit en kvalitativ ansats och haft sin grundi semistrukturerade intervjuer vars subjekt har utgjorts av ett urval av representanter förnoga utvalda verksamheter inom kommunens regi.Resultaten av datainsamlingen visade att det finns en stark koppling mellanvälfungerande interkommunala samarbeten och ett övergripande gemensamt synsättmed etablerade informationskanaler. En avgörande faktor för framgångsrikasamarbeten har visat sig vara att involvera samtliga delar av organisationen för att dranytta av insikter och kompetenser som finns i olika skikt av verksamheterna ochetablera ett gemensamt tankesätt. Resultatet har lett fram till upptäckten att nyttogradenav samarbeten framför allt ligger i att identifiera verksamheter med gemensammaintressen och behov.Denna studie har lagt grunden för att utreda aspekter av samarbete mellan olikaverksamheter och öppnar upp för vidare forskning på samarbeten inom organisationeroch företag med fokus på den interna verksamhetens struktur. / Technology impacts all aspects of society, especially businesses and organizations thatare forced to undergo digitalization to remain relevant. Internet of Things (IoT) is apopular technology used for streamlining and automation of processes.The rapid pace of technological development makes it challenging to integrate it intocultural and social contexts. To address the challenges brought by digitalization,variables such as collaboration need to be developed in order to take advantage oftechnological advancements in environments such as workplaces and cities.This study has therefore focused on a municipal collaboration regarding theimplementation of a shared IoT platform. The study aimed to examine thecircumstances underlying intermunicipal collaborations between departments andcompanies with a common goal of creating a smart city using the Internet of Things.This work has been conducted as a case study with Jönköping Municipality as thesubject of investigation. The study took a qualitative approach and was based on semi-structured interviews with representatives from selected departments within themunicipality.The results of the data collection showed a strong connection between well-functioningintermunicipal collaborations and an overall shared mindset with establishedcommunication channels. A crucial factor for successful collaborations has been theinvolvement of all parts of the organization in order to leverage insights and expertisefrom different layers of the operations and establish a common mindset. The findingshave led to the discovery that the degree of novelty in collaborations primarily lies inidentifying operations with common interests and needs.This study has laid the foundation for investigating aspects of collaboration betweendifferent operations and opens for further research on collaborations withinorganizations and companies with a focus on the internal operational structure.

The Internet of Things (IoT) has seen a huge growth spurt in the last few years which has resulted in the need for more standardised IoT technology. Because of this, numerous IoT platforms have sprung up that offer a variety of features and use different technologies which may not necessarily be compliant with each other or with other technologies. Companies that wish to enter theIoT market are in constant need to find the most suitable IoT platform for their business and have a certain set of requirements that need to be fulfilled by the IoT platforms in order for the application to be fully functional. The problem that this thesis project is trying to address is a standardised procedure for selecting the IoT platforms. The project aims to suggest a list of requirements derived from the available IoT architecture models, that must be followed by IoT applications in general, and a subset of these requirements may be specified by the companies as essentials for their application. This thesis project also aims at development of a Web platform to automate this process, by listing the requirements on this website and allowing companies to input their choices,and accordingly show them the list of IoT platforms that comply with their input requirements. A simple Weighted Sum Model is used to rank the search result in order to prioritise the IoT platforms in order of the features that they provide. This thesis project also infers the best IoT architectural model available based on a comparative study of three major IoT architectures with respect to the requirements proposed. Hence the project concludes that this Web platform will ease the process of searching for the right IoT platform andthe companies can therefore make an informed decision about the kind of IoT platform that they should use, thereby reducing their time spent on market research and hence their time-to-market.