Denna rapport beskriver ett kandidatarbete som utfördes av åtta studenter i kursen TDDD96 - Kandidatprojekt i programvaruutvecklingvid Linköpings universitet våren 2021. Projektet handlade om att skapa ett system för att spåra och visualisera förekomsten av farliga ämnen som kan förekomma på olycksplatser och på så sätt underlätta räddningstjänstens arbete. Resultatet av projektet bestod av en sensorenhet som fästs på räddningspersonalens hjälm. Sensorenheten detekterar halten butan, vätgas, ammoniak, sulfider och bensen i luften och skickar dessa värden tillsammans med GPS och acceleration till en instrumentbräda. Där visas all data och kan användas avbakre led. Rapporten beskriver projektets arbete beställt av forskningsgruppen Ubiquitous Computing and Analytics Group vid Institutionen för Datavetenskap på Linköpings universitet. Teorin kring systemet lägger grunden till förståelse av rapporten, samt hur arbete kan effektiviseras med hjälp av till exempel Scrum, parprogrammering och ärendespårning (eng.issue tracking). Rapporten redovisar även projektets resultat och hur den slutgiltiga produktens hårdvara, server och användargränssnitt fungerar. Till sist presenteras gruppmedlemmarnas individuella bidrag som innehåller djupdykningar inom olika områden med koppling till projektet.

Design is all about visuals, or that is what I have found out during this thesis, from the process materials to the outcome our main entry point to any problem is how will we solve it visually so it’s understandable for the general user. This aspect is problematic in itself due to the fact that we, as humans, understand the world and the things around using all our senses continuously, even though we can forget as visuals are so overpowering. There is a huge opportunity area in exploring our other senses and bringing them back to technology, and this can be seen in works in the past like Tangible Interactions [1] or Natural User Interfaces [2]. But in this moment in time, where all these new technologies like VR/AR and IoT are about to enter our lives and change them forever, this topic is more important than ever. We have already seen what happens when we turn humans into mere machines with some fingers as interactive inputs, and barely any senses to process all the information given to us. Now that these technologies are still young and malleable, we can direct the future to where we want it instead of being guided by the technology itself. To do this we need to reimagine the design process, not reinvent the wheel, but add experts which we currently leave behind and I argue are key to unlock these technologies, experts not only of the technological side of things but on the human side too, like physiotherapists and dancers. Add also people who we never think about when we think of VR like visually impaired users, which could make these technologies inclusive since early on, instead of as an afterthought like we usually do. Not only people, but we also need to add new materials to understand how we use our senses and explore ways that we can understand and explore them differently; like bodystorming and improv theatre because when things aren’t visual, how do you sketch it? A sketch turns into a video about movement. The end result provides a wide breadth of examples of the types of innovations that can come out of using these new design materials, and to open new frontiers. From a VR game with no visuals whatsoever to an AR location based story game, to a home sized multimodal operating system containing several different apps controlled through physical movement. The examples open up the space instead of closing into a single solution. This is just the tip of the iceberg, a hope that others will be inspired by it and continue with this journey that has just started, to guide the future into one that is more technological and at the same time more human than ever before. What we know is that VR does not equate Visual Reality.

Due to the influence of information fusion in Industrial Internet of Things (IIoT) environments, there are many problems, such as weak intelligent visual target positioning, disappearing features, large error in visual positioning processes, and so on. Therefore, this paper proposes a weak target positioning method based on multi-information fusion, namely the “confidence interval method”. The basic idea is to treat the brightness and gray value of the target feature image area as a population with a certain average and standard deviation in IIoT environments. Based on the average and the standard deviation, and using a reasonable confidence level, a critical threshold is obtained. Compared with the threshold obtained by the maximum variance method, the obtained threshold is more suitable for the segmentation of key image features in an environment in which interference is present. After interpolation and de-noising, it is applied to mobile weak target location of complex IIoT systems. Using the metallurgical industry for experimental analysis, results show that the proposed method has better performance and stronger feature resolution.

Cloud computing is about delivery of different computing services involving databases, analytics, software, networking with the use of internet to enhance innovation, incorporate flexibility in resources and broaden profitability. However, Internet of Things (IoT) is an essential system for interrelating computer devices, digital machines, people and others which are offered with unique identifiers where data can be transferred with human involvement and wireless network. 42% of organisations in UK use cloud computing. The problem with cloud computing revolves around security and privacy issues as data is stored by a third party from inside or outside of the organisation leading to broken authentication, compromising of credentials and others. The use of IoT is vulnerable as it provides connectivity to devices, machines and people therefore, it needs to contain more storage that is made from cloud facilities. Survey has been conducted where primary quantitative method has been considered to obtain data from 101 managers of the organisation that has adopted cloud computing and IoT. However, 8 close-ended questions have been asked to 101 managers. Positivism philosophy has been used to make quantifiable observations along with descriptive design and others. The results and discussion will analyse responses of the respondents after conducting statistical analysis. However, research has been revolving around making a comparison between using cloud computing and IoT along with analysing organisational behaviour. / Revisión por pares

The application of Internet of Things (IoT) where sensors and actuators embedded in physical objects are linked through wired and wireless networks has shown a rapid growth over the past years in various domains with the benefits of improving efficiency and productivity, reducing cost, providing mobility and agility, etc. This dissertation focuses on developing signal processing and machine learning based techniques in IoT with applications to 1) smart energy generation and 2) robust indoor localization in smart city. Smart grids, in contrast to legacy grids, facilitate more efficient electricity generation and consumption by allowing two-way information exchange among various components in the grid and the users based on the measurements from numerous sensors located at different places. Due to the introduction of information communications, a smart grid is faced with the risk of external attacks which is aimed to take control of the grid. In particular, electricity generation from photovoltaic (PV) systems is a mature power generation technology utilizing renewable resources, owning to its advantages in clean production, reduced cost and high flexibility. However, the performance of a PV system can be susceptible and unstable due to various physical failures and dynamic environments (internal circuit faults, partial shading, etc.). To safeguard the system security, fault or attack detection technologies are of great importance for PV systems and smart grids. Existing approaches on fault or attack detection either rely on the prediction by a predetermined system model which acts as reference data for comparison or can be applied only within a certain set of component (e.g., several PV strings) based on local statistical properties without the capability of generalization. Furthermore, the output performance of a PV system is dynamic under different environmental conditions (irradiance level, temperature, etc.), which can be optimized by the technique of maximum power point tracking (MPPT). However, previous studies on MPPT usually require prior knowledge of the system model or high computational complexity for iterative optimization. Smart city, as another important application of IoT, relies on analysis of the measurement data from sensors located at users and environments to provider intelligent solutions in our daily life. One of the fundamental tasks for advanced location-based services is to accurately localize the user in a certain environment, e.g., on a certain floor inside a building. Indoor localization is faced with challenges of moving users, limited availability of sensors and noisy measurements due to hardware constraints and external interferences. This dissertation first describes our advanced fault/attack detection and localization methods for PV systems and smart grids, then develops our enhanced MPPT techniques for PV systems, and finally presents our robust indoor localization methods for smartphone users, based on statistical signal processing and machine learning approaches. In Chapter 2 and Chapter 3, we proposes fault/attack detection method in PV systems and smart grids respectively in the framework of abrupt change detection utilizing sequential output measurements without assuming any prior knowledge of the system characteristics or particular faulty/attack patterns, such that an alarm will triggered regardless of the magnitude or the type of faulty/attack signals. Starting from the proposed fault detection method in Chapter 2, we present our fault localization method for PV systems in Chapter 4 where the central controller is able to identify the faulty PV strings without full knowledge of each local measurements. Chapter 5 studies the MPPT method under dynamic shading conditions where we adopt neural networks to assist the identification of the global maximum power point by depicting the relationship between the system output power and the operating voltage. In Chapter 6, to tackle the challenge of accurate and robust indoor localization for smart city when sensors provides noisy measurement data, we propose a cooperative localization method which exploits the readings of the received strengths of Wi-Fi signals at the smartphone users and the relative distances among neighboring users to combat the deterioration due to aggregated measurement errors. Throughout the dissertation, our proposed methods are followed by simulations (of a PV system or a grid under various operating conditions) or experiments (of localizing moving users with smartphones to record sensors' measurements). The results demonstrate that our proposed fault/attack detection and localization methods and MPPT schemes can achieve higher adaptivity and efficiency with robustness against various external conditions an lower computational complexity, and our cooperative localization methods have high localization accuracy even given large measurement errors and limited measurement data.

The current network trends point towards a significant discrepancy between the data usage and the underlying architecture; a severely increasing amount of data is being sent from more devices while data usage is becoming more data-centric instead of the previously host-centric. Information Centric Network (ICN) is a new alternative network paradigm that is designed for a data-centric usage. ICN is based on uniquely naming data packages and making it location independent. This thesis researched how to implement an efficient naming for ICN in a Smart Home Scenario. The results are based on testing how the forwarding information base is populated for numerous different scenarios and how a node's duty cycle affects its power usage. The results indicate that a hierarchical naming is optimized for hierarchical-like network topology and a flat naming for interconnected network topologies. An optimized duty cycle is strongly dependent on the specific network and accordingto the results can a sub-optimal duty cycle lead to excessive powerusage.

Denna studie har undersökt hur användare av smarta hem-produkter i Sverige förhåller sig tillsin personliga integritet i relation till sitt användande av dessa produkter. Den har ocksåundersökt om användarvillkor är ett effektivt verktyg för att säkra ett giltigt informeratsamtycke från användare av smarta hem-produkter i Sverige. Studien vill bidra tillforskningssamhället genom att lyfta frågan om informerat samtycke i relation till IoT (Internetof Things). Det främsta syftet med studien är att förstå i vilken utsträckning konsumenter iSverige ger informerat samtycke till insamling och behandling av data i samband medanvändande av smarta hem-produkter.Studien genomfördes med en kombination av kvalitativa och kvantitativa metoder. Denkvalitativa undersökningen bestod av 6 semistrukturerade intervjuer och den kvantitativa av enwebbenkät med 207 respondenter. Resultatet som framkom genom undersökningarna stämdetill stor del överens med tidigare forskning om personlig integritet och informerat samtycke isamband med insamling av data. En minoritet av respondenterna läser användarvillkor och dengenerella kunskapen om datainsamling visade sig vara låg i förhållande till hur mycket mångarespondenter uppger att de värderar sin personliga integritet. Flera respondenter värderar sinbekvämlighet över den personliga integriteten, vissa genom sitt agerande och andra mer explicitgenom att uttrycka att det är ett val de gjort.Slutsatserna i denna studie överensstämde med tidigare studier. Respondenterna har eninkonsekvent relation till sin personliga integritet. De upplever villkor och avtal för sina smartahem-enheter som svåra att förstå och många vet inte vad de givit sitt samtycke till. / This study has examined how users of smart home devices in Sweden relate to their personalintegrity in relation to their use of these devices. It has also examined whether end useragreements are an effective tool for securing informed consent to the collection of data fromusers of smart home devices in Sweden. The study hopes to contribute to the research societywithin its field by raising the issue of informed consent in relation to Internet of Things. Themain purpose of this study is to understand to what extent users of smart home devices inSweden provide informed consent to the collection and use of their data.The study was conducted with a combination of qualitative and quantitative methods. Theresearcher conducted 6 semi structured interviews and a web survey with 207 respondents. Theresults collected through the surveys were consistent with several previous studies on personalintegrity and informed consent in connection with data collections. A minority of therespondents read end user agreements and the overall knowledge about data collection proved tobe low in comparison to how many respondents state that they value their personal integrity.Several respondents place a larger value on their convenience than their personal integrity, somethrough their actions and others more explicitly by expressing that it is a choice they have made.The conclusions in this study have been largely consistent with previous studies. Respondentshave an inconsistent relationship to their personal integrity. They experience major difficultieswith understanding end user agreements and privacy policies and many do not know what theyhave given their consent to in regard to their smart home devices.

Internet of Things (förkortat IoT) representerar den 4:e vågen av digitalisering och harsom fokus att koppla samman smarta enheter (eller Things). De flesta av dagens mobiltelefoner är utrustade med ett flertal sensorer och kamera. Augmented Reality har settutveckling inom industrin och hälsa de senaste åren. Ett återkommande problem för ubikdatateknik är dynamiska miljöer. I detta arbete tar vi dessa observationer i åtanke och medhjälp av Design Science Research Methodology utvecklar en prototyp som utnyttjar Augmented Reality för att visa information om enheter, eller Things, och utvärderar teknikensfördelar och nackdelar för detta syfte. Vi utforskar även Emergent Configurations sominspiration till design, samt design-principer som kan tillämpas i vår prototyp, genom enlitteraturstudie där vi utforskar tidigare studier. Vi finner att Augmented Reality kan användas för att visualisera IoT system och data och att det finns flera designprinciper och nackdelar att överväga. / Internet of Things (IoT for short) represents the 4th wave of digitization and focuses onconnecting smart devices (or Things). Most of today’s mobile phones are equipped withseveral sensors and a camera. Augmented reality has in recent years seen developmentwithin industry and health care. A recurrent problem for ubiquitous computing is thedynamic environment Things, services and applications are presented with. Taking theseobservations into mind and utilizing so called Design Science Research Methodology, wedevelop a prototype that use Augmented Reality to display information and data of devices,or Things, and evaluate the pros and cons of the technique for this purpose. We alsoexplore Emergent Configurations as an inspiration of design and explore design principlesthat could be applicable to our prototype by carrying out a literature study and evaluatingprevious work. We find that Augmented Reality can be used to visualize IoT systems anddata and that there are several design principles as well as drawbacks to consider.

Den här uppsatsen beskriver processen av att skapa en plattformsoberoende mobilapplikation för att koppla upp mobila enheter mot trådlösa sensorer med hjälp av Bluetooth Low Energy, samla in data från uppkopplade sensorer och ladda upp den insamlade datan till en molnlagringstjänst. Allt eftersom konsumenter och forskare använder fler sensorer och andra Bluetooth-enheter, [1] ökar behovet av simplare och standardiserade lösningar för att arbeta med dessa. En litteraturstudie har genomförts där information om närliggande forskning insamlats och viktig information om de nödvändiga mjukvarukomponenter som krävs har utvärderats. I kombination med litteraturstudien har en IT-artefakt utvecklats i form av en mobilapplikation som har testats utefter insamlade krav för att säkerställa applikationens funktionalitet. Syftet med det här arbetet är att tydliggöra och konkretisera en mjukvaruutvecklingsprocess som kan användas för att skapa en mobilapplikation av det här slaget, samt vilka potentiella svårigheter som finns i dagsläget med att utforma den här typen av applikationer. Resultaten visar att en del tillverkare inte följer standarden för Bluetooth-kommunikation, detta gör det svårt att skriva generaliserade metoder för att hämta data från sensorer av alla typer och från samtliga tillverkare. / This thesis describes the process of creating a platform-independent mobile application for connecting mobile devices to wireless sensors using Bluetooth Low Energy, collecting data from connected sensors and uploading the collected data to a cloud storage service. As consumers and researchers use more sensors and other Bluetooth-devices, [1] one could argue that there is a need for simpler and standardised solutions to working with these. A literature study has been conducted where information on related research has been collected and important information about the necessary software components has been evaluated. In combination with the literature study, an IT artefact has been developed in the form of a mobile application that has been tested according to collected requirements to ensure the application's functionality. The purpose of this work is to contribute with a clear scientific process over what is required to create a mobile application of this kind and what potential difficulties exist in present-day design of this type of applications. The results show that some manufacturers may not be following the standards for Bluetooth data communication, thus making it hard to write generalized methods for retrieving data from sensors of any type or manufacturer.

I dagens samhälle går den tekniska utvecklingen fort framåt. Artificiell intelligens och Internet of Things är två tekniker inom utvecklingen vars popularitet har ökat på senare tid. Dessa tekniker i integration har visat sig kunna bidra med stora verksamhetsnyttor, bland annat i form av ökad precishet vad gäller analyser, bättre kundvärde och effektivisering av ”downtime”. Med ny teknik kommer även utmaningar. I takt med att teknologierna ständigt växer uppstår frågor kring säkerhet och etik och hur detta ska hanteras. Målet med denna studien var att ta reda på hur experter värderar etiska frågor när artificiell intelligens används i kombination med Internet of Things-enheter. Vi fokuserade på följande forskningsfråga för att nå vårt mål: Hur värderas frågor om etik när artificiell intelligens används i kombination med Internet of Things? Resultatet vi kom fram till visar att både forskare och näringslivet värderar de etiska aspekterna högt. Studien visar även att de ansåg att teknikerna kan vara lösningen till många samhällsproblem men att etiken bör vara ett ämne som löpande bör diskuteras. / In today's society, technological developments are moving fast. Artificial intelligence and the Internet of Things are two technologies within the development whose popularity has increased in recent years. These technologies in integration have proven to be able to contribute with major business benefits, including in the form of increased precision with regard to analyzes, better customer value and efficiency of downtime. New technology also presents challenges. As the technologies are constantly growing, issues arise regarding safety and ethics and how this should be managed. The aim of this study is to find out how experts value ethical issues when using artificial intelligence in combination with the Internet of Things devices. We focused on the following research question to reach our goal: How are ethical issues evaluated when using artificial intelligence in combination with the Internet of Things? The result we found shows that both researchers and the business world value the ethical aspects highly. The study also shows that they considered the techniques to be the solution to many societal problems, but that ethics should be a topic that should be discussed on an ongoing basis.