The total number of mobile subscriptions has been announced to reach 6 billion in the market, of which 4 billion are individual users. The rest of the people on earth are potential subscribers that mainly live in rural areas lacking mobile connectivity today. Many of these users do not have access to electricity and have 6 U.S. dollar per month (USD/month) of average revenue per person.   Referring to the year 2007, the telecommunication industry had a contribution of 0.6 percent of direct global carbon dioxide (CO2) or 0.4 percent of global carbon dioxide equivalent (CO2e). From 2007 to 2009, the number of off-grid radio base stations located in rural areas went up from 350,000 to 500,000. Nearly all of these sites use diesel generators and large amounts of fossil fuels during the operational stage. In addition the grid sites with diesel back-up were about 0.5 million in 2009. The financial and environmental consequences of the life cycle impact of the diesel fuel depleted can be significant. Adaptation of renewable energy has therefore become important for both environmental and economic reasons.   In this master thesis a Life Cycle Assessment of Ericsson’s Managed Rural Coverage (MRC) solution was made. Four main life cycle stages were included: manufacturing, transportation, operation and end-of-life treatment. MRC is an off-grid site solution consisting of electronic communication equipment (radio base station, base station controller, hub, cable) photovoltaic cells, battery, antenna, and constructions part (antenna pole, tower and foundation). This study also includes the satellite connection as well as Ericsson and operator activities in the assessment. The MRC distinguishes itself from the conventional base stations, by its significant decrease of energy consumption in its operational stage as well as the business model around the offering. The assessment in this thesis was carried out in accordance with data retrieved from an Ericsson’s pilot system in Dungunab, Sudan. The ISO 1404X series of LCA standards was followed and Gabi software w used to evaluate the results.   The carbon footprint was found to be 0.3 kg CO2e/subscriber for the pilot setup. These calculations were based on an assumption that each pilot site serviced 1000 users. The maximum number of subscribers can be about 3200, which would decrease the life cycle CO2 emissions per user by 2/3. According to the sensitivity analysis the maximum CO2 emissions for a conservative MRC scenario is less than 1 kg CO2e/subscriber. Although this figure represents a very conservative scenario, the result is low in comparison with an average GSM network which has an approximate carbon footprint of 15 kg CO2e/subscriber. It is important to note that the MRC is not intended to replace all conventional macro RBS sites due to limitations in performance and capabilities, but is rather a complement to conventional macro radio base station sites for applicable scenarios. / <p>Thesis registration number: EGI-2013-024MSC  EKV941</p>

We need to employ modern-day technologies in our daily lives to make our life easier. In this thesis, we analyze the user’s oral hygiene habits and core body temperature to help people to track the state of their health. We designed a system in which the data are directly extracted from the mouth, then stored and presented in the application. By means of the system, the people can keep track oftheir core temperature without any extra function apart from their daily chores.The system can also help to keep track of the health of people with symptoms ofdementia and Alzheimer. We used an LM35 temperature sensor to measure temperature. The sensor is mounted on a powered toothbrush head. When the user starts to brush, the sensor records the temperature data for seven times in two minutes of an average brush time and sends it to the mobile application using WiFi. We used a NodeMCUboard, ThingSpeak server and MIT inventor app to transfer the data and designthe mobile application.

The great popularity of portable, wearable, and implantable smart electronics has intensively boosted the development of flexible miniaturized power supplies. Owing to the fast charge/discharge capability, high power delivery, long cycling lifetime, easy fabrication and integration, flexible in-plane micro-supercapacitors (FPMSCs) are of significance as the micropower sources for the next-generation flexible on-chip electronics. In this review, we provide a comprehensive overview about FPMSCs and discuss the recent advances in their fabrication and applications. Particular emphasis is put on the emergent device fabrication technologies of FPMSCs, including deposition techniques, coating strategies, etching methods, and printing technologies. Moreover, we highlight the unique applications of FPMSCs in constructing smart responses and self-powered integrated systems in terms of multifunctional operation modes. Finally, the remaining challenges regarding flexibility, performance improvement, smart response, and microdevice integration of FPMSCs are discussed, which will stimulate further research in this thriving field.

Ventilation on demand (VOD) concept has earned significant worldwide attention by several mining companies in recent years. It is a concept where airflow is provided only to areas that require ventilation. The implementation of the concept has resulted in significant savings in annual energy consumption and cost for several companies globally. The research presented in this thesis sought to present the VOD system as an alternative solution and strategy to improve the ventilation system of Konsuln mine. The system is expected to cope with a planned increase in production rate and meet requirements in the new Swedish Occupational Health &amp; Safety (OH&amp;S) regulations, Arbetsmiljöverkets förtfattningssamling (AFS) 2018:1, which is based on the EU directive 2017/164 where Threshold Limit Value (TLV) for gases have been significantly reduced and provide safe work environment for workers in the mine. The thesis work started with planning and execution of a PQ (Pressure – Quantity) survey to calibrate the existing ventilation model of Konsuln mine. This was to ensure that the model is reasonably accurate to give reliable simulation predictions of the performance of Konsuln ventilation system in its current state and for the future. The good correlation between the modelled and underground measured values validated the model for further ventilation planning. The study further investigated and analyzed the current and future ventilation demand of LKAB test mine, Konsuln, to design a VOD system for its operations.The work outlined three main VOD design scenarios I, II, and III based on the proposed production plan, schedule, and the mining process that present the underground working conditions on the three main levels (436, 486 and 536) of Konsuln mine. Diesel, battery-powered, heat, and blast simulations were carried out for all the scenarios in the calibrated ventilation model using VentSim Design simulation software. The model was again used to estimate the annual ventilation power cost for the VOD scenarios to highlight the benefit and cost savings advantage under the VOD design system to deliver enough airflow quantity compared to the conventional system of ventilation. Simulation results showed that about 15.6% – 49.1% and 76.4% - 86.7% of significant cost savings will be achieved for diesel and battery-powered machineries respectively, while still supplying the needed amount of air to working areas to keep contaminants below their Threshold Limit Value -Time Weighted Average (TLV-TWA) and provide a good working environment. For additional benefits and savings of the Ventilation on Demand (VOD) system implementation, some considerations for equipment, personnel positioning and identification, monitoring system, and stations have also been discussed in this work.  These include; (i) Utilization of LKAB’s database system, Giron, in addition to mounting tags with unique IDs on machineries, to track the route of LHDs and trucks to deal with the challenge of airflow supply shortfall associated with auxiliary fans adjustment to affect target locations. (ii) Installation of temperature sensors, flow meters, gases and Diesel Particulate Matter (DPM) monitoring systems at specific, appropriate, and optimal locations in the mine for efficient implementation of the VOD system strategy. The heat simulations for both diesel and battery-powered machineries were carried out for the month of July when the highest temperatures in Kiruna are often recorded for the summer. They predicted the highest temperatures in working areas to be well below the limit used in Australia, 28°C Wet Bulb (WB). Four scenarios A, B, C and D were also considered for blast clearance time simulation using both the ramp and exhaust shaft. The blast simulation results indicated that the time to dilute and clear blast fumes through the exhaust shaft saves some clearance time compared to exhaustion through the ramp, although the shaft exhaustion will require additional financial commitment to purchase and install exhaust fans on each of the three main levels of the mine. Nevertheless, major ventilation work and practices such as removal of regulator in front of primary fans, additional radon measurement, and good auxiliary ventilation practices have been recommended to improve and actualize the benefits outlined in this work.

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The growing presence of algorithm-generated recommendations in AI-powered services highlights the importance of responsible systems that explain outputs in a human-understandable form, especially in an automotive context. Implementing explainability in recommendations of AI-powered eco-driving is important in ensuring that drivers understand the underlying reasoning behind the recommendations. Previous literature on explainable AI (XAI) has been primarily technological-centered, and only a few studies involve the end-user perspective. There is a lack of knowledge of drivers' needs and requirements for explainability in an AI-powered eco-driving context. This study addresses the attributes that make a “satisfactory” explanation, i,e., a satisfactory interface between humans and AI. This study uses scenario-based interviews to understand the explainability attributes that influence truck drivers' intention to use eco-driving recommendations. The study used thematic analysis to categorize seven attributes into context-dependent (Format, Completeness, Accuracy, Timeliness, Communication) and generic (Reliability, Feedback loop) categories. The study contributes context-dependent attributes along three design dimensions: Presentational, Content-related, and Temporal aspects of explainability. The findings of this study present an empirical foundation into end-users' explainability needs and provide valuable insights for UX and system designers in eliciting end-user requirements.

Methods were developed for the design of a solar powered UAV capable of tracking the sun to achieve maximum solar energy capture. A single-axis solar tracking system was designed and constructed. This system autonomously rotated an onboard solar panel to find the angle of maximum solar irradiance while the UAV was airborne. A microcontroller was programmed and implemented to control the solar tracking system. A solar panel and an efficient airframe capable of housing the solar tracking system was designed and constructed. Each of these subsystems was tested individually with either ground or flight tests. Ultimately, the final assembled system was tested. These tests were used to determine where and when a UAV with an onboard solar tracker would be advantageous over a conventional solar powered UAV with PV cells statically fixed to its wings. The final UAV had a wingspan of 3.2 meters, a length of 2.6 meters, and weighed 4.1 kilograms. Its solar panel provided a maximum power output of 37.7 watts. The predicted system performance, airframe drag, and system power requirements were validated with a battery powered flight test. The UAV's analytical model predicted the drag to be 41% lower than the actual drag found from flight testing. Full system functionality was verified with a solar powered flight test. The results and analysis of the system tests are presented in this thesis. The net energy increase from the solar tracking UAV over a conventional solar powered UAV for the duration of a day is dependent on season and geographical location. The solar tracking UAV that was developed was found to have a maximum net energy gain of 34.5% over a conventional solar powered version of the UAV. The minimum net energy gain of the solar tracking UAV was found to be 0.8%.

Medellivslängden i Sverige har, under de senaste decennierna, ökat. Det leder till att sjukvårdsköerna och belastningen för vårdpersonalen förändras. Det i sin tur innebär att fortsatt utveckling av hälso- och sjukvård måste prioriteras. En viktig faktor för att kunna utveckla arbetssätten inom sjukvården är digitalisering.  Syftet med studien är att undersöka vilka utmaningar som kan uppstå i samband med användning av AI- hjälpmedel som beslutsstöd vid diagnostiserings-processen i sjukvården.  Studien startade med litteraturgenomgång av tidigare forskning. Studien genomfördes med en kvalitativ ansats där datainsamlingsmetoden är semistrukturerade individuella intervjuer. Analysen genomfördes med strukturen tematisk analysmetod. Studiens fem teman är: Arbetssätt; kompetensutveckling; partiska algoritmer; ansvarstagande och överdiagnostisering.  Studiens resultat indikerar att det finns olika utmaningar vid användning av AI inom vården. I den här studien har följande utmaningar påvisats: arbetssätt- exempelvis nya rutiner, kompetensutveckling- exempelvis mindre tid för utvecklingsarbete, ansvarstagande - till exempel vem som ansvarar för resultatet och överdiagnostisering – vilket till exempel kan vara multipla diagnoser som kan vara ofarliga för patienten. / The average life expectancy in Sweden has, in recent decades, increased. This leads to changes in the healthcare queues and the burden on the healthcare staff. This in turn means that continued development of healthcare must be prioritized. An important factor in being able to develop working methods in healthcare is digitization. The purpose of the study is to investigate which challenges may arise in connection with the use of AI- powered decision making in the diagnosis process in healthcare. The study started with a literature review of previous research. The study was carried out with a qualitative approach where the data collection method is semi-structured individual interviews. The analysis was carried out using the structured thematic analysis method. The study's five themes are: Work methods; skills development; biased algorithms; taking responsibility and overdiagnosing. The study's results indicate that there are various challenges when using AI in healthcare. In this study, the following challenges have been demonstrated: working methods - for example new routines, competence development - for example less time for development work, taking responsibility - for example who is responsible for the result and overdiagnosis - which can for example be multiple diagnoses that can be harmless to the patient.

This study aims to evaluate the diffusion process of a solar-powered refrigerator system, by implementing a sustainable business model as an approach of assessing key features to facilitate the process. The aspiration of this study is to develop a business perspective that can be utilized by companies when aiming to diffuse sustainable enhancing innovations in developing countries with the aim of improving entrepreneurship.  The conclusion of this study is based on the alignment of a theoretical framework centered on a sustainable business model and the theory for diffusion of innovation, alongside empirical findings obtained during a case study in Linga Linga, Mozambique. Primary data was acquired through active observations and semi-structured interviews of both female fish entrepreneurs and two organizations with ties to Sweden, operating in Linga Linga.  Empirical findings reveled limited availability of new products in Linga Linga, obstructing the diffusion of innovations. Businesses struggles to diffuse innovations in developing countries because of insufficient knowledge of culture differences and the basic needs of the end user. Sustainable development is highlighted as crucial when operating in the Western word but stated as challenging to implement to the same extent in the developing world. The fulfillment of basic needs, rather than operating sustainable and the unfamiliarity with sustainable development as a concept, is found as the reason for the challenge of implementing sustainable development for individuals afflicted by poverty.  The alignment of the theoretical framework and the empirical findings in the discussion chapter underscores the benefits of implementing a sustainable business model. Furthermore, the discussion emphasizes the importance of extending the model with knowledge as an additional key feature to comprehensively understand the end users and their basic need in the developing world.   This study concludes that utilizing a sustainable business model to assess key features is crucial for facilitating diffusion of innovations, with a particular focus on understanding end user´s basic needs. The study emphasizes the significance of circular economy as a key feature in ensuring durable and reliable products and highlights the importance of comprehensive value chain assessments. Empirical finding concluded that providing solar-powered refrigerator system for the female fish entrepreneurs in Linga Linga could potentially expand their business opportunities, ensuring an increased disposable income, and reduce workload.

L'objectif de cette thèse est de développer des outils d'analyse de données recueillies sur les deux roues motorisés (2RMs). Dans ce cadre, des expérimentations sont menées sur des motos instrumentés dans un contexte de conduite réelle incluant à la fois des conduites normales dites naturelles et des conduites à risques (presque chute et chute). Dans la première partie de la thèse, des méthodes d'apprentissage supervisé ont été utilisées pour la classification de situations de conduite d'un 2RM. Les approches développées dans ce contexte ont montré l'intérêt de prendre en compte l'aspect temporel des données dans la conduite d'un 2RM. A cet effet, nous avons montré l'efficacité des modèles de Markov cachés. La seconde partie de cette thèse porte sur le développement d'outils de détection et de classification hors ligne des évènements critiques de conduite, ainsi que, la détection en ligne des situations de chute d'un 2RM. L'approche proposée pour la détection hors ligne des évènements critiques de conduite repose sur l'utilisation d'un modèle de mélange de densités gaussiennes à proportions logistiques. Ce modèle sert à la segmentation non supervisée des séquences de conduite. Des caractéristiques extraites du paramètre du modèle de mélange sont utilisées comme entrées d'un classifieur pour classifier les évènements critiques. Pour la détection en ligne de chute, une méthode simple de détection séquentielle d'anomalies basée sur la carte de contrôle MCUSUM a été proposée. Les résultats obtenus sur une base de données réelle ont permis de montrer l'efficacité des méthodologies proposées à la fois pour la classification de situations de conduite et à la détection des évènements critiques de conduite / This thesis aims to develop framework tools for analyzing and understanding the riding of Powered Two Wheelers (PTW). Experiments are conducted using instrumented PTW in real context including both normal (naturalistic) riding behaviors and critical riding behaviors (near fall and fall). The two objectives of this thesis are the riding patterns classification and critical riding events detection. In the first part of this thesis, a machine-learning framework is used for riding pattern recognition problem. Therefore, this problem is formulated as a classification task to identify the class of riding patterns. The approaches developed in this context have shown the interest to take into account the temporal aspect of the data in PTW riding. Moreover, we have shown the effectiveness of hidden Markov models for such problem. The second part of this thesis focuses on the development of the off-line detection and classification of critical riding events tools and the on-line fall detection. The problem of detection and classification of critical riding events has been performed towards two steps: (1) the segmentation step, where the multidimensional time of data were modeled and segmented by using a mixture model with quadratic logistic proportions; (2) the classification step, which consists in using a pattern recognition algorithm in order to assign each event by its extracted features to one of the three classes namely Fall, near Fall and Naturalistic riding. Regarding the fall detection problem, it is formulated as a sequential anomaly detection problem. The Multivariate CUmulative SUM (MCUSUM) control chart was applied on the data collected from sensors mounted on the motorcycle. The obtained results on a real database have shown the effectiveness of the proposed methodology for both riding pattern recognition and critical riding events detection problems