The purpose of this thesis is to devise a system based on RFID (Radio Frequency IDentification) that can be used for smart healthcare applications. Location estimation, eloping prevention and occupancy detection are monitoring applications of smart healthcare which can provide very useful information for the nursing and administration staff of the nursing-home/hospital. The introduction of ubiquitous networking along with the concepts such as Internet of Things (IoT) can certainly help achieve the goals of smart healthcare. RFID technology has features, such as low power and small size, which makes this technology suitable for researching solutions for smart healthcare. Today several nursing-home/hospital monitoring solutions exist in the market and academia alike. The solutions marketed commercially are very expensive whereas the solutions from academia provides solutions to isolated problems but a comprehensive all in one solution that can meet the need of smart healthcare monitoring applications is missing. In this thesis we present a system that is low cost and suitable for accommodating a number of the smart healthcare applications including occupancy detection, location estimation, eloping prevention and access control. The solution is implemented on a customized Openbeacon Active RFID System (OARS). Active RFID based proximity detection is the core of our system. Practical experiments based on novel Proximity Detection based Weighted Centroid Localization (PD-WCL) method were done to analyze the performance of the system with different applications to highlight the applicability of the system.

The purpose of this thesis is to devise a system based on RFID (Radio Frequency IDentification) that can be used for smart healthcare applications. Location estimation, eloping prevention and occupancy detection are monitoring applications of smart healthcare which can provide very useful information for the nursing and administration staff of the nursing-home/hospital. The introduction of ubiquitous networking along with the concepts such as Internet of Things (IoT) can certainly help achieve the goals of smart healthcare. RFID technology has features, such as low power and small size, which makes this technology suitable for researching solutions for smart healthcare. Today several nursing-home/hospital monitoring solutions exist in the market and academia alike. The solutions marketed commercially are very expensive whereas the solutions from academia provides solutions to isolated problems but a comprehensive all in one solution that can meet the need of smart healthcare monitoring applications is missing. In this thesis we present a system that is low cost and suitable for accommodating a number of the smart healthcare applications including occupancy detection, location estimation, eloping prevention and access control. The solution is implemented on a customized Openbeacon Active RFID System (OARS). Active RFID based proximity detection is the core of our system. Practical experiments based on novel Proximity Detection based Weighted Centroid Localization (PD-WCL) method were done to analyze the performance of the system with different applications to highlight the applicability of the system.

The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumption through adaptive heating that uses climate data to detect occupancy in apartments using machine learning. The application of the study has been made using environmental data from one of KTH Live-In Labs apartments. The data was first used to investigate the possibility to detect occupancy through machine learning and was then used as input in an adaptive heating model to investigate potential benefits on the energy consumption and costs of heating. The result of the study show that occupancy can be detected using environmental data but not with 100% accuracy. It also shows that the features that have greatest impact in detecting occupancy is light and carbon dioxide and that the best performing machine learning algorithm, for the used dataset, is the Decision Tree algorithm. The potential energy savings through adaptive heating was estimated to be up to 10,1%. In the final part of the paper, it is discussed how a value creating service can be created around adaptive heating and its possibility to reach the market. / Syftet med den här rapporten är att undersöka om det är möjligt att sänka Sveriges energikonsumtion genom att i lägenheter införa adaptiv uppvärmning som baserar sig på närvaroklassificering av klimatdata. Klimatdatan som använts i studien är tagen från en av KTH Live-In Labs lägenheter. Datan användes först för att undersöka om det var möjligt att detektera närvaro  genom maskininlärning och sedan som input i en modell för adaptiv uppvärmning. I modellen för adaptiv uppvärmning undersöktes de potentiella besparingarna i energibehov och uppvärmningskostnader. Resultaten visar att de bästa featuresen för att klassificera närvaro är ljus och koldioxid. Den maskininlärningsalgoritm som presterade bäst på datasetet var Decision Tree algoritmen. Den potentiella energibesparingen genom införandet av adaptiv uppvärmning uppskattas vara upp till 10,1%. I rapportens sista del diskuteras det hur en värdeskapande tjänst kan skapas kring adaptiv uppvärmning samt dess potential att nå marknaden.

The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumption through adaptive heating that uses climate data to detect occupancy in apartments using machine learning. The application of the study has been made using environmental data from one of KTH Live-In Labs apartments. The data was first used to investigate the possibility to detect occupancy through machine learning and was then used as input in an adaptive heating model to investigate potential benefits on the energy consumption and costs of heating. The result of the study show that occupancy can be detected using environmental data but not with 100% accuracy. It also shows that the features that have greatest impact in detecting occupancy is light and carbon dioxide and that the best performing machine learning algorithm, for the used dataset, is the Decision Tree algorithm. The potential energy savings through adaptive heating was estimated to be up to 10,1%. In the final part of the paper, it is discussed how a value creating service can be created around adaptive heating and its possibility to reach the market.

Практическая значимость данной выпускной квалификационной работы связана с изложенной в ней разработкой системы централизованного управления трансляцией контента, которая успешно реализуется на рынке. С внедрением информационных технологий в нашу жизнь изменяется характер предоставления публичной информации в обществе. На смену бумажным вариантам объявлений и вывесок приходят электронные аналоги, отличающиеся высокой яркостью, динамичность, скоростью обновления информации. Высокий спрос на оперативное, централизованное обновление транслируемого на экраны контента, способствовал появлению на рынке “цифровых вывесок” систем Digital Signage, позволяющих централизованно управлять показываемым контентом на распределенной сети медиа устройств, обновлять его, не производя манипуляций непосредственно с каждым девайсом. Результатом работы является разработанная система управления контентом MMVS Digital Signage, которая успешно реализуется на рынке и дает компании ряд конкурентных преимуществ. Результаты работы подтверждены расчетами экономических показателей. / The practical significance of this final qualifying work is associated with the development of a system for centralized content broadcasting management, which is successfully implemented on the market, as described in it. With the introduction of information technology into our life, the nature of the provision of public information in society is changing. The paper versions of advertisements and signs are being replaced by electronic counterparts, which are distinguished by high brightness, dynamism, and the speed of information updating. The high demand for prompt, centralized updating of content broadcasted to screens has contributed to the appearance on the market of “digital signage” of Digital Signage systems, which allow centrally managing the displayed content on a distributed network of media devices, updating it without manipulating directly with each device. The result of the work is the developed content management system MMVS Digital Signage, which is successfully implemented in the market and gives the company a number of competitive advantages. The results of the work are confirmed by calculations of economic indicators.

Thesis (MScEng)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Developed countries have led the way in the implementation of Intelligent Transport Systems (ITS), with the main objectives of improving road safety and efficiency. Current ITS solutions are heavily dependent on advanced and expensive technologies, and do not necessarily meet the unique requirements of public transportation in Sub-Saharan Africa (SSA). The informal minibus taxi sector dominates public transport in SSA in general, and in South Africa in particular, and is notoriously dangerous – leading to many fatalities annually. This work presents the design and testing of a sensing and reporting system for public transport in SSA. The system contributes to improving the safety and efficiency of minibus taxis in SSA. The system provides three core functions, namely, reckless driving detection, multiple occupancy detection, and wireless reporting to a visualised online platform. The reckless driving detection system implements a novel model that augments inertial vehicle acceleration data with GPS speed information. The model is based on standards used in road design, and takes into account the relationship between a vehicle’s tyres and the road surface. A lateral acceleration threshold, which is speed dependant, and a longitudinal acceleration threshold are suggested to detect reckless driving. Acceleration data is filtered to remove both high-frequency noise and zero-frequency offset, and compared to the thresholds to detect reckless driving events. The occupancy detection system detects multiple occupants in the minibus taxi using low-cost capacitive sensor electrodes, which utilise the electrical field properties of a human body for presence detection. A simplified mathematical model was created to calculate the expected capacitance on the occupancy sensor electrode, and was compared to the measured capacitance in the minibus taxi. The theoretical and empirical results demonstrate that the capacitance of an occupied seat is more than double that of an unoccupied seat. Occupants were clearly detected in various scenarios, such as different occupant sizes, water on seat, various seated positions on the sensor, etc. The wireless reporting inside the vehicle is implemented using a ZigBee network on an Arduino platform. The extra-vehicle wireless reporting uses the existing SSA cellular network, and the online data visualisation is implemented on Trinity Telecoms’ SMART platform. The complete sensing and reporting system is implemented as a prototype, and tested in South African and Ugandan minibus taxis. The results demonstrate that the system achieves the set goals, and could be used to make transport in SSA safer and more efficient. / AFRIKAANSE OPSOMMING: Ontwikkelde lande neem die voortou met die implementering van Intelligente Vervoer Stelsels (IVS) met die hoof doelwit om padveiligheid en vervoerstelsels se effektiwiteit te verbeter. Huidige stelsels wat ontwikkel is vir IVS is baie afhanklik van duur en gevorderde tegnologieë en bevredig dus nie die huidige vereistes binne die openbare vervoer stelsel van Sub-Sahara Afrika (SSA) nie. Die minibus taxi sektor domineer die openbare vervoer stelsel in SSA en meer spesifiek in Suid-Afrika, en daar is jaarliks duisende ongelukke waarvan baie tot sterftes lei. In hierdie werkstuk word daar ’n stelsel voorgestel wat minibus taxi’s in SSA kan monitor. Die doel van die stelsel is om die openbare vervoerstelsel se effektiwiteit en padveiligheid te verbeter. Die stelsel bestaan uit: roekelose bestuur opsporing, veelvoudigepassasier waarneming (monitor van aantal passasiers in voertuig) en network verslagdoening na ’n aanlyn platform. ’n Nuwe model is ontwikkel om roekelose bestuur op te spoor – deur die voertuig se versnelling en spoed te kombineer in berekenings. Die model se berekenings is ook gebasseer op die verwantskap tussen die voertuig se bande en die padoppervlak. Roekelose bestuur word bespeur deur ’n laterale en longitudinale drempel wat spoed afhanklik is. Versnellingsdata word gefilter om hoë-frekwensie geraas en nul-frekwensie afwykings te verwyder. Gefilterde data word dan met die gepaste drempel vergelyk om te bepaal of die bestuurder ’n roekelose beweging uitgevoer het. Die veelvoudige-passasier waarnemingstelsel is getoets in ’n minibus taxi en bestaan uit ’n lae-koste kapasitiewe sensor stelsel. Die stelsel meet ’n passasier se liggaamlike elektriese lading. ’n Wiskundige uitrukking van die kapasitiewe sensor stelsel is bepaal wat ’n teoretiese kapasitansie waarde gee. Dié waarde is met die gemete kapasitansie op die sensor elektrode vergelyk. Die resultate bevestig dat die ontwikkelde stelsels duidelik ’n sittende passasier kan identifiseer. Verskeie toetse is gedoen om te verseker dat die kapasitiewe stelsel gepas is vir die heterogene minibus taxi omgewing. Draadlose verslagdoening word binne die voertuig uitgevoer met behulp van ’n ZigBee netwerk wat geïmplementeer is op ’n Arduino platform. Die buite-voertuig verslagdoening stelsel gebruik bestaande sellulêre kommunikasie netwerke en die inligting word dan op Trinity Telecoms’ SMART platform visueel vertoon. Die volledige ontwikkelde stelsel is as ’n prototipe geïmplementeer en getoets in Suid-Afrikaanse en Ugandese minibus taxi’s. Die resultate toon aan dat die stelsel die doelwitte bereik en dat dit gebruik kan word om die vervoer stelsel in Suid Afrika veiliger en meer doeltreffend te maak.

The quest to balance occupant comfort with energy efficiency is a key challenge in the field of heating systems, particularly for hydronic radiators. This study addresses this issue by investigating the integration of body heat predictions into a gain-scheduling controller for a hydronic radiator system. Although the benefits of gain-scheduling control strategies are acknowledged in HVAC systems, this exploration into the integration of body heat predictions in hydronic radiator systems presents a novel approach. A Linear Parameter-Varying (LPV) controller was employed and its impact on comfort, energy consumption, and robustness in the face of varying parameters such as the number of occupants, inaccuracies in body heat prediction, and set-point temperature changes was examined. This proposed controller was tested in a simulated house heating system made in Simulink. Findings indicated a substantial enhancement in comfort, especially under low-load scenarios. The controller demonstrated notable robustness against disturbances, highlighting the system’s reliability. Although energy consumption did not show significant reduction, the ability to maintain comfort levels without increasing energy use is a valuable contribution to sustainable heating practices. The results of this study extend our understanding of control strategies in hydronic radiator systems, providing a promising approach towards more comfortable, robust, and energy-efficient solutions. Further research should focus on improving the accuracy of body heat prediction algorithms and incorporating renewable energy sources for increased energy efficiency. In sum, this work represents a significant step towards a more balanced and sustainable future in the operation of hydronic radiator systems. / Denna studie utforskar möjligheten att balansera komfort och energieffektivitet i vattenburna elementsystem genom att integrera kroppsvärmeberäkningar i en gain-scheduling regleralgoritm. Vi presenterar en nyanserad metod som använder en Linjär Parameterberoende (LPV) reglerare. Denna reglerare anpassar sig till varierande parametrar som antal personer i rummet, osäkerheter i kroppsvärmeberäkningar och förändringar i inställd temperatur. Den föreslagna regleraren testades i ett simulerat husvärmesystem skapat i Simulink. Resultaten indikerade en betydande förbättring i komfort, särskilt under låglastscenarier. Regleraren uppvisade också anmärkningsvärd robusthet mot störningar, vilket understrykersystemets tillförlitlighet. Även om ingen signifikant minskning i energiförbrukning observerades, är förmågan att bibehålla komfortnivåer utan att öka energianvändningen ett värdefullt bidrag till hållbara uppvärmningsmetoder. Denna studie utökar vår förståelse för reglerstrategier i vattenburna elementsystem och erbjuder en lovande väg framåt mot mer komfortabla, robusta och energieffektiva lösningar. För framtida forskning bör fokus ligga på att förbättra noggrannheten i kroppsvärmeberäkningsalgoritmer och att integrera förnybara energikällor för ökad energieffektivitet. Sammantaget representerar detta arbete ett betydande steg mot en mer balanserad och hållbar framtid i drift av vattenburna elementsystem.