Denna rapport beskriver designprocessen och utvecklingen av en mobilapplikation kallad Gruppis. Rapporten syftar till att redogöra för hela processen från konceptualisering av idén till en slutgiltig interaktiv hi-fiprototyp. Syftet med applikationen är att underlätta kommunikation och informationsspridning mellan personal och vårdnadshavare i förskola, skola eller andra barngrupper. Arbetsprocessen innefattade förarbete i form av fokusgrupp och PACT-analys för att få en uppfattning om användarna och deras behov. Utifrån relevanta designprinciper och riktlinjer för interaktionsdesign har sedan två olika gränssnitt, anpassade för smartphone och surfplatta, skapats. Dessa har sedan testats och utvärderats vilket har lett till revideringar i design och navigation. För att optimera upplevelsen av applikationen har även en grafisk design skapats. Examensarbete resulterade i två interaktiva och verklighetstrogna hi- fiprototyper för både smartphone och surfplatta.

This thesis is to help developers in the touch design of casual games. The thesis work was made on the development platform Gideros Mobile and much of the thesis theory and methods will be based on that work. The purpose of the report is to show what one should think about when making a casual game in a touch design perspective, like taking into account that most people are used to one type of input design (like swiping or tapping), that you should design the game with the purpose to reach out to as a large audience as possible (taking into account people with disabilities) and some small notes on what should be avoided so not to deter people from wanting to play the game. It is important to note that this thesis is built for the purpose of mobile casual games, others will probably not find this thesis relevant.

Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Road accidents are a growing concern for governments and is rising to become one of the leading causes of death in developing countries. Aggressive driving is one of the major causes of road accidents, and it is therefore important to investigate ways to improve people's driving habits. The ubiquitous presence of smartphones provides a new platform on which to implement sensor networks in vehicles, and therefore this thesis focuses on the use of smartphones to monitor a person's driving behaviour. The framework for a smartphone-based system that can detect and classify various driving manoeuvres is researched. As a proof of concept, a system is developed that specifically detects lateral driving manoeuvres and that classifies them as aggressive or not, using a supervised learning classification algorithm. Existing solutions found in research literature are investigated and presented. The best existing solution, a dynamic time warping classification approach, is also implemented and tested. We use an aggressive driving model that is based on the angle of a turn, the lateral force exerted on the vehicle and its speed through the turn. The tests and results of the implemented manoeuvre detection and classifcation algorithms are presented, and thoroughly discussed. The performance of each classifer is tested using the same data set, and a quantitative comparison are made between them. Ultimately, a lateral driving manoeuvre detection and recognition system was successfully developed, and its potential to be implemented on a smartphone was substantiated. The suitability of supervised learning classi ers for classifying aggressive driving, in comparison to dynamic time warping classifcation, was successfully demonstrated and used to validate our aggressive driving model. Conceivably, this work can be employed in the future to develop an holistic smartphone-based driver behaviour monitoring system, which can be easily deployed on a large scale to help make the public drive better. This would make our roads safer, reducing the occurrence of road accidents and fatalities. / AFRIKAANSE OPSOMMING: Padongelukkige is 'n groeiende bekommernis vir regerings en is een van die hoof oorsake van sterftes in ontwikkelende lande. Aggressiewe bestuur is een van die grootste oorsake van padongelukke, en dit is dus belangrik om ondersoek in te stel oor hoe mense se bestuurgewoontes verbeter kan word. Die alomteenwoordigheid van slimfone bied 'n nuwe platform waarop sensor netwerke geïmplementeer kan word in voertuie. Daarom fokus hierdie tesis op die gebruik van slimfone om 'n persoon se bestuurgedrag te moniteer. Die raamwerk vir 'n slimfoon-gebaseerde stelsel wat verskeie bestuurbewegings kan opspoor en klassifiseer is nagevors. As 'n bewys van die konsep, is 'n stelsel ontwikkel wat spesifiek laterale bestuurbewegings opspoor en dan klassifiseer of dit aggressief is of nie, met behulp van 'n klassifikasie algoritme wat onder toesig geleer is. Bestaande oplossings gevind in navorsingsliteratuur word ondersoek en aangebied. Die beste bestaande oplossing, 'n dinamiese tyd buiging klassifikasie benadering, word ook geïmplementeer en getoets. Ons gebruik 'n aggressiewe bestuurmodel wat gebaseer is op die hoek van 'n draai, die laterale krag wat uitgeofen is op die voertuig en sy spoed deur die draai. Die toetse en die resultate van die geïmplementeer beweging opsporing en klassifisering algoritmes word aangebied, en deeglik bespreek. Die prestasie van elke klassifiseerder is getoets met behulp van dieselfde stel data, en 'n kwantitatiewe vergelyking is tussen beide gemaak. Oplaas is 'n laterale bestuurbeweging bemerking en herkenning stelsel suksesvol ontwikkel en sy potensiaal om geïmplementeer te word op 'n slimfoon is gestaaf. Die geskiktheid van die onder-toesig-geleerde klassifiseerders vir die klassifikasie van aggressiewe bestuur, in vergelyking met dinamiese tyd buiging klassifikasie, was suksesvol gedemonstreer en gebruik om ons aggressiewe bestuurmodel te bewys. Hierdie werk kan in die toekoms gebruik word in 'n holistiese slimfoon-gebaseerde bestuurdergedrag monitering stelsel, wat maklik op groot skaal ontplooi kan word om te help verseker dat die publiek beter bestuur. Dit sal ons paaie veiliger maak, en die voorkoms van padongelukke en sterftes verminder.

The growing importance of multimedia content generated by ordinary users demands research for models, methods, technologies and systems that support multimedia production. Despite recent results allowing the collaborative capture of video via mobile devices, there is gap in supporting the collaborative capture of multiple media. In this dissertation we propose that ubiquitous collaborative multimedia production can be carried out by users who capture and annotate multiple media using the CMoViA mobile application. CMoViA also allows export the user-generated content to the CI+WaC, which allows them to edit the user-generated content in the form of interactive and extensible multimedia documents. The proposal demanded extending recent work reported in the literature, namely the I+WaC-IE (Interactors+WaC-Interaction Events) model, the I+WaC-Editor tool and MoViA tool. Hence, CMoViA follows the proposed CI+WaC-IE model. We discuss results from a case study, carried out in the educational domain, in which students collaboratively capture a lecture. / A crescente importância de conteúdo multimídia gerado por usuários amadores exige pesquisas por modelos, métodos, tecnologias e sistemas que apoiem a produção multimídia. Apesar dos recentes resultados que permitem captura colaborativa em vídeo utilizando dispositivos móveis, existe uma lacuna no apoio à captura colaborativa de múltiplas mídias. O trabalho apresentado nesta dissertação propõe que a produção multimídia colaborativa ubíqua possa ser alcançada por usuários que realizem a captura de múltiplas mídias e de anotações utilizando o aplicativo móvel CMoViA. CMoViA também permite que o conteúdo gerado por esses usuários seja exportado para a plataforma CI+WaC, a qual permite editar e anotar documentos multimídia interativos. Essa proposta requer a extensão de trabalho recentes reportados na literatura: o modelo I+WaC-IE (Interactors+WaC-Interaction Events), a ferramenta I+WaC-Editor e a ferramenta MoViA. Assim, a aplicação CMoViA segue o modelo CI+WaC-IE proposto neste trabalho como extensão do modelo I+WaC-IE. A proposta foi avaliada por meio de estudo de caso realizado no domínio educacional, no qual estudantes capturam colaborativamente uma palestra.

La reconnaissance biométrique a été utilisée longtemps dans des espaces confinés, généralement à l'intérieur, où les opérations de sécurité exigeaient des systèmes de haute précision, par exemple dans les postes de police, les banques, les entreprises, les aéroports. Les activités de terrain, au contraire, exigent plus de flexibilité et portabilité conduisant au développement de dispositifs pour l'acquisition des traits biométriques et des algorithmes pour la reconnaissance biométrique dans des conditions moins contraintes. L'application de la reconnaissance biométrique "portable" est limitée dans des domaines spécifiques, par exemple pour le contrôle de l'immigration, et exige des dispositifs dédiés. Pour étendre l'utilisation de la biométrie sur les appareils personnels, des tentatives ont été faites par l’intégration des scanners d'empreintes digitales dans les ordinateurs portables ou les smartphones. Mais la reconnaissance biométrique sur les appareils personnels a été utilisée seulement pour un nombre limité de tâches, comme le déverrouillage d'écrans à l'aide des empreintes digitales au lieu de mots de passe. Les activités décrites dans cette thèse se sont portées sur le développement de solutions pour la reconnaissance de l'iris sur les appareils mobiles: - Acquisition: collection de la base de données MICHE, contenant des images d'iris capturée par des appareils mobiles; - Segmentation: développement d'un algorithme de segmentation innovante; - Extraction de caractéristiques: la reconnaissance de l'iris a été combinée avec le visage et la reconnaissance du smartphone.Enfin, la reconnaissance du regard a été étudiée afin de vérifier sa possible fusion avec l'iris / Biometric recognition for a long time has been used in confined spaces, usually indoor, where security-critical operations required high accuracy recognition systems, e.g. in police stations, banks, companies, airports. Field activities, on the contrary, required more portability and flexibility leading to the development of devices for less constrained biometric traits acquisition and consequently of robust algorithms for biometric recognition in less constrained conditions. However, the application of "portable" biometric recognition, was still limited in specific fields e.g. for immigration control, and still required dedicated devices. A further step would be to spread the use of biometric recognition on personal devices, as personal computers, tablets and smartphones. Some attempts in this direction were made embedding fingerprint scanners in laptops or smartphones. So far biometric recognition on personal devices has been employed just for a limited set of tasks, as to unlock the screen using fingerprints instead of passwords. The research activities described in this thesis were focused on studying and developing solutions for iris recognition on mobile devices. This topic has been analyzed in all its main phases: - Acquisition: collection of the MICHE database, containing pictures of irises acquired by mobile devices; - Segmentation: development of an innovative iris segmentation algorithm; - Feature extraction and matching: iris recognition has been combined with the face and with sensor (smartphone) recognition. Finally, the use of gaze analysis for human recognition has been investigated in order to verify its possible fusion with iris.

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The goal of this master thesis was to evaluate the field of Smart home applications run on mobile platforms such as smart phones. This was at the time a relatively new field that has attracted the attention of Smart phone giants like Apple and Google. This raised the question whether or not the users willingness to embrace the technology. To evaluate the field, a literature study was conducted covering the Smart home technology, and Apple’s and Google’s Smart home solutions. The rendered in a prototype for a Smart home communication application which was run on the Android platform. The prototype was then used in user tests focusing on the usability of the application and the field of Smart home smart phone applications. Even though the usability of the application was regarded fairly low, positive results were obtained regarding the evaluation of the field it self. This points to promising progress of Smart home applications run on smart phones.

This study examined whether the current generation of consumer-grade digital mobile computing technology, so called smartphone technology, is usable to perform and improve field data collection in the context of sustainable forest management. An electronic data acquisition system, based on a handheld smartphone device and desktop geographic information system (GIS), was developed. A proprietary timber cruise application and commercial mapping software were used with the smartphone/desktop GIS to record and process forest stand and geospatial data. Usability testing was carried out to measure workflow efficiency and system performance of the smartphone GIS compared to traditional paper-based methods. The smartphone GIS successfully met performance objectives and significantly increased workflow efficiencies by improving data transfer and processing times over conventional paper methods; however, use of the mobile device resulted in greater data entry errors, increased data collection times, and led to more equipment malfunctions than use of paper recording methods together with a GPS and digital camera. Overall, the prototype electronic data acquisition system was not reliable as a stand-alone solution solely responsible for collecting cruise data, but was found to be well suited for ad-hoc mapping of forest features.

Schizophrenia is a complex and devastating illness with heterogeneous symptoms, late diagnosis, and excess early mortality. It is also associated with comorbidities including substance abuse, depression, anxiety, and sleep problems, that have adverse effects on the individual over the entire course of the disease. While effects of these comorbidities have been identified in the literature, few studies have involved longitudinal assessments and reproducible data collection in large populations. Recent smartphone research tools have been developed that provide better access to patients and can enable a real-world snapshot of a person’s mental state. In addition, these tools use the phone’s sensors to construct a digital phenotype of an individual, with the potential to detect changes in symptoms and cognition on a moment-by-moment basis. Previous studies report associations between anxiety and smartphone use, but most involve cross-sectional data and cohorts of healthy controls completing paper and pencil scales. A recent smartphone study collected day-to-day symptomatology, cognition, and phone usage data and discovered that the association between anxiety and smartphone use is more complex than originally thought.