The technological advances in wireless networks, smart phones, social networks, embedded sensor technologies and the wide spread of mobile devices have exposed customers to number of services. With these advanced technological innovations, computing capability and connectivity, customers look forward to get useful services and information by means of their mobile devices anywhere and at anytime thereby saving time and money. The importance of mobile commerce is increasing every day, since the mobile devices are becoming central part of our lives. One of the challenge here is the ability to reinforce the application behavior by utilizing context information. The analysis and utilization of context information is necessary to build intelligent applications and thereby focusing on less user attention by understanding the current situation. The information about the current location of a mobile customer, the time of request, and personal characteristics like nature of work, profession and economic status are utilized by applications to provide accurate context-aware services. Many of context-aware applications focus mainly on user activity, preferences which are not sufficient to provide context-aware intelligent services. However, there are few works in developing an integrated model for analyzing the context information. Many authors describe the context representation using five elements like who, what, where, when and how to provide a user centric view without emphasizing on the feature of generality and structural representation of context parameters. Since context information takes multiple forms, it is essential and necessary to make broad classification which helps application designers and developers to deal with possible contexts and their impact on application behavior. In addition, the context classification enables to understand complex customer situations due to changing mobile environment. Therefore, it is required to design a model which analyzes the context information of customers in a dynamic environment and hence, provide real time accurate service. The design and development of context-aware mobile commerce services requires a general conceptual model which can handle any type of context information for different applications. Due to the dynamic nature of business environment and also the customer preferences keep emerging, there is a need to develop business model which adapts to changing environment. To understand the current situation of customers in such highly dynamic environments and to enable the business transactions quickly among parties involved, it is essential to construct and analyze an integrated view of information from distinct sources. The adaptation of the provided services based on customer needs depends when the relevant context information is self-described in the form of beliefs. The observations made on combination of context information are deduced into beliefs as a result the decision making time to provide service reduces considerably. The aim of the thesis, is to design and develop a context-aware system which has been applied for mobile commerce environment by considering the customer context information. To do this, we have designed two models: the Context-Information, Observation and Belief (C-IOB)model and the commercial business model. The main function of C-IOB model is to support the application to identify a suitable context-aware service and to execute business transaction for a customer by analyzing the context information in the form of beliefs. We classify the used Context Information(CI)into four types: physical, system, application and social environment. The business model discusses the formal description of participants who are involved in commercial business. The C-IOB model The Context Information, Observation and Belief model deduces beliefs on customer, by combination of available context information during transaction execution or service provision. The beliefs represent the various situations of customers based on specific nature of the applications. The beliefs developed about an entity(e.g. ,person, place, thing) are primitive in most theories of decision making so that applications can use these beliefs to identify and execute context-aware services. The C-IOB model reduces the solution search space, since the knowledge about an entity is organized using cognitive factors, which maps user context information into real world observations and beliefs, as a result the decision making time by the system reduces considerably. The five CI -constructs: who, what, where, when and how enable many types of context information acquisition in our work. The commercial business model A commercial business model mainly involves the formal description of business participants who are involved in commercial business transactions. To meet the growing needs and to fulfill high expectations of customers, it is very important that application designers have to address the issue of building viable business models for commercial environment. The business model describes how an enterprise or an organization captures and delivers economical value to customers. In particular, the customers play major role in transactions execution and hence understanding and identifying the needs of customer is an important issue in building the business model for commercial purpose. Mobile Commerce Environment Mobile commerce environment (MCE) is one of the specific forms of commercial business model. It deals with transactions like purchases with the objective of supplying commodities like goods and services to customers using mobile devices. A Mobile commerce environment is established by considering set of customers, vendors and bankers, who are involved in commercial business activities like buying of electronic goods and services. The environment is based on certain factors like the type of customers, the type of transactions and the type of electronic products involved in purchasing. M-commerce is one of the most effective and useful ways of conducting business as the customers are constantly using mobile devices and it significantly assists customers in making transactions anywhere, anytime and thereby improving the customer satisfaction. C-IOB model based mobile commerce environment Mobile commerce applications are required to be flexible, in providing services due to inherent anytime and anywhere paradigm. The traditional systems during commercial business transactions, take large time to search the right product, which leads to more utilization of device resources like memory and computational power. In addition, the users are striked with more information which is not significant. Therefore, there is a need to design applications, which identify the customer requirements by acquiring the context information from distinct sources and thereby providing timely and specific information or services to the customer. Hence, to adapt services based on various situations, it is required to develop a systematic approach for representation and utilization of context information modified to special characteristics of mobile commerce applications. The mobile commerce environment uses C-IOB model for analyzing the relevant context information of customers and the context based beliefs helps to identify a suitable service for an end customer, thereby reducing mobile transaction execution time and providing customer benefits. The simulation environment consists of 10,000 electronic products which are categorized based on technical and commercial features. The simulation is carried out with ten mobile commerce transactions, the database consists of information about500 customers and 100vendors who deal with electronic products selling and10bankersfor money transactions. The customer context information is acquired from physical, system, application and social environment. When customers ends are quest for a service, the current context information is acquired, a set of observations is formulated and belief is deduced. The customer is provided with relevant information or service based on deduced belief. The simulation exhaustively tests the working of the system for mobile commerce transactions under different context environments. Some of the case studies are designed by applying the C-IOB model which includes placing the purchase order for the product, money transfer and after sales service. In summary, we have developed a context-aware system by using C-IOB model and also the design of commercial business model. To evaluate the performance of the system, we have incorporated context-awareness aspect for 10 business transactions applied to mobile commerce. The proposed system using C-IOB model provides customer required services as accurately as possible. The system has the capability to adapt to real time situation of customer needs, thereby enhancing the customer satisfaction. The simulation results have shown that the time to execute mobile commerce transactions is less using context based beliefs compared to context unaware approach. The accuracy of the system with belief based approach is higher than without context information. The customer benefits in business transaction are also enhanced by our design approach.

[pt] Diversos sistemas e aplicações são capazes de identificar um determinado contexto de uso em tempo real, detectando informações para antecipar situações e otimizar sua interface. Esses sistemas que agem de forma contextual e, muitas das vezes, proativa pertencem à área da Computação ciente de contexto. O aplicativo Google para sistemas Android e IOS possui um serviço de assistente virtual para dispositivos móveis que utiliza dados da conta do usuário obtidos através dos serviços Google, além de dados do próprio dispositivo. O assistente é capaz de identificar hábitos, antever necessidades e oferecer cards de informações antes mesmo que sejam pedidos pelo usuário. Pertencendo ao campo da computação ciente de contexto, o aplicativo Google foi eleito como objeto de estudo e avaliado sob o viés da engenharia semiótica. Através da interface do aplicativo, analisou-se a qualidade da comunicação designer-usuário, tendo por objetivo verificar não apenas a eficiência da assistência virtual oferecida pelo sistema, mas também a autonomia do usuário e a flexibilidade do aplicativo diante de suas necessidades. / [en] Many modern systems and applications are capable of analising the contexts of use in real time, identifying key information to anticipate upcoming actions and optimize their interfaces. Those systems that work in a contextual manner and, usually, in a proactive way, belong to the Context Aware Computing area. The Google App for Android and iOS devices has a virtual assistant service that collects data obtained from different sources associated to the user account and links them to data from the user device. The assistant can identify habits, anticipate probable needs and offer information cards even before the user asks for them. Being part of the Context Aware Computing field, the Google App was elected as study object and was evaluated under the Semiotics Engineering bias. From the application s interface, the quality of the user-designer communication was analysed so, not only the virtual assistant efficiency could be evaluated, but also the user autonomy and the application flexibility according to his needs.

PhD (Business Information Systems) / Department of Business Information Systems / Collaborative Decision Making (CDM) is a never-ending challenge in complex-problem situations where multiple actors are involved. Complex-problem situations involve problems that are ill-defined, ill-structured and wicked such as terrorism. Problems of this nature usually warrant a collaborative effort between actors (organizations) with multiple skill-sets and expertise that at times might be at variance with each other. In order to address this gap, three sub-objectives were postulated from the main research objective, “To determine how optimal/effective CDM can be realized amongst counter-terrorism organizations through context-aware technologies.” Using the theory of synergetics and following deductive thematic analysis, the socio-technical nature of the terrorism problem was depicted by postulating a Digital Terrorism Ecology that consists of Open Digital Infrastructure (ODI), Digital Information Ecosystem (DIE), Digital Terrorism Enactment (DTE), Digital Capability and Digital Enslavement. Based on institutional theory and using PLS-SEM technique, Group/departmental relationships, Organizational co-operation, Organizational form, Technical infrastructure and interoperability, Information and knowledge sharing were identified as the factors influencing attainment of Optimal/effective CDM amongst counter-terrorism organizations. In order to explicate the role of context-aware technologies in enhancing CDM amongst counter-terrorism organizations, a context-aware CDM framework was developed following Design Science Research (DSR) methodology. In this study it was evident from the findings that attainment of OCDM in counter-terrorism contexts is challenging even though it is essential. Among the factors considered as possible influencers of attainment of OCDM, Organizational form (OF) was found to influence Organizational cooperation (OC) and Technical infrastructure and inter-operability (TI). Group/departmental relationships (GDR) were found to influence OF and OC. TI was found to influence OC and GDR and further, Information and knowledge sharing (IKS) was found to influence Optimal/effective CDM (OCDM). Of the three pillars of institutional theory, the regulative pillar offered more insights on issues related to rules, discourse and practice and hence the challenges of OCDM attainment. Practically, this study aims to re-orient the thinking of counter-terrorism organizations by presenting the socio-technical nature of the terrorism problem as well as explicating the role of digital technologies in terrorism. / NRF

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Recommender systems are helpful tools employed abundantly in online applications to help users find what they want. This thesis re-purposes a collaborative filtering recommender built for incorporating social media (hash)tags to be used as a context-aware recommender, using time of day and activity as contextual factors. The recommender uses a matrix factorization approach for implicit feedback, in a music streaming setting. Contextual data is collected from users' mobile phones while they are listening to music. It is shown in an offline test that this approach improves recall when compared to a recommender that does not account for the context the user was in. Future work should explore the qualities of this model further, as well as investigate how this model's recommendations can be surfaced in an application.

This master’s thesis project “A Presence Server for Context-aware Applications” was carried out at KTH Center for Wireless Systems (Wireless@KTH). The overall goal of this thesis project is to implement a context aware infrastructure to serve as middleware for different kinds of context aware applications, such as a context-aware printing application, location based notifier application, etc. This thesis examines different types of context aware architectures and considers different forms of context modeling. Additionally the thesis also explores some of the related technology, in order to provide the reader with suitable background information to understand the rest of the thesis. By using the SIP Express Router (SER) and its presence module (pa) a context server has been designed, implemented, and evaluated. Evaluation reveals that the critical bottleneck is the increasing service time as the number of Publish messages for different events in the SER database increases, i.e. the time required for handling and sending the Notify messages when a new Publish message is received increases as a function of the number of earlier Publish messages. The evaluation also shows that the dependence of SER upon the MySQL database as incorrect database queries can cause SER to crash. Additionally the performance of the database limits the performance of the context server. A number of future improvements are necessary to address security issues (in particular the authentication of Watchers) and adding policy based control in order to send Notify messages only to the Watchers authorized to receive information for a specific event. / Examensarbetet "A Presence Server for Context-aware Applications" genomfördes på Kungliga Tekniska Högskolan, KTH Center for Wireless Systems (Wireless@KTH). Det övergripande målet med detta examensarbetsprojekt är att implementera en kontextmedveten infrastruktur som fungerar som "middleware" för olika typer av kontextmedvetna applikationer. Exempel på dessa är kontextmedveten utskriftsapplikation och platsberoende meddelarapplikation osv. Rapporten undersöker olika typer av kontextmedvetna arkitekturer och betraktar olika former av kontextmodellering. Rapporten utforskar även vissa besläktade teknologier för att kunna tillhandahålla läsaren med en passande bakgrundsinformation och därmed öka förståelsen för resten av examensarbetet. Genom att använda Sip Express Routern (SER) och dess närvaromodul (presence module, PA) har en kontextserver designats, implementerats och utvärderats. Utvärderingen visar att den kritiska flaskhalsen är tiden det tar för SER servern att svara på nya Publish meddelanden, för olika händelser, i SER databasen. Svarstiden ökar allteftersom databasen fylls med mer data. Detta påverkar hantering och sänding av Notify meddelande när en ny Publish meddelande är mottagen. Uvärderingen visar också att en viktig fråga är relationen mellan SER servern och MySQL databasen, eftersom felaktiga förfrågningar till databasen kan krascha SER servern. De viktigaste framtida förbättringarna är säkerhetsaspekter (mer specifikt autenticering av Watchers) och tillägg av policybaserad sändning av Notify meddelanden endast till auktoriserade Watchers för specifika händelser.

This paper aimed to discover how player satisfaction is affected by context-aware elements based on physical, real-world factors in an action role-playing game. The possibility of utilizing player modelling to counteract the reduction in player empowerment in a game heavily influenced by external factors was also explored. This was accomplished by creating an ARPG heavily integrated with various weather, and daytime, context data obtained from web-based APIs. Followed by conducting qualitative tests with help of eleven participants during a time period of a week. The evaluated results were presented in a manner of relevance for both context-driven applications as a whole, and for further exploration within game developments utilization of state of the art technology.

L'objectif de cette thèse est de contribuer à l'élaboration d'une méthode de test de systèmes mobiles. L'approche développée est fondée sur la description de tests à l'aide de scénarios et leurs vérifications sur une trace d'exécution. Un scénario modélise le comportement et les interactions que l'on souhaite observer entre un ensemble de nœuds. Les caractéristiques des systèmes mobiles nous ont conduit à représenter un scénario sous deux points de vue différents et complémentaires. Un premier représente des événements de communications entre les nœuds et un second représente la topologie des liens entre ces nœuds. Notre approche est décomposée en deux étapes : une étape de spécification des cas de tests à l'aide de scénarios et une étape de vérification de ces scénarios sur des traces d'exécutions. La première consiste à spécifier à l'aide du langage dédié TERMOS les cas de test de l'application mobile à vérifier. Ce langage TERMOS a été mis en œuvre au sein de l'atelier UML Papyrus. À partir des scénarios décrits de manière graphique, nous générons pour chacun d'eux un automate ainsi qu'une séquence de topologie que nous utilisons dans l'étape suivante. La deuxième étape consiste à vérifier chaque scénario sur des traces d'exécutions provenant de l'application à tester. Pour cela un premier outil recherche les occurrences de la séquence de topologie du scénario dans la trace d'exécution. Pour chacune d'entre elles, l'automate est exécuté et conclut à un verdict. L'analyse de l'ensemble des verdicts d'un scénario permet de détecter les fautes présentes dans le système. / The main objective of this thesis is to contribute to elaborating a mobile system test method. The proposed approach is based on test definition using scenarios and their verification on an execution trace. A scenario modelizes the behavior and the interactions we want to achieve on a set of nodes. Considering the characteristics of mobile systems we represented scenarios from two different but complementary points of view. The first represents communication events between nodes and the second represents the link topology between the nodes. Our approach is composed of two steps : a first step to specify the test cases by using scenarios and a second step to verify these scenarios on execution flows. The first step consists in using the dedicated TERMOS language in order to specify the test cases of the mobile application. The TERMOS language has been developed in the UML Papyrus workshop. Based on the graphically defined scenarios, we generate an automaton for each one of them, as well as a sequence of topologies which we will be using in the next step. The second step consists in verifying each scenario by using execution traces from the application to be tested. Therefore a first tool detects scenario topology sequences in the execution flow. For each one of them the automaton is executed and comes out with a verdict. The analysis of all the verdicts of a scenario allows the detection of faults in the system.

Music listening is considered one of the most ubiquitous activities in everyday life, and one of the main reasons why people listen is to affect and regulate their mood. The vast availability and unlimited access of music has made it difficult to find relevant music that fits both the context and the preferences of the music listener. The aim of this project was to investigate the personalized relationship between music and mood using everyday technologies, focusing on how a listening experience could be adapted to the desired affect of a music listener while also taking the user’s individual listening history into account. In large, the project concentrated on the possibility of using context-aware music recommendation to generate personalized playlists by focusing on the audio features and corresponding mood of the music. A web-based application was developed to act as a prototype for the study, where the application allowed users to connect to Spotify, pick a desired mood and generate a playlist. By allowing people to access music in this personalized way, a user study could be conducted in order to investigate their music listening while incorporating this recommendation tool. The findings showed that the users’ found the experience to be engaging in that they could use the application as a companion to everyday tasks in addition to it being a tool for getting new, personalized music recommendations. Overall, the participants also found the generated playlists to be accurate to their music preferences and desired affective state.

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