We are rapidly entering a world with an immense amount of services and devices available to humans and machines. This is a promising future, however there are at least two major challenges for using these services and devices: (1) they have to be found and (2) after being found, they have to be selected amongst. A significant difficulty lies in not only finding most available services, but presenting the most useful ones. In most cases, there may be too many found services and devices to select from.

Service discovery needs to become more aimed towards humans and less towards machines. The service discovery challenge is especially prevalent in ubiquitous computing. In particular, service and device flux, human overloading, and service relevance are crucial. This thesis addresses the quality of use of services and devices, by introducing a sophisticated discovery model through the use of new layers in service discovery. This model allows use of services and devices when current automated service discovery and selection would be impractical by providing service suggestions based on user activities, domain knowledge, and world knowledge. To explore what happens when such a system is in place, a wizard of oz study was conducted in a command and control setting.

To address service discovery in ubiquitous computing new layers and a test platform were developed together with a method for developing and evaluating service discovery systems. The first layer, which we call the Enhanced Traditional Layer (ETL), was studied by developing the ODEN system and including the ETL within it. ODEN extends the traditional, technical service discovery layer by introducing ontology-based semantics and reasoning engines. The second layer, the Relevant Service Discovery Layer, was explored by incorporating it into the MAGUBI system. MAGUBI addresses the human aspects in the challenge of relevant service discovery by employing common-sense models of user activities, domain knowledge, and world knowledge in combination with rule engines.

 The RESPONSORIA system provides a web-based evaluation platform with a desktop look and feel. This system explores service discovery in a service-oriented architecture setting. RESPONSORIA addresses a command and control scenario for rescue services where multiple actors and organizations work together at a municipal level. RESPONSORIA was the basis for the wizard of oz evaluation employing rescue services professionals. The result highlighted the importance of service naming and presentation to the user. Furthermore, there is disagreement among users regarding the optimal service recommendation, but the results indicated that good recommendations are valuable and the system can be seen as a partner.

Vi rör oss snabbt in i en värld med en enorm mängd tjänster och enheter som finns tillgängliga för människor och maskiner. Detta är en lovande framtid, men det finns åtminstone två stora utmaningar för att använda dessa tjänster och enheter: (1) de måste hittas och (2) rätt tjänst/enhet måste väljas. En betydande svårighet ligger i att, inte bara finna de mest lättillgängliga tjänsterna och enheterna, men också att presentera de mest användbara sådana. I de flesta fall kan det vara för många tjänster och enheter som hittas för att kunna välja mellan.

Upptäckten av tjänster och enheter behöver bli mer anpassad till människor och mindre till maskiner. Denna utmaning är särskilt framträdande i desktopmetaforens efterföljare Ubiquitous Computing. (Det vill säga en form av interaktion med datorer som blivit integrerad i aktiviteter och objekt i omgivningen.) Framförallt tjänster och enheters uppdykande och försvinnande, mänsklig överbelastning och tjänstens relevans är avgörande utmaningar. Denna avhandling behandlar kvaliteten på användningen av tjänster och enheter, genom att införa en sofistikerad upptäcktsmodell med hjälp av nya lager i tjänsteupptäcktsprocessen. Denna modell tillåter användning av tjänster och enheter när nuvarande upptäcktsprocess och urval av dessa skulle vara opraktiskt, genom att ge förslag baserat på användarnas aktiviteter, domänkunskap och omvärldskunskap. För att utforska vad som händer när ett sådant system är på plats, gjordes ett så kallat Wizard of Oz experiment i ledningscentralen på en brandstation. (Ett Wizard Of Oz experiment är ett experiment där användaren tror att de interagerar med en dator, men i själva verket är det en människa som agerar dator.)

För att hantera tjänste- och enhetsupptäckt i Ubiquitous Computing utvecklades nya lager och en testplattform tillsammans med en metod för att utveckla och utvärdera system för tjänste- och enhetsupptäckt. Det första lagret, som vi kallar Förbättrat Traditionellt Lager (FTL), studerades genom att utveckla ODEN och inkludera FTL i den. ODEN utökar det traditionella, datororienterade tjänste- och enhetsupptäcktslagret genom att införa en ontologibaserad semantik och en logisk regelmotor. Det andra skiktet, som vi kallar Relevant Tjänst Lager, undersöktes genom att införliva det i systemet MAGUBI. MAGUBI tar sig an de mänskliga aspekterna i den utmaning som vi benämner relevant tjänste- och enhetsupptäckt, genom att använda modeller av användarnas aktiviteter, domänkunskap och kunskap om världen i kombination med regelmotorer.

RESPONSORIA är en webbaserad plattform med desktoputseende och desktopkänsla, och är ett system för utvärdering av ovanstående utmaning tillsammans med de tidigare systemen. Detta system utforskar tjänste- och enhetsupptäckt i ett tjänsteorienterat scenario. RESPONSORIA tar ett ledningsscenario för räddningstjänst där flera aktörer och organisationer arbetar tillsammans på en kommunal nivå. RESPONSORIA låg till grund för ett Wizard of Oz experiment där experimentdeltagarna var professionella räddningsledare. Resultatet underströk vikten av namngivning av tjänster och enheter samt hur dessa presenteras för användaren. Dessutom finns det oenighet bland användare om vad som är den optimala service-/enhets-rekommendationen, men resultaten visar att goda rekommendationer är värdefulla och systemet kan ses som en partner.

Service discovery is an important part of pervasive computing. Present mainstream service discovery protocols are to a high degree focused on the immediate properties of services and devices, as well as ensuring a high degree of connectivity. As the amount of discovered available services and devices go up, the challenge becomes how to ensure that systems and humans find relevant services, without overloading the systems or humans. Magubi is a model and implementation that is able to not only do advanced standard service discovery, but also, by viewing human tasks and activities as services, is able to expand the realm of service discovery for pervasive computing while addressing the overload challenge. Here, we present the model, and how we model services, humans, and activities. By taking the magubi-approach, service discovery also becomes proactive and is able to assist in a wide range of human endeavors.

Developing user interfaces for a heterogeneous environment is a difficult challenge. Partial distribution of the user interface is an event harder one. Specifically providing developers with means of describing and controlling how components move around as devices are included or removed We present an approach to overcome these challenges, by combining ontologies with reasoning engines. Our tool MaDoE uses Protégé in combination with Jess to exemplify this in a simulated home setting. Our approach allows system developers to take advantage of the formal knowledge in the ontologies as well harnessing the power of rules inside the expert system when they design distributed user interfaces.

Ubiquitous computing (Ubicomp) increases in proliferation. Multiple and ever growing in numbers, computational devices are now at the users' disposal throughout the physical environment, while simultaneously being effectively invisible. Consequently, a significant challenge is service discovery. Services may for instance be physical, such as printing a document, or virtual, such as communicating information. The existing solutions, such as Bluetooth and UPnP, address part of the issue, specifically low-level physical interconnectivity. Still absent are solutions for high-level challenges, such as connecting users with appropriate services. In order to provide appropriate service offerings, service discovery in Ubicomp must take the users' context, tasks, goals, intentions, and available resources into consideration. It is possible to divide the high-level service-discovery issue into two parts; inadequate service models, and insufficient common-sense models of human activities.

This thesis contributes to service discovery in Ubicomp, by arguing that in order to meet these high-level challenges, a new layer is required. Furthermore, the thesis presents a prototype implementation of this new service-discovery architecture and model. The architecture consists of hardware, ontology-layer, and common-sense-layer. This work addresses the ontology and common-sense layers. Subsequently, implementation is divided into two parts; Oden and Magubi. Oden addresses the issue of inadequate service models through a combination of service-ontologies in concert with logical reasoning engines, and Magubi addresses the issue of insufficient common-sense models of human activities, by using common sense models in combination with rule engines. The synthesis of these two stages enables the system to reason about services, devices, and user expectations, as well as to make suitable connections to satisfy the users' overall goal.

Designing common-sense models and service ontologies for a Ubicomp environment is a non-trivial task. Despite this, we believe that if correctly done, it might be possible to reuse at least part of the knowledge in different situations. With the ability to reason about services and human activities it is possible to decide if, how, and where to present the services to the users. The solution is intended to off-load users in diverse Ubicomp environments as well as provide a more relevant service discovery.

With the evolvingfunctionality in television-based Tvbasedinformation andentertainment appliances, there is an increased need to enableusers input text through remote control devices. We present a noveltext input method, The Numpad Typer TNT, for interactive TV,multimediahome terminals or other similar applications. Embodied ina TV remote control and guided by a visual map on the Tvscreen, TNTwas designed for consistent spatial Stimuli-Response S-Rcompatibility and consistency of use. Fiveusers tested TNT in tensessions of 45-minutes. This initial investigation showed thatusers on average could type 9.3 and 17.7 correct words per minutewith TNT doing the slowest and the fastest session respectively.The study also showed that the users found the TNT method easy tograsp and fun to use. Subjectively the participants felttheymastered the method rather quickly in comparison to theiractual speed improvement.