<p>The purpose of the study is to explore the context, from the users’ perspective, in order to find relevant context parameters that can be useful in the development of the future context-aware technology. The goal is to find some of the context parameters relevant to the situated activity and investigate to what extent and in which way they influence the user in everyday planning activities.</p><p>The method used in the study was based on scenario descriptions. A total of 41 participants reported how they would have acted in the different situations and they also rated how important they believed the different context factors were in the situations. Analyses were made to reveal relationships between context factors and service properties used by the participants in the scenarios.</p><p>In the study several interesting relationships between context factors and the use of services were discovered. The level of urgency was in several situations considered to be important, and it was also found to have an impact on how the participants chose to communicate. The cost was introduced by the participants during the study. It seemed to be important; however, in situations with high urgency it became less important. The study revealed a potential relationship between the risk of disturbing the people in the vicinity and the effort to communicate quietly. Another interesting finding was the relationship between privacy and the choice of modality when communicating: voice-based services were avoided. Further, the importance of privacy and disturbance also appeared to have greater influence in non-anonymous situations than in anonymous.</p> / <p>Syftet med studien är att undersöka kontexten, utifrån användarens perspektiv, för att kunna hitta relevanta kontextfaktorer som kan vara användbara i utvecklingen av kontextmedveten teknologi. Målet är att finna kontextfaktorer som är relevanta för den pågående aktiviteten och undersöka i vilken utsträckning och på vilka sätt dessa faktorer påverkar användaren i de dagliga planeringsaktiviteterna.</p><p>Metoden som användes i studien baserades på scenariobeskrivningar. 41 stycken försöksdeltagare fick beskriva hur de skulle ha handlat i de olika situationerna och de fick också skatta hur viktiga de olika kontextfaktorerena var i situationerna. Analyser genomfördes för att finna samband mellan kontextfaktorer och egenskaper hos de tjänster som försöksdeltagarna använde sig av i scenarierna.</p><p>I studien upptäcktes en rad intressanta relationer mellan kontextfaktorer och användningen av tjänster. Exempelvis ansågs nivån av brådska vara betydelsefull i flera situationer och den verkade också ha inverkan på hur försöksdeltagarna valde att kommunicera. Försöksdeltagarna introducerade under studien kontextfaktorn kostnad. Kostnaden påverkade valet av tjänster men blev mindre betydande i situationer med stor brådska. Studien visade också på potentiella samband mellan risken att störa människor i sin omgivning och viljan att kommunicera tyst. En annan intressant upptäckt var sambandet mellan avskildhet och kommunikationssätt: röstbaserade tjänster undveks när andra människor fanns i närheten. Dessutom verkade det som om det var viktigare att värna om sin avskildhet och att inte störa andra i ickeanonyma situationer än i situationer där man var helt anonym.</p>

Context-aware computing is based on using knowledge about the current context. Interpretation of current context to an understandable knowledge is carried out by reasoning over context and in some cases by matching the current context with the desired context. In this thesis we concentrated on context matching issue in context-aware computing domain. Context matching can be done in various ways like it is done in other matching processes. Our matching approach is best matching in order to generate granular similarity results and not to be limited to Boolean values. We decided to use Ontology as the encoded domain knowledge for our matching method. Context matching method is related to the method that we represent context. We selected conceptual graphs to represent the context. We proposed a generic algorithm for context matching based on the ontological information that benefit from the conceptual graph theory and its advantages.

Current trends in society and technology make interruption a central human computer interaction problem. Many intelligent computer systems exist, but one that determines when best to interact with a user at appropriate times as s/he performs computer-based tasks does not. In this work, an Interaction Algorithm was designed, developed and evaluated that draws from a user model and real-time observations of the user’s actions as s/he works on computer-based tasks to determine ideal times to interact with the user. This research addresses the complex problem of determining the precise time to interrupt a user and how to best support him/her during and after the interruption task. Many sub-problems have been taken into account such as determining the task difficulty, the intent of the user as s/he is performing the task and how to incorporate personal user characteristics. This research is quite timely as the number of interruptions people experience on a daily basis has grown considerably over the last decade and this growth has not shown any signs of subsiding. Furthermore, with the exponential growth of mobile computing, interruptions are permeating the user experience. Thus, systems must be developed to manage interruptions by reasoning about ideal timings of interactions and determining appropriate notification formats. This research shed light on this problem as described below: 1. The algorithm developed uses a user model in its’ reasoning computations. Most of the research in this area has focused on task-based contextual information when designing systems that reason about interruptions. Researchers support additional work should be done in this area by including subjective preferences. 2. The algorithm’s performance is quite promising at 96% accuracy in several models created. 3. The algorithm was implemented using an advanced machine learning technology—an Adaptive Neural-Fuzzy Inference System—which is a novel contribution. 4. The algorithm developed does not rely on any user involvement. In other systems, users laboriously review video sessions after working with the system and record interruption annotations so that the system can learn. 5. This research shed light on reasoning about ideal interruption points for free-form tasks. Currently, this is an unsolved problem.

No description available.

In this thesis, we focused on two problems in mobile application development: contextualization and large-scale testing. We identified the limitations of current contextualization and testing solutions. On one hand, advanced-remote-computing- based mobilization does not provide context awareness to the mobile applications it mobilized, so we presented contextify to provide context awareness to them without rewriting the applications or changing their source code. Evaluation results and user surveys showed that contextify-contextualized applications reduce users' time and effort to complete tasks. On the other hand, current mobile application testing solutions cannot conduct tests at the UI level and in a large-scale manner simultaneously, so we presented and implemented automated cloud computing (ACT) to achieve this goal. Evaluation results showed that ACT can support a large number of users and it is stable, cost-efficiency as well as time-efficiency.

Knowing the semantic category of a robot's current position not only facilitates the robot's navigation, but also greatly improves its ability to serve human needs and to interpret the scene. Visual Place Categorization (VPC) is addressed in this dissertation, which refers to the problem of predicting the semantic category of a place using visual information collected from an autonomous robot platform. Census Transform (CT) histogram and Histogram Intersection Kernel (HIK) based visual codebooks are proposed to represent an image. CT histogram encodes the stable spatial structure of an image that reflects the functionality of a location. It is suitable for categorizing places and has shown better performance than commonly used descriptors such as SIFT or Gist in the VPC task. HIK has been shown to work better than the Euclidean distance in classifying histograms. We extend it in an unsupervised manner to generate visual codebooks for the CT histogram descriptor. HIK codebooks help CT histogram to deal with the huge variations in VPC and improve system accuracy. A computational method is also proposed to generate HIK codebooks in an efficient way. The first significant VPC dataset in home environments is collected and is made publicly available, which is also used to evaluate the VPC system based on the proposed techniques. The VPC system achieves promising results for this challenging problem, especially for important categories such as bedroom, bathroom, and kitchen. The proposed techniques achieved higher accuracies than competing descriptors and visual codebook generation methods.

Location information is used to provide a diverse range of services to users such as emergency, navigation, billing, security, information and advertising services. This information is derived from a broad range of indoor and outdoor technologies. The location information thus derived is of different granularity, different co-ordination system and is controlled by numerous service providers. In addition to this, broad selections of devices are used for providing these services. Having a diverse range of applications requiring location information at different levels of granularity, the need to export location information across multiple devices and the existence of different location determination technologies necessitates the need for heterogeneous location network. These networks derive location information from multiple sources and provides various location-based services to users irrespective of the medium, device or technology used. Security, user privacy and management of location information are some of the important issues that need to be addressed. The main contribution of this thesis is the design of a secure and privacy assured heterogeneous location architecture. A formal methodology was chosen to design the heterogeneous location architecture. The design of the architecture resulted in a novel key distribution protocol and a model for information flow that can be easily encapsulated into applications or architectures having similar requirements. The research also resulted in the enhancement of a proposed location framework for securing critical infrastructures using context-aware self-defending objects. The proposed enhanced framework helps to negate the security vulnerabilities introduced through the use of general-purpose computer systems in critical infrastructures.

Computing is increasingly pervading the activities of our everyday lives: at work, at home, and out on the town. When designing these pervasive systems there is a need to better understand and incorporate the context of use and yet there are limited empirical investigations into what constitutes this context. The user’s physical and social situation is an important part of their context when operating in an urban environment and thus needs to be understood and included in the interaction design of context-aware pervasive computing. This thesis has combined ideas from human computer interaction (HCI) and architecture to investigate indexicality in interface design as an instrument for incorporating physical and social context of the built environment into context-aware pervasive computing. Indexicality in interface design is a new approach to designing HCI for pervasive computing that relies on knowledge of current context to implicitly communicate between system and user. It reduces the amount of information that needs to be explicitly displayed in the interface while maintaining the usefulness and understandability of the communication.

Thesis (Ph.D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Abler, Randal T.; Committee Member: Copeland, John A.; Committee Member: Haas, Kevin; Committee Member: Moore II, Elliot; Committee Member: Owen III, Henry L.

Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2009. / Committee Chair: Abowd, Gregory; Committee Member: Edwards, Keith; Committee Member: Grinter, Rebecca; Committee Member: LaMarca, Anthony; Committee Member: Starner, Thad.