Proximity-based systems: Incorporating mobility and scalability through proximity sensing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis argues that the concept of spatial proximity offers a viable and practical option for the development of context-aware systems for highly mobile and dynamic environments. Such systems would overcome the shortcomings experienced by today’s location-based and infrastructure dependent systems whose ability to deliver context-awareness is prescribed by their infrastructure. The proposed architecture will also allow for scalable interaction as against the single level of interaction in existing systems which limits services to a particular sized area. The thesis examines the concept of spatial proximity and demonstrates how this concept can be exploited to take advantage of technological convergence to offer mobility and scalability to systems. It discusses the design of a proximity-based system that can deliver scalable context-aware services in highly mobile and dynamic environments. It explores the practical application of this novel design in a proximity-sensitive messaging application by creating a proof-of-concept prototype. The proof-of-concept prototype is used to evaluate the design as well as to elicit user views and expectations about a proximity-based approach. Together these provide a valuable insight into the applicability of the proximity-based approach for designing context-aware systems. The design and development work discussed in the thesis presents a Proximity-Sensitive System Architecture that can be adapted for a variety of proximity-sensitive services. This is illustrated by means of examples, including a variety of context-aware messaging applications. The thesis also raises issues for information delivery, resource sharing, and human-computer interaction. While the technological solution (proximity-based messaging) offered is only one among several that can be developed using this architecture, it offers the opportunity to stimulate ideas in the relatively new field of proximity and technological convergence research, and contributes to a better understanding of their potential role in offering context-aware services

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users’ demands in a complicated environment and suggested the feasibility by the experimental results

Proximity-based systems : incorporating mobility and scalability through proximity sensing

This thesis argues that the concept of spatial proximity offers a viable and practical option for the development of context-aware systems for highly mobile and dynamic environments. Such systems would overcome the shortcomings experienced by today’s location-based and infrastructure dependent systems whose ability to deliver context-awareness is prescribed by their infrastructure. The proposed architecture will also allow for scalable interaction as against the single level of interaction in existing systems which limits services to a particular sized area. The thesis examines the concept of spatial proximity and demonstrates how this concept can be exploited to take advantage of technological convergence to offer mobility and scalability to systems. It discusses the design of a proximity-based system that can deliver scalable context-aware services in highly mobile and dynamic environments. It explores the practical application of this novel design in a proximity-sensitive messaging application by creating a proof-of-concept prototype. The proof-of-concept prototype is used to evaluate the design as well as to elicit user views and expectations about a proximity-based approach. Together these provide a valuable insight into the applicability of the proximity-based approach for designing context-aware systems. The design and development work discussed in the thesis presents a Proximity-Sensitive System Architecture that can be adapted for a variety of proximity-sensitive services. This is illustrated by means of examples, including a variety of context-aware messaging applications. The thesis also raises issues for information delivery, resource sharing, and human-computer interaction. While the technological solution (proximity-based messaging) offered is only one among several that can be developed using this architecture, it offers the opportunity to stimulate ideas in the relatively new field of proximity and technological convergence research, and contributes to a better understanding of their potential role in offering context-aware services.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Proximity-based systems : incorporating mobility and scalability through proximity sensing

This thesis argues that the concept of spatial proximity offers a viable and practical option for the development of context-aware systems for highly mobile and dynamic environments. Such systems would overcome the shortcomings experienced by today’s location-based and infrastructure dependent systems whose ability to deliver context-awareness is prescribed by their infrastructure. The proposed architecture will also allow for scalable interaction as against the single level of interaction in existing systems which limits services to a particular sized area. The thesis examines the concept of spatial proximity and demonstrates how this concept can be exploited to take advantage of technological convergence to offer mobility and scalability to systems. It discusses the design of a proximity-based system that can deliver scalable context-aware services in highly mobile and dynamic environments. It explores the practical application of this novel design in a proximity-sensitive messaging application by creating a proof-of-concept prototype. The proof-of-concept prototype is used to evaluate the design as well as to elicit user views and expectations about a proximity-based approach. Together these provide a valuable insight into the applicability of the proximity-based approach for designing context-aware systems. The design and development work discussed in the thesis presents a Proximity-Sensitive System Architecture that can be adapted for a variety of proximity-sensitive services. This is illustrated by means of examples, including a variety of context-aware messaging applications. The thesis also raises issues for information delivery, resource sharing, and human-computer interaction. While the technological solution (proximity-based messaging) offered is only one among several that can be developed using this architecture, it offers the opportunity to stimulate ideas in the relatively new field of proximity and technological convergence research, and contributes to a better understanding of their potential role in offering context-aware services.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Designing a Situational Awareness Information Display: Adopting an Affordance-Based Framework to Amplify User Experience in Environmental Interaction Design

User experience remains a crucial consideration when assessing the successfulness of information visualization systems. The theory of affordances provides a robust framework for user experience design. In this article, we demonstrate a design case that employs an affordance-based framework and evaluate the information visualization display design. SolarWheels is an interactive information visualization designed for large display walls in computer network control rooms to help cybersecurity analysts become aware of network status and emerging issues. Given the critical nature of this context, the status and performance of a computer network must be precisely monitored and remedied in real time. In this study, we consider various aspects of affordances in order to amplify the user experience via visualization and interaction design. SolarWheels visualizes the multilayer multidimensional computer network issues with a series of integrated circular visualizations inspired by the metaphor of the solar system. To amplify user interaction and experience, the system provides a three-zone physical interaction that allows multiple users to interact with the system. Users can read details at different levels depending on their distance from the display. An expert evaluation study, based on a four-layer affordance framework, was conducted to assess and improve the interactive visualization design

Out on the town:a Socio-Physical Approach to the Design of a Context-Aware Urban Guide

As urban environments become increasingly hybridized, mixing the social, built, and digital in interesting ways, designing for computing in the city presents new challenges—how do we understand such hybridization, and then respond to it as designers? Here we synthesize earlier work in human-computer interaction, sociology and architecture in order to deliberately influence the design of digital systems with an understanding of their built and social context of use. We propose, illustrate, and evaluate a multidisciplinary approach combining rapid ethnography, architectural analysis, design sketching, and paper prototyping. Following the approach we are able to provide empirically grounded representations of the socio-physical context of use, in this case people socializing in urban spaces. We then use this understanding to influence the design of a context aware system to be used while out on the town. We believe that the approach is of value more generally, particularly when achieving powerfully situated interactions is the design ambition.

Ontology-based user modeling in an augmented audio reality system for museums

Ubiquitous computing is a challenging area that allows us to further our understanding and techniques of context-aware and adaptive systems. Among the challenges is the general problem of capturing the larger context in interaction from the perspective of user modeling and human–computer interaction (HCI). The imperative to address this issue is great considering the emergence of ubiquitous and mobile computing environments. This paper provides an account of our addressing the specific problem of supporting functionality as well as the experience design issues related to museum visits through user modeling in combination with an audio augmented reality and tangible user interface system. This paper details our deployment and evaluation of ec(h)o – an augmented audio reality system for museums. We explore the possibility of supporting a context-aware adaptive system by linking environment, interaction object and users at an abstract semantic level instead of at the content level. From the user modeling perspective ec(h)o is a knowledge based recommender system. In this paper we present our findings from user testing and how our approach works well with an audio and tangible user interface within a ubiquitous computing system. We conclude by showing where further research is needed

Bringing context-aware access to the web through spoken interaction

The web has become the largest repository of multimedia information and its convergence with telecommunications is now bringing the benefits of web technology to hand-held devices. To optimize data access using these devices and provide services which meet the user needs through intelligent information retrieval, the system must sense and interpret the user environment and the communication context. In addition, natural spoken conversation with handheld devices makes possible the use of these applications in environments in which the use of GUI interfaces is not effective, provides a more natural human-computer interaction, and facilitates access to the web for people with visual or motor disabilities, allowing their integration and the elimination of barriers to Internet access. In this paper, we present an architecture for the design of context-aware systems that use speech to access web services. Our contribution focuses specifically on the use of context information to improve the effectiveness of providing web services by using a spoken dialog system for the user-system interaction. We also describe an application of our proposal to develop a context-aware railway information system, and provide a detailed evaluation of the influence of the context information in the quality of the services that are supplied.Research funded by projects CICYT TIN2011-28620-C02-01, CICYT TEC 2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

Self-adaptive unobtrusive interactions of mobile computing systems

[EN] In Pervasive Computing environments, people are surrounded by a lot of embedded services. Since pervasive devices, such as mobile devices, have become a key part of our everyday life, they enable users to always be connected to the environment, making demands on one of the most valuable resources of users: human attention. A challenge of the mobile computing systems is regulating the request for users¿ attention. In other words, service interactions should behave in a considerate manner by taking into account the degree to which each service intrudes on the user¿s mind (i.e., the degree of obtrusiveness). The main goal of this paper is to introduce self-adaptive capabilities in mobile computing systems in order to provide non-disturbing interactions. We achieve this by means of an software infrastructure that automatically adapts the service interaction obtrusiveness according to the user¿s context. This infrastructure works from a set of high-level models that define the unobtrusive adaptation behavior and its implication with the interaction resources in a technology-independent way. Our infrastructure has been validated through several experiments to assess its correctness, performance, and the achieved user experience through a user study.This work has been developed with the support of MINECO under the project SMART-ADAPT TIN2013-42981-P, and co-financed by the Generalitat Valenciana under the postdoctoral fellowship APOSTD/2016/042.Gil Pascual, M.; Pelechano Ferragud, V. (2017). Self-adaptive unobtrusive interactions of mobile computing systems. Journal of Ambient Intelligence and Smart Environments. 9(6):659-688. https://doi.org/10.3233/AIS-170463S65968896Aleksy, M., Butter, T., & Schader, M. (2008). Context-Aware Loading for Mobile Applications. Lecture Notes in Computer Science, 12-20. doi:10.1007/978-3-540-85693-1_3Y. Bachvarova, B. van Dijk and A. Nijholt, Towards a unified knowledge-based approach to modality choice, in: Proc. Workshop on Multimodal Output Generation (MOG), 2007, pp. 5–15.Barkhuus, L., & Dey, A. (2003). Is Context-Aware Computing Taking Control away from the User? Three Levels of Interactivity Examined. Lecture Notes in Computer Science, 149-156. doi:10.1007/978-3-540-39653-6_12Bellotti, V., & Edwards, K. (2001). Intelligibility and Accountability: Human Considerations in Context-Aware Systems. Human–Computer Interaction, 16(2-4), 193-212. doi:10.1207/s15327051hci16234_05D. Benavides, P. Trinidad and A. Ruiz-Cortés, Automated reasoning on feature models, in: Proceedings of the 17th International Conference on Advanced Information Systems Engineering, CAiSE’05, Springer-Verlag, Berlin, 2005, pp. 491–503.Bernsen, N. O. (1994). Foundations of multimodal representations: a taxonomy of representational modalities. Interacting with Computers, 6(4), 347-371. doi:10.1016/0953-5438(94)90008-6Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., & Riboni, D. (2010). A survey of context modelling and reasoning techniques. Pervasive and Mobile Computing, 6(2), 161-180. doi:10.1016/j.pmcj.2009.06.002Blumendorf, M., Lehmann, G., & Albayrak, S. (2010). Bridging models and systems at runtime to build adaptive user interfaces. Proceedings of the 2nd ACM SIGCHI symposium on Engineering interactive computing systems - EICS ’10. doi:10.1145/1822018.1822022D.M. Brown, Communicating Design: Developing Web Site Documentation for Design and Planning, 2nd edn, New Riders Press, 2010.J. Bruin, Statistical Analyses Using SPSS, 2011, http://www.ats.ucla.edu/stat/spss/whatstat/whatstat.htm#1sampt.J. Cámara, G. Moreno and D. Garlan, Reasoning about human participation in self-adaptive systems, in: SEAMS 2015, 2015, pp. 146–156.Campbell, A., & Choudhury, T. (2012). From Smart to Cognitive Phones. IEEE Pervasive Computing, 11(3), 7-11. doi:10.1109/mprv.2012.41Y. Cao, M. Theune and A. Nijholt, Modality effects on cognitive load and performance in high-load information presentation, in: Proceedings of the 14th International Conference on Intelligent User Interfaces, IUI’09, ACM, New York, 2009, pp. 335–344.Chang, F., & Ren, J. (2007). Validating system properties exhibited in execution traces. Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering - ASE ’07. doi:10.1145/1321631.1321723H. Chen and J.P. Black, A quantitative approach to non-intrusive computing, in: Mobiquitous’08: Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), ICST, Brussels, 2008, pp. 1–10.Chittaro, L. (2010). Distinctive aspects of mobile interaction and their implications for the design of multimodal interfaces. Journal on Multimodal User Interfaces, 3(3), 157-165. doi:10.1007/s12193-010-0036-2Clerckx, T., Vandervelpen, C., & Coninx, K. (2008). Task-Based Design and Runtime Support for Multimodal User Interface Distribution. Lecture Notes in Computer Science, 89-105. doi:10.1007/978-3-540-92698-6_6Cook, D. J., & Das, S. K. (2012). Pervasive computing at scale: Transforming the state of the art. Pervasive and Mobile Computing, 8(1), 22-35. doi:10.1016/j.pmcj.2011.10.004Cornelissen, B., Zaidman, A., van Deursen, A., Moonen, L., & Koschke, R. (2009). A Systematic Survey of Program Comprehension through Dynamic Analysis. IEEE Transactions on Software Engineering, 35(5), 684-702. doi:10.1109/tse.2009.28Czarnecki, K. (2004). Generative Software Development. Lecture Notes in Computer Science, 321-321. doi:10.1007/978-3-540-28630-1_33M. de Sá, C. Duarte, L. Carriço and T. Reis, Designing mobile multimodal applications, in: Information Science Reference, 2010, pp. 106–136, Chapter 5.C. Duarte and L. Carriço, A conceptual framework for developing adaptive multimodal applications, in: Proceedings of the 11th International Conference on Intelligent User Interfaces, IUI’06, ACM, New York, 2006, pp. 132–139.Evers, C., Kniewel, R., Geihs, K., & Schmidt, L. (2014). The user in the loop: Enabling user participation for self-adaptive applications. Future Generation Computer Systems, 34, 110-123. doi:10.1016/j.future.2013.12.010Fagin, R., Halpern, J. Y., & Megiddo, N. (1990). A logic for reasoning about probabilities. Information and Computation, 87(1-2), 78-128. doi:10.1016/0890-5401(90)90060-uFerscha, A. (2012). 20 Years Past Weiser: What’s Next? IEEE Pervasive Computing, 11(1), 52-61. doi:10.1109/mprv.2011.78Floch, J., Frà, C., Fricke, R., Geihs, K., Wagner, M., Lorenzo, J., … Scholz, U. (2012). Playing MUSIC - building context-aware and self-adaptive mobile applications. Software: Practice and Experience, 43(3), 359-388. doi:10.1002/spe.2116Gibbs, W. W. (2005). Considerate Computing. Scientific American, 292(1), 54-61. doi:10.1038/scientificamerican0105-54Gil, M., Giner, P., & Pelechano, V. (2011). Personalization for unobtrusive service interaction. Personal and Ubiquitous Computing, 16(5), 543-561. doi:10.1007/s00779-011-0414-0Gil Pascual, M. (s. f.). Adapting Interaction Obtrusiveness: Making Ubiquitous Interactions Less Obnoxious. A Model Driven Engineering approach. doi:10.4995/thesis/10251/31660Haapalainen, E., Kim, S., Forlizzi, J. F., & Dey, A. K. (2010). Psycho-physiological measures for assessing cognitive load. Proceedings of the 12th ACM international conference on Ubiquitous computing - Ubicomp ’10. doi:10.1145/1864349.1864395Hallsteinsen, S., Geihs, K., Paspallis, N., Eliassen, F., Horn, G., Lorenzo, J., … Papadopoulos, G. A. (2012). A development framework and methodology for self-adapting applications in ubiquitous computing environments. Journal of Systems and Software, 85(12), 2840-2859. doi:10.1016/j.jss.2012.07.052Hassenzahl, M. (2004). The Interplay of Beauty, Goodness, and Usability in Interactive Products. Human-Computer Interaction, 19(4), 319-349. doi:10.1207/s15327051hci1904_2Hassenzahl, M., & Tractinsky, N. (2006). User experience - a research agenda. Behaviour & Information Technology, 25(2), 91-97. doi:10.1080/01449290500330331Ho, J., & Intille, S. S. (2005). Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’05. doi:10.1145/1054972.1055100Horvitz, E., Kadie, C., Paek, T., & Hovel, D. (2003). Models of attention in computing and communication. Communications of the ACM, 46(3), 52. doi:10.1145/636772.636798Horvitz, E., Koch, P., Sarin, R., Apacible, J., & Subramani, M. (2005). Bayesphone: Precomputation of Context-Sensitive Policies for Inquiry and Action in Mobile Devices. Lecture Notes in Computer Science, 251-260. doi:10.1007/11527886_33Kephart, J. O., & Chess, D. M. (2003). The vision of autonomic computing. Computer, 36(1), 41-50. doi:10.1109/mc.2003.1160055Korpipaa, P., Malm, E.-J., Rantakokko, T., Kyllonen, V., Kela, J., Mantyjarvi, J., … Kansala, I. (2006). Customizing User Interaction in Smart Phones. IEEE Pervasive Computing, 5(3), 82-90. doi:10.1109/mprv.2006.49S. Lemmelä, A. Vetek, K. Mäkelä and D. Trendafilov, Designing and evaluating multimodal interaction for mobile contexts, in: Proceedings of the 10th International Conference on Multimodal Interfaces, ICMI’08, ACM, New York, 2008, pp. 265–272.Lim, B. Y. (2010). Improving trust in context-aware applications with intelligibility. Proceedings of the 12th ACM international conference adjunct papers on Ubiquitous computing - Ubicomp ’10. doi:10.1145/1864431.1864491J.-Y. Mao, K. Vredenburg, P.W. Smith and T. Carey, User-centered design methods in practice: A survey of the state of the art, in: Proceedings of the 2001 Conference of the Centre for Advanced Studies on Collaborative Research, CASCON’01, IBM Press, 2001, p. 12.Maoz, S. (2009). Using Model-Based Traces as Runtime Models. Computer, 42(10), 28-36. doi:10.1109/mc.2009.336Mayer, R. E., & Moreno, R. (2003). Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educational Psychologist, 38(1), 43-52. doi:10.1207/s15326985ep3801_6Motti, V. G., & Vanderdonckt, J. (2013). A computational framework for context-aware adaptation of user interfaces. IEEE 7th International Conference on Research Challenges in Information Science (RCIS). doi:10.1109/rcis.2013.6577709R. Murch, Autonomic Computing, IBM Press, 2004.Obrenovic, Z., Abascal, J., & Starcevic, D. (2007). Universal accessibility as a multimodal design issue. Communications of the ACM, 50(5), 83-88. doi:10.1145/1230819.1241668Patterson, D. J., Baker, C., Ding, X., Kaufman, S. J., Liu, K., & Zaldivar, A. (2008). Online everywhere. Proceedings of the 10th international conference on Ubiquitous computing - UbiComp ’08. doi:10.1145/1409635.1409645Pielot, M., de Oliveira, R., Kwak, H., & Oliver, N. (2014). Didn’t you see my message? Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI ’14. doi:10.1145/2556288.2556973Poppinga, B., Heuten, W., & Boll, S. (2014). Sensor-Based Identification of Opportune Moments for Triggering Notifications. IEEE Pervasive Computing, 13(1), 22-29. doi:10.1109/mprv.2014.15S. Ramchurn, B. Deitch, M. Thompson, D. De Roure, N. Jennings and M. Luck, Minimising intrusiveness in pervasive computing environments using multi-agent negotiation, in: Mobile and Ubiquitous Systems: Networking and Services, MOBIQUITOUS 2004. The First Annual International Conference on, 2004, pp. 364–371.C. Roda, Human Attention and Its Implications for Human-Computer Interaction, Cambridge University Press, 2011.S. Rosenthal, A.K. Dey and M. Veloso, Using decision-theoretic experience sampling to build personalized mobile phone interruption models, in: Proceedings of the 9th International Conference on Pervasive Computing, Pervasive 2011, Springer-Verlag, Berlin, 2011, pp. 170–187.E. Rukzio, K. Leichtenstern and V. Callaghan, An experimental comparison of physical mobile interaction techniques: Touching, pointing and scanning, in: 8th International Conference on Ubiquitous Computing, UbiComp 2006, Orange County, California, 2006.Serral, E., Valderas, P., & Pelechano, V. (2010). Towards the Model Driven Development of context-aware pervasive systems. Pervasive and Mobile Computing, 6(2), 254-280. doi:10.1016/j.pmcj.2009.07.006D. Siewiorek, A. Smailagic, J. Furukawa, A. Krause, N. Moraveji, K. Reiger, J. Shaffer and F.L. Wong, Sensay: A context-aware mobile phone, in: Proceedings of the 7th IEEE International Symposium on Wearable Computers, ISWC’03, IEEE Computer Society, Washington, 2003, p. 248.Tedre, M. (2006). What should be automated? Proceedings of the 1st ACM international workshop on Human-centered multimedia - HCM ’06. doi:10.1145/1178745.1178753M. Valtonen, A.-M. Vainio and J. Vanhala, Proactive and adaptive fuzzy profile control for mobile phones, in: IEEE International Conference on Pervasive Computing and Communications, 2009, PerCom, 2009, pp. 1–3.Vastenburg, M. H., Keyson, D. V., & de Ridder, H. (2007). Considerate home notification systems: a field study of acceptability of notifications in the home. Personal and Ubiquitous Computing, 12(8), 555-566. doi:10.1007/s00779-007-0176-xWarnock, D., McGee-Lennon, M., & Brewster, S. (2011). The Role of Modality in Notification Performance. Lecture Notes in Computer Science, 572-588. doi:10.1007/978-3-642-23771-3_43Weiser, M., & Brown, J. S. (1997). The Coming Age of Calm Technology. Beyond Calculation, 75-85. doi:10.1007/978-1-4612-0685-9_6Van Woensel, W., Gil, M., Casteleyn, S., Serral, E., & Pelechano, V. (2013). Adapting the Obtrusiveness of Service Interactions in Dynamically Discovered Environments. Mobile and Ubiquitous Systems: Computing, Networking, and Services, 250-262. doi:10.1007/978-3-642-40238-8_2