Mobile location recognition by capturing images of the environment (visual localization) is a promising technique for indoor navigation in arbitrary surroundings. However, it has barely been investigated so far how the user interface (UI) can cope with the challenges of the vision-based localization technique, such as varying quality of the query images. We implemented a novel UI for visual localization, consisting of Virtual Reality (VR) and Augmented Reality (AR) views that actively communicate and ensure localization accuracy. If necessary, the system encourages the user to point the smartphone at distinctive regions to improve localization quality. We evaluated the UI in a experimental navigation task with a prototype, informed by initial evaluation results using design mockups. We found that VR can contribute to efficient and effective indoor navigation even at unreliable location and orientation accuracy. We discuss identified challenges and share lessons learned as recommendations for future work.

Mobility and independence are key aspects for self-determined living in today's world and demographic change presents the challenge to retain these aspects for the aging population. Augmented Reality (AR) user interfaces might support the elderly, for example, when navigating as pedestrians or by explaining how devices and mobility aids work and how they are maintained. This poster reports on the results of practical field tests with elderly subjects testing handheld AR applications. The main finding is that common handheld AR user interfaces are not suited for the elderly because they require the user to hold up the device so the back-facing camera captures the object or environment related to which digital information shall be presented. Tablet computers are too heavy and they do not provide sufficient grip to hold them over a long period of time. One possible alternative is using head-mounted displays (HMD). We present the promising results of a user test evaluating whether elderly people can deal with AR interfaces on a lightweight HMD. We conclude with an outlook to improved handheld AR user interfaces that do not require continuously holding up the device, which we hope are better suited for the elderly.

In this paper, we review the use of gameful design in the automotive domain. Outside of vehicles the automotive industry is mainly using gameful design for marketing and brand forming. For in-vehicle applications and for applications directly connected to real vehicles, the main usage scenarios of gameful design are navigation, eco-driving and driving safety. The objective of this review is to answer the following questions: (1) What elements of gameful design are currently used in the automotive industry? (2) What other automotive applications could be realized or enhanced by applying gameful design? (3) What are the challenges and limitations of gameful design in this domain especially for in-vehicle applications? The review concludes that the use of gameful design for in-vehicle applications seems to be promising. However, gamified applications related to the serious task of driving require thought-out rules and extensive testing in order to achieve the desired goal.

Self-reporting techniques, such as data logging or a diary, are frequently used in long-term studies, but prone to subjects' forgetfulness and other sources of inaccuracy. We conducted a six-week self-reporting study on smartphone usage in order to investigate the accuracy of self-reported information, and used logged data as ground truth to compare the subjects' reports against. Subjects never recorded more than 70% and, depending on the requested reporting interval, down to less than 40% of actual app usages. They significantly overestimated how long they used apps. While subjects forgot self-reports when no automatic reminders were sent, a high reporting frequency was perceived as uncomfortable and burdensome. Most significantly, self-reporting even changed the actual app usage of users and hence can lead to deceptive measures if a study relies on no other data sources.

User authentication on publicly exposed terminals with established mechanisms, such as typing the credentials on a virtual keyboard, can be insecure e.g. due to shoulder surfing or due to a hacked terminal. In addition, username and password entry can be time-consuming and thus improvable with relation to usability. As security and comfort are often competing with each other, novel authentication and authorization methods especially for public terminals are desirable. In this paper, we present an approach on a distributed authentication and authorization system, where the user can be easily identified and enabled to use a service with his smartphone. The smartphone (as personal and private device the user is always in control of) can provide a highly secure authentication token that is renewed and exchanged in the background without the user's participation. The claimed improvements were supported by a user survey with an implementation of a digital room management system as an example for a public display. The proposed authentication procedure would increase security and yet enable fast authentication within publicly exposed terminals.

Vision-based approaches for mobile indoor localization do not rely on the infrastructure and are therefore scalable and cheap. The particular requirements to a navigation user interface for a vision-based system, however, have not been investigated so far.

We present GymSkill, a personal trainer for ubiquitous monitoring and assessment of physical activity using standard fitness equipment. The system records and analyzes exercises using the sensors of a personal smartphone attached to the gym equipment. Novel fine-grained activity recognition techniques based on pyramidal Principal Component Breakdown Analysis (PCBA) provide a quantitative analysis of the quality of human movements. In addition to overall quality judgments, GymSkill identifies interesting portions of the recorded sensor data and provides suggestions for improving the individual performance, thereby extending existing work. The system was evaluated in a case study where 6 participants performed a variety of exercises on balance boards. GymSkill successfully assessed the quality of the exercises, in agreement with the professional judgment provided by a physician. User feedback suggests that GymSkill has the potential to serve as an effective tool for motivating and supporting lay people to overcome sedentary, unhealthy lifestyles. GymSkill is available in the Android Market as `VMI Fit'.

Advances in the fields of distributed computing, wireless sensor networks, ubiquitous computing and many more have facilitated the development of a plenitude of Intelligent Environments (IE). The development processes, underlying tools and methods have however not yet been in the focus of researchers. A significant amount of time has to be spent for building a novel ecology of distributed systems to form an Intelligent Environment to conduct novel research in. A sophisticated middleware can shift the focus from building to research. Yet, a middleware is only one of the many requirements for leveraging the development process of Intelligent Environments. In this paper, we present a complete tool chain to simplify research on Intelligent Environments and to ease their creation. This tool chain consists out of middleware, simulation, visualization and prototyping tools. We start by modeling the physical environment using a CAD software and visualization tool including physical properties. The tool chain is complemented by a middleware and a sophisticated simulation environment allowing e.g. to simulate mobile phone interactions triggering, and the deployment to the real-world events. For developers and researchers of Intelligent Environments, creation and maintenance of Intelligent Environments is significantly improved. Development is speeded up as algorithms, interaction can be already evaluated and tested in simulation before the deployment to the real world.

"There's An App For That" -- but how do we actually develop them? While smartphones and tablet PCs are getting more and more popular and their application scenarios are growing, we still develop them using only a standard integrated development environment. Although context-based services and apps do, next to network connectivity, require lots of sensor data, the tools for providing realistic sensor data during development are still immature.