The application of mobile computing is currently altering patterns of our behavior to a greater degree than perhaps any other invention. In combination with the introduction of power efficient wireless communication technologies, such as Bluetooth Low Energy (BLE), designers are today increasingly empowered to shape the way we interact with our physical surroundings and thus build entirely new experiences. However, our evaluations of BLE and its abilities to facilitate mobile location-based experiences in public environments revealed a number of potential problems. Most notably, the position and orientation of the user in combination with various environmental factors, such as crowds of people traversing the space, were found to cause major fluctuations of the received BLE signal strength. These issues are rendering a seamless functioning of any location-based application practically impossible. Instead of achieving seamlessness by eliminating these technical issues, we thus choose to advocate the use of a seamful approach, i.e. to reveal and exploit these problems and turn them into a part of the actual experience. In order to demonstrate the viability of this approach, we designed, implemented and evaluated the Ghost Detector - an educational location-based museum game for children. By presenting a qualitative evaluation of this game and by motivating our design decisions, this paper provides insight into some of the challenges and possible solutions connected to the process of developing location-based BLE-enabled experiences for public cultural spaces.
black Similarly, studies have shown that the introduction of computing technology into museum environments can have a positive impact on the user experience, particularly so when it comes to engaging visitors in explanations of complex artifacts. @cite_30
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Designing technologies that support the explanation of museum exhibits is a challenging domain. In this paper we develop an innovative approach - providing a robot guide with resources to engage visitors in an interaction about an art exhibit. We draw upon ethnographical fieldwork in an art museum, focusing on how tour guides interrelate talk and visual conduct, specifically how they ask questions of different kinds to engage and involve visitors in lengthy explanations of an exhibit. From this analysis we have developed a robot guide that can coordinate its utterances and body movement to monitor the responses of visitors to these. Detailed analysis of the interaction between the robot and visitors in an art museum suggests that such simple devices derived from the study of human interaction might be useful in engaging visitors in explanations of complex artifacts. In recent years there has been a dramatic rise in the number of participatory media technologies which museums have employed to engage people in new ways under the rubric of Web 2.0. Blogs, wikis, podcasts, vodcasts, photo and video sharing, virtual environments, tagging, annotation and other authoring tools offer people new opportunities to engage with museum content processes through co-creation and interactive cultural experiences. Arguably, these platforms and tools are creating new relationships between institutions and the public. In many cases, visitors come to a museum in small groups. In such cases, the visitors’ social context has an impact on their museum visit experience. Knowing the social context may allow a system to provide socially aware services to the visitors. Evidence of the social context can be gained from observing monitoring the visitors’ social behavior. However, automatic identification of a social context requires, on the one hand, identifying typical social behavior patterns and, on the other, using relevant sensors that measure various signals and reason about them to detect the visitors’ social behavior. We present such typical social behavior patterns of visitor pairs, identified by observations, and then the instrumentation, detection process, reasoning, and analysis of measured signals that enable us to detect the visitors’ social behavior. Simple sensors’ data, such as proximity to other visitors, proximity to museum points of interest, and visitor orientation are used to detect social synchronization, attention to the social companion, and interest in museum exhibits. The presented approach may allow future research to offer adaptive services to museum visitors based on their social context to support their group visit experience better. This paper reports on a field trial with interactive humanoid robots at a science museum where visitors are supposed to study and develop an interest in science. In the trial, each visitor wore an RFID tag while looking around the museum's exhibits. Information obtained from the RFID tags was used to direct the robots' interaction with the visitors. The robots autonomously interacted with visitors via gestures and utterances resembling the free play of children [1]. In addition, they performed exhibit-guiding by moving around several exhibits and explaining the exhibits based on sensor information. The robots were highly evaluated by visitors during the two-month trial. Moreover, we conducted an experiment in the field trial to compare the detailed effects of exhibit-guiding and free-play interaction under three operating conditions. This revealed that the combination of the free-play interaction and exhibit-guiding positively affected visitors' experiences at the science museum.