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 Perhaps the best known example of a seamful mobile application was the 2001 chase game (CYSMN). @cite_0 In CYSMN a small number of was tasked to move around through the streets of Sheffield. Meanwhile, a different group of players was introduced to a virtual representation of the same city online. Their position was tracked in real time and displayed to the runners through their PDA devices. Likewise, the position of runners was tracked using GPS and displayed to the online players in their virtual environment. The goal of the runners was then to catch as many of the online players as possible by moving into sufficient proximity of the position they were occupying in the virtual world. The fluctuating GPS coverage made it difficult for runners to catch online players in certain areas of the map and keeping track of GPS coverage became an important strategic advantage, thus adding an extra dimension to the gameplay.
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We present a study of a mobile mixed reality game called Can You See Me Now? in which online players are chased through a virtual model of a city by ‘runners’ (professional performers equipped with GPS and WiFi technologies) who have to run through the actual city streets in order to catch the players. We present an ethnographic study of the game as it toured through two different cities and draws upon video recordings of online players, runners, technical support crew, and also on system logs of text communication. Our study reveals the diverse ways in which online players experienced the uncertainties inherent in GPS and WiFi, including being mostly unaware of them, but sometimes seeing them as problems, or treating the as a designed feature of the game, and even occasionally exploiting them within gameplay. In contrast, the runners and technical crew were fully aware of these uncertainties and continually battled against them through an ongoing and distributed process of orchestration. As a result, we encourage designers to deal with such uncertainties as a fundamental characteristic of location-based experiences rather than treating them as exceptions or bugs that might be ironed out in the future. We argue that designers should explicitly consider four potential states of being of a mobile participant: connected and tracked, connected but not tracked, tracked but not connected, and neither connected nor tracked. We then introduce five strategies that might be used to deal with uncertainty in these different states for different kinds of participant: remove it, hide it, manage it, reveal it, and exploit it. Finally, we present proposals for new orchestration interfaces that reveal the ‘seams’ in the underlying technical infrastructure by visualizing the recent performance of GPS and WiFi and predicting the likely future performance of GPS. Seamful design is a new approach to reveal and exploit inevitable technical limitations in Ubiquitous Computing technology rather than hiding them. In this paper we want to introduce its general ideas and apply them to the design of location-aware games for mobile phones. We introduce our own seamful trading-game called “Tycoon” to explore seams on this platform and show how to incorporate them into the design of mobile games. We want to evaluate how applications for the mobile phone platform which use cell-positioning can exploit seams for better interaction, gameplay and usability. Recent research has shown that surprisingly rich models of human behavior can be learned from GPS (positional) data. However, most research to date has concentrated on modeling single individuals or aggregate statistical properties of groups of people. Given noisy real-world GPS data, we—in contrast—consider the problem of modeling and recognizing activities that involve multiple related individuals playing a variety of roles. Our test domain is the game of capture the flag—an outdoor game that involves many distinct cooperative and competitive joint activities. We model the domain using Markov logic, a statistical relational language, and learn a theory that jointly denoises the data and infers occurrences of high-level activities, such as capturing a player. Our model combines constraints imposed by the geometry of the game area, the motion model of the players, and by the rules and dynamics of the game in a probabilistically and logically sound fashion. We show that while it may be impossible to directly detect a multi-agent activity due to sensor noise or malfunction, the occurrence of the activity can still be inferred by considering both its impact on the future behaviors of the people involved as well as the events that could have preceded it. We compare our unified approach with three alternatives (both probabilistic and nonprobabilistic) where either the denoising of the GPS data and the detection of the high-level activities are strictly separated, or the states of the players are not considered, or both. We show that the unified approach with the time window spanning the entire game, although more computationally costly, is significantly more accurate. Recent improvements in image-based localization have produced powerful methods that scale up to the massive 3D models emerging from modern Structure-from-Motion techniques. However, these approaches are too resource intensive to run in real-time, let alone to be implemented on mobile devices. In this paper, we propose to combine the scalability of such a global localization system running on a server with the speed and precision of a local pose tracker on a mobile device. Our approach is both scalable and drift-free by design and eliminates the need for loop closure. We propose two strategies to combine the information provided by local tracking and global localization. We evaluate our system on a large-scale dataset of the historic inner city of Aachen where it achieves interactive framerates at a localization error of less than 50cm while using less than 5MB of memory on the mobile device.