The potential use of augmented reality in gamification

The use of augmented reality (AR) and gamification in various fields is currently gaining popularity for its capability in engaging users.Gamification is a term that defines the use of game-based elements, such as game mechanics, aesthetics, dynamics, and game thinking in the non-game context environment.Meanwhile, AR is a technology that has an ability to overlap computer graphics onto the real environment.However, as a newly emerging concept, gamification seems to have some arguments related to its elements, concepts, and effectiveness in a similar intervention. Therefore, this paper discusses gamification. Although dozens of studies have implemented AR games, there is still an obvious lack in discussing and relating it to a gamified platform. Nevertheless, previous adaptation of games in AR seems that there are also potentials to utilise gamification and AR concepts and elements, as well as AR and AR games in brief.This paper also justifies several previous empirical studies in AR and gamification to look into its elements, research design, and the potentials of AR and gamification combinatio

GNSS Shadow Matching: Improving Urban Positioning Accuracy Using a 3D City Model with Optimized Visibility Prediction Scoring

The poor performance of global navigation satellite systems (GNSS) user equipment in urban canyons is a well-known problem, especially in the cross-street direction. A new approach, shadow matching, has recently be proposed to improve the cross-street accuracy using GNSS, assisted by knowledge derived from 3D models of the buildings close to the user of navigation devices. In this work, four contributions have been made. Firstly, a new scoring scheme, a key element of the algorithm to weight candidate user locations, is proposed. The new scheme takes account of the effects of satellite signal diffraction and reflection by weighting the scores based on diffraction modelling and signal-to-noise ratio (SNR). Furthermore, an algorithm similar to k-nearest neighbours (k-NN) is developed to interpolate the position solution over an extensive grid. The process of generating this grid of building boundaries is also optimized. Finally, instead of just testing at two locations as in the earlier work, realworld GNSS data has been collected at 22 different locations in this work, providing a more comprehensive and statistical performance analysis of the new shadowmatching algorithm. In the experimental verification, the new scoring scheme improves the cross street accuracy with an average bias of 1.61 m, with a 9.4% reduction compared to the original SS22 scoring scheme. Similarly, the cross street RMS is 2.86 m, a reduction of 15.3%. Using the new scoring scheme, the success rate for determining the correct side of a street is 89.3%, 3.6% better than using the previous scoring scheme; the success rate of distinguishing the footpath from a traffic lane is 63.6% of the time, 6.8% better than using the previous scoring scheme

Kinematic GNSS Shadow Matching Using Particle Filters

Student Paper Award Winner. The poor performance of GNSS user equipment in urban canyons is a well-known problem and is particularly inaccurate in the cross-street direction. However, the accuracy in this direction greatly affects many applications, including vehicle lane identification and high-accuracy pedestrian navigation. Shadow matching was proposed to help solve this problem by using information derived from 3D models of buildings. Though users of GNSS positioning typically move, previous research has focused on static shadow-matching positioning. In this paper, for the first time, kinematic shadow-matching positioning is tackled. Kalman filter based shadow matching is proposed and also, in order to overcome some of its predicted limitations, a particle filter is proposed to better solve the problem

The usability attributes and evaluation measurements of mobile media AR (augmented reality)

This research aims to develop a tool for creating user-based design interfaces in mobile augmented reality (MAR) education. To develop a design interface evaluation tool, previous literature was examined for key design elements in the educational usage of MAR. The evaluation criteria identified were presence, affordance, and usability. The research used a focus group interview with 7 AR experts to develop a basic usability evaluation checklist, which was submitted to factor analysis for reliability by 122 experts in practice and academia. Based on this checklist, a MAR usability design interface test was conducted with seven fourth-grade elementary students. Then, it conducted follow-up structured interviews and questionnaires. This resulted in 29 questions being developed for the MAR interface design checklist.ope

Sensor fusion of camera, GPS and IMU using fuzzy adaptive multiple motion models

A tracking system that will be used for augmented reality applications has two main requirements: accuracy and frame rate. The first requirement is related to the performance of the pose estimation algorithm and how accurately the tracking system can find the position and orientation of the user in the environment. Accuracy problems of current tracking devices, considering that they are low-cost devices, cause static errors during this motion estimation process. The second requirement is related to dynamic errors (the end-to-end system delay, occurring because of the delay in estimating the motion of the user and displaying images based on this estimate). This paper investigates combining the vision-based estimates with measurements from other sensors, GPS and IMU, in order to improve the tracking accuracy in outdoor environments. The idea of using Fuzzy Adaptive Multiple Models was investigated using a novel fuzzy rule-based approach to decide on the model that results in improved accuracy and faster convergence for the fusion filter. Results show that the developed tracking system is more accurate than a conventional GPS–IMU fusion approach due to additional estimates from a camera and fuzzy motion models. The paper also presents an application in cultural heritage context running at modest frame rates due to the design of the fusion algorithm

The intention of consumers to use augmented reality apps in gastronomy – case of Málaga

Versión aceptadaThe intention of consumers to use mobile applications with augmented reality is analyzed in order to assess which variables have the greatest influence on their use by consumers. The UTAUT-2 model has been used, analyzing: performance expectancy, effort expectancy, social influence, hedonic motivation, price value, facilitating conditions, habit and behavioural intention. The results show that predictors of a more social nature, such as aspects associated with perceived enjoyment: habits and social influence are not supported. Also, the hypothesis on the value of price could not be supported; since most augmented reality applications are free, although it is a variable that exerts a positive influence on the intention to use because of the perceived benefits. The demographic profiles of consumers can also become important predictors when using augmented reality apps, being the millennial generation and generation Z the most likely to use mobile devices with augmented reality

Urban Positioning on a Smartphone: Real-time Shadow Matching Using GNSS and 3D City Models

The performance of global navigation satellite system (GNSS) user equipment in urban canyons is particularly poor in the cross-street direction. This is because more signals are blocked by buildings in the cross-street direction than along the street [1]. To address this problem, shadow matching has been proposed to improve cross-street positioning from street-level to lane-level (meters-level) accuracy using 3D city models. This is a new positioning method that uses the city model to predict which satellites are visible from different locations and then compares this with the measured satellite visibility to determine position [2]. In previous work, we have demonstrated shadow matching using GPS and GLONASS data recorded using a geodetic GNSS receiver in Central London, achieving a cross-street position accuracy within 5m 89% of the time [3]. This paper describes the first real-time implementation of shadow matching on a smartphone capable of receiving both GPS and GLONASS. The typical processing time for the system to provide a solution was between 1 and 2 seconds. On average, the cross-street position accuracy from shadow matching was a factor of four better than the phone’s conventional GNSS position solution. A number of groups have also used 3D city models to predict and, in some cases, correct non-line-of-sight reception [4-6]. However, to our knowledge, this paper reports the first ever demonstration of any 3D-model-aided GNSS positioning technique in real time, as opposed to using recorded GNSS data. When it comes to real-time positioning on a smartphone, various obstacles exist including lower-grade GNSS receivers, limited availability of computational power, memory, and battery power. To tackle these problems, in this work, an efficient smartphone-based shadow-matching positioning system was designed. The system was then implemented in an app (i.e. application or software) on the Android operating system, the most common operating system for smartphones. The app has been developed in Java using Eclipse, a software development environment (SDE). It was built on Standard Android platform 4.0.3, using the Android Application programming interface (API) to retrieve information from the GNSS chip. The new positioning system does not require any additional hardware or real-time rendering of 3D scenes. Instead, a grid of building boundaries is computed in advance and stored within the phone. This grid could also be downloaded from the network on demand. Shadow matching is therefore both power-efficient and cost-effective. Experimental testing was performed in Central London using a Samsung Galaxy S3 smartphone. This receives both GPS and GLONASS satellites and has an assisted GNSS (AGNSS) capability. A 3D city model of the Aldgate area of central London, supplied by ZMapping Ltd, was used. Four experimental locations with different building topologies were selected on Fenchurch Street, a dense urban area. Using the Android app developed in this work, real-time shadow-matching positioning was performed over 6 minutes at each site with a new position solution computed every 5 seconds using both GPS and GLONASS observations were used for real-time positioning. The measurement data was also recorded at 1-second intervals for later analysis. Various criteria are applied to access the new system and compare it with the conventional GNSS positioning results. The experimental results show that the proposed system outperforms the conventional GNSS positioning solution, reducing the mean absolute deviation of the cross-street positioning error from 14.81 m to 3.33 m, with a 77.5 percentage reduction. The feasibility of deploying the new system on a larger scale is also discussed from three perspectives: the availability of 3D city models and satellite information, data storage and transfer requirements, and demand from applications. This meters-level across-street accuracy in urban areas benefits a variety of applications from Intelligent Transportation Systems (ITS) and land navigation systems for automated lane identification to step-by-step guidance for the visually impaired and for tourists, location-based advertisement (LBA) for targeting suitable consumers and many other location-based services (LBS). The system is also expandable to work with Galileo and Beidou (Compass) in the future, with potentially improved performance. In the future, the shadow-matching system can be implemented on a smartphone, a PND, or other consumer-grade navigation device, as part of an intelligent positioning system [7], along with height-aided conventional GNSS positioning, and potentially other technologies, such as Wi-Fi and inertial sensors to give the best overall positioning performance. / References [1] Wang, L., Groves, P. D. & Ziebart, M. Multi-constellation GNSS Performance Evaluation for Urban Canyons Using Large Virtual Reality City Models. Journal of Navigation, July 2012. [2] Groves, P. D. 2011. Shadow Matching: A New GNSS Positioning Technique for Urban Canyons The Journal of Navigation, 64, pp417-430. [3] Wang, L., Groves, P. D. & Ziebart, M. K. GNSS Shadow Matching: Improving Urban Positioning Accuracy Using a 3D City Model with Optimized Visibility Prediction Scoring. ION GNSS 2012. [4] Obst, M., Bauer, S. and Wanielik, G. Urban Multipath Detection and mitigation with Dynamic 3D Maps for Reliable Land Vehicle Localization. IEEE/ION PLANS 2012. [5] Peyraud, S., Bétaille, D., Renault, S., Ortiz, M., Mougel, F., Meizel, D. and Peyret, F. (2013) About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm. Sensors, Vol. 13, 2013, 829?847. [6] Bourdeau, A., M. Sahmoudi, and J.-Y. Tourneret, “Tight Integration of GNSS and a 3D City Model for Robust Positioning in Urban Canyons,” Proc. ION GNSS 2012. [7] Groves, P. D., Jiang, Z., Wang, L. & Ziebart, M. Intelligent Urban Positioning using Multi-Constellation GNSS with 3D Mapping and NLOS Signal Detection. ION GNSS 2012

Mobile gaming: Industry challenges and policy implications

Mobile games are a prime example of a successful mobile application and demonstrate the increasing range of platforms for the media and entertainment industries. Against this convergent background, this paper introduces the basic features of the mobile gaming market and its industrial ecosystem together with its main actors and activities. The focus of the paper lies in the challenges ahead for the evolution of mobile applications into a potentially dominant game platform and the possible disruptions along this road. The deep personal relationships between users and their mobile devices are considered to further explore the link between mobile games, players’ strategies and pending techno-economic developments. The paper concludes with a brief discussion of some policy options to assist with the development of this domain

Disaster Tales as Communication Tool for Increasing Risk Resilience

Agencies in charge of flood management use disaster reports (DRs) as the preferred source of information on past flooding events. A systematic survey of DRs prepared by Italian agencies suggests that DRs could be widely enhanced in view of targeting more effective communication to citizens, reinforcing the communication pillar in civil protection planning and management, and improving the resilience of the population to extreme events. Without loss of the rigor and details required for all the usual technical uses of DRs, we suggest recompiling them in the form of “disaster tales” (DTs), as tools that offer wider knowledge of the events to improve people’s preparedness and self-protection behavior. Recent major flooding events have demonstrated the communication potential that videos and pictures taken by citizens have for risk perception and disaster preparedness. By watching and listening to what has happened the communication recipient can better understand the feelings of the people experiencing an emergency. The structure of the improved reports, we suggest, will finally integrate data, graphs, and maps with interactive tools and be able to present handier multimedia views of the events. Application to three case studies of flooding in Italy illustrates how to concretely implement the suggested disaster reports to create more readily accessible disaster tales