An Engine Enabling Location-based Mobile Augmented Reality Applications

Contemporary smart mobile devices are already capable of running advanced mobile applications with demanding resource requirements. However, utilizing the technical capabilities of such devices constitutes a challenging task (e.g., when querying their sensors at run time). This paper deals with the design and implementation of an advanced mobile application, which enables location-based mobile augmented reality on different mobile operating systems (i.e., iOS and Android). In particular, this kind of application is characterized by high resource demands. For example, at run time various calculations become neccessary in order to correctly position and draw virtual objects on the screen of the smart mobile device. Hence, we focus on the lessons learned when implementing a robust and efficient, location-based mobile augmented reality engine as well as efficient mobile business applications based on it

Advanced Algorithms for Location-Based Smart Mobile Augmented Reality Applications

During the last years, the computational capabilities of smart mobile devices have been continuously improved by hardware vendors, raising new opportunities for mobile application engineers. Mobile augmented reality is one scenario demonstrating that smart mobile applications are becoming increasingly mature. In the AREA (Augmented Reality Engine Application) project, we developed a kernel that enables such location-based mobile augmented reality applications. On top of the kernel, mobile application developers can easily realize their individual applications. The kernel, in turn, focuses on robustness and high performance. In addition, it provides a flexible architecture that fosters the development of individual location-based mobile augmented reality applications. In the first stage of the project, the LocationView concept was developed as the core for realizing the kernel algorithms. This LocationView concept has proven its usefulness in the context of various applications, running on iOS, Android, or Windows Phone. Due to the further evolution of computational capabilities on one hand and emerging demands of location-based mobile applications on the other, we developed a new kernel concept. In particular, the new kernel allows for handling points of interests (POI) clusters or enables the use of tracks. These changes required new concepts presented in this paper. To demonstrate the applicability of our kernel, we apply it in the context of various mobile applications. As a result, mobile augmented reality applications could be run on present mobile operating systems and be effectively realized by engineers utilizing our approach. We regard such applications as a good example for using mobile computational capabilities efficiently in order to support mobile users in everyday life more properly

Enabling Tracks in Location-Based Smart Mobile Augmented Reality Applications

To assist users through contemporary mobile technology is demanded in a multitude of scenarios. Interestingly, more and more users crave for mobile assistance in their leisure time. Consequently, the number of mobile applications that support leisure activities increases significantly. Mobile augmented reality applications constitute an example for user assistance that is welcome in these scenarios. In the AREA (Augmented Reality Engine Application) project, we developed a kernel that enables sophisticated location-based mobile augmented reality applications. On top of this kernel, various projects were realized. In many of these projects, a feature to enable tracks was demanded. Tracks, for example, may assist users in the context of mountaineering. The development of an AREA algorithm that enables track handling requires new concepts that are presented in this paper. To demonstrate the performance of the developed algorithm, also results of an experiment are presented. As a lesson learned, mobile augmented reality applications that want to make use of the new algorithm can be efficiently run on present mobile operating systems and be effectively realized by engineers using the AREA framework. Altogether, the new track feature is another valuable step for AREA towards a comprehensive location-based mobile augmented reality framework

The AREA Algorithm Framework Enabling Location-based Mobile Augmented Reality Applications

The dramatically increased computational capabilities of mobile devices have leveraged the opportunities for mobile application engineers. Respective scenarios, in which these opportunities can be exploited, emerge almost per day. In this context, mobile augmented reality applications play an important role in many business scenarios. In the automotive domain, they are mainly used to provide car customers with new experiences. For example, customers can use their own mobile device to experience the interior of a car by moving the mobile device around. The device’s camera then detects interior parts and shows additional information to the customer within the camera view. Although the computational capabilities have been increased, the realization of such mobile augmented reality applications is still a complex endeavor. In particular, the different mobile operating systems and their peculiarities must be carefully considered. In the AREA (Augmented Reality Engine Application) project, a powerful kernel was realized that enables location-based mobile augmented reality applications. This kernel, in turn, mainly focuses on robustness and performance. In addition, it provides a flexible architecture that fosters the development of individual location-based mobile augmented reality applications. As many aspects have to be considered to implement individual applications based on top of AREA, this paper provides the first comprehensive overview of the entire algorithm framework. Moreover, a recently realized algorithm and new features will be presented. To demonstrate the applicability of the kernel, its features are applied in the context of various mobile applications. As the major lesson learned, powerful mobile augmented reality applications can be efficiently run on present mobile operating systems and be effectively realized by engineers using AREA. We consider such mobile frameworks as being crucial to provide more generic concepts that are able to abstract from the peculiarities of the underlying mobile operating system and to support mobile application developers more properly

The AREA Framework for Location-Based Smart Mobile Augmented Reality Applications

During the last years, the computational capabilities of smart mobile devices have been continuously improved by hardware vendors, raising new opportunities for mobile application engineers. Mobile augmented reality can be considered as one demanding scenario demonstrating that smart mobile applications are becoming more and more mature. In the AREA (Augmented Reality Engine Application) project, we developed a powerful kernel that enables location-based, mobile augmented reality applications. On top of this kernel, mobile application developers can realize sophisticated individual applications. The AREA kernel, in turn, allows for both robustness and high performance. In addition, it provides a flexible architecture that fosters the development of individual location-based mobile augmented reality applications. As a particular feature, the kernel allows for the handling of points of interests (POI) clusters. Altogether, advanced concepts are required to realize a location-based mobile augmented reality kernel that are presented in this paper. Furthermore, results of an experiment are presented in which the AREA kernel was compared to other location-based mobile augmented reality applications. To demonstrate the applicability of the kernel, we apply it in the context of various mobile applications. As a lesson learned, sophisticated mobile augmented reality applications can be efficiently run on present mobile operating systems and be effectively realized by engineers using the AREA framework. We consider mobile augmented reality as a killer application for mobile computational capabilities as well as the proper support of mobile users in everyday life

Flexible development of location-based mobile augmented reality applications with AREA

Mobile applications have garnered a lot of attention in the last years. The computational capabilities of mobile devices are the mainstay to develop completely new application types. The provision of augmented reality experiences on mobile devices paves one alley in this feld. For example, in the automotive domain, augmented reality applications are used to experience, inter alia, the interior of a car by moving a mobile device around. The device’s camera then detects interior parts and shows additional information to the customer within the camera view. Another application type that is increasingly utilized is related to the combination of serious games with mobile augmented reality functions. Although the latter combination is promising for many scenarios, technically, it is a complex endeavor. In the AREA (Augmented Reality Engine Application) project, a kernel was implemented that enables location-based mobile augmented reality applications. Importantly, this kernel provides a fexible architecture that fosters the development of individual location-based mobile augmented reality applications. The work at hand shows the fexibility of AREA based on a developed serious game. Furthermore, the algorithm framework and major features of it are presented. As the conclusion of this paper, it is shown that mobile augmented reality applications require high development eforts. Therefore, fexible frameworks like AREA are crucial to develop respective applications in a reasonable time

The Conception and Realization of a Mobile Windows Phone Location-based Augmented Reality Application

It is considered very evolved having Augmented Reality (AR) to be used in an application. This raises the need to have good AR frameworks and AR engines to facilitate the development. Most of the available engines and frameworks are either hard to understand, due to poor documentation or do not provide a sufficient insight, or are proprietary, which force the developer to pay for it. This thesis introduces a location-based AR engine from scratch, which is in its dynamic structure easy to understand and to integrate it in any custom application. The usage of user controls and the possibility to extend the available classes provide a good basis to individualize the engine. This engine is based on the original AREA for iOS[1] and uses advanced calculations to enhance performance. This engine is made for Windows Phone 8.1 using C# with XAML(Extensible Application Markup Language) to create the UI

Implementation and evaluation of a mobile iOS application for auditory stimulation of chronic tinnitus patients

Mobile devices take in more and more space in our lifes and as tinnitus becomes a much more widespread disease, science started to develop treatment strategies. One of those treatment strategies is ’auditory training’ and with this strategy in mind a game concept with spatial audio was developed to provide an easily available ambulant help for chronic tinnitus patients. In the course of this thesis a seperate game only using spatial audio is developed on mobile iOS devices and in a study it is evaluated how good spatial audio can work on different mobile platforms. At the end of thesis the work is summarized and improvements in the game are displayed for further use in the above mentioned game scenario

Design and Implementation of an Android Sleep Monitoring Framework

Smartphones were originally mainly used for making phone calls and playing games, but as they become more powerful and are equipped with a wide variety of sensors new use cases become interesting. One of these use cases is sleep monitoring, which is interesting for many different research areas. The goal of this bachelor thesis is to develop a sleep monitoring framework for the Android platform which can be used easily by third party applications. The framework takes care of detecting sleep related events like snoring and movement as well as monitoring the ambient light during the night. Additionally, a demo application is developed to demonstrate the functionality of the framework and to highlight some best practices regarding Android background services as they are essential for monitoring sleep