Matthias Baldauf

Bio: Matthias Baldauf is an academic researcher from University of St. Gallen. The author has contributed to research in topics: Computer science & Mobile device. The author has an hindex of 14, co-authored 60 publications receiving 2558 citations. Previous affiliations of Matthias Baldauf include Vienna University of Technology.

A survey on context-aware systems

Abstract: Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behaviour accordingly. Especially in combination with mobile devices, these mechanisms are of high value and are used to increase usability tremendously. In this paper, we present common architecture principles of context-aware systems and derive a layered conceptual design framework to explain the different elements common to most context-aware architectures. Based on these design principles, we introduce various existing context-aware systems focusing on context-aware middleware and frameworks, which ease the development of context-aware applications. We discuss various approaches and analyse important aspects in context-aware computing on the basis of the presented systems.

Markerless visual fingertip detection for natural mobile device interaction

Abstract: The vision-based detection of hand gestures is one technological enabler for Natural User Interfaces which try to provide a natural and intuitive interaction with computers. In particular, mobile devices might benefit from such a less device-centric but more natural input possibility. In this paper, we introduce our ongoing work on the visual markerless detection of fingertips on mobile devices. Further, we shed light on the potential of mobile hand gesture detection and present several promising use cases and respective demo applications based on the presented engine.

On the move, wirelessly connected to the world

Abstract: How to experience real-world landmarks through a wave, gaze, location coordinates, or touch, prompting delivery of useful digital information.

KIBITZER: a wearable system for eye-gaze-based mobile urban exploration

Abstract: Due to the vast amount of available georeferenced information novel techniques to more intuitively and efficiently interact with such content are increasingly required. In this paper, we introduce KIBITZER, a lightweight wearable system that enables the browsing of urban surroundings for annotated digital information. KIBITZER exploits its user's eye-gaze as natural indicator of attention to identify objects-of-interest and offers speech- and non-speech auditory feedback. Thus, it provides the user with a 6th sense for digital georeferenced information. We present a description of our system's architecture and the interaction technique and outline experiences from first functional trials.

When Smart Devices Interact With Pervasive Screens: A Survey

Abstract: The meeting of pervasive screens and smart devices has witnessed the birth of screen-smart device interaction (SSI), a key enabler to many novel interactive use cases. Most current surveys focus on direct human-screen interaction, and to the best of our knowledge, none have studied state-of-the-art SSI. This survey identifies three core elements of SSI and delivers a timely discussion on SSI oriented around the screen, the smart device, and the interaction modality. Two evaluation metrics (i.e., interaction latency and accuracy) have been adopted and refined to match the evaluation criterion of SSI. The bottlenecks that hinder the further advancement of the current SSI in connection with this metrics are studied. Last, future research challenges and opportunities are highlighted in the hope of inspiring continuous research efforts to realize the next generation of SSI.

Internet of things: Vision, applications and research challenges

Abstract: The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

Context Aware Computing for The Internet of Things: A Survey

Abstract: As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.

Intuitive computing methods and systems

Abstract: A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Context-aware systems

Abstract: Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification framework of context-aware systems, and explore each feature of classification framework. This paper is based on a literature review of context-aware systems from 2000 to 2007 using a keyword index and article title search. The classification framework is developed based on the architecture of context-aware systems, which consists of the following five layers: concept and research layer, network layer, middleware layer, application layer and user infrastructure layer. The articles are categorized based on the classification framework. This paper allows researchers to extract several lessons learned that are important for the implementation of context-aware systems.

Challenges, issues and trends in fall detection systems

Abstract: Since falls are a major public health problem among older people, the number of systems aimed at detecting them has increased dramatically over recent years. This work presents an extensive literature review of fall detection systems, including comparisons among various kinds of studies. It aims to serve as a reference for both clinicians and biomedical engineers planning or conducting field investigations. Challenges, issues and trends in fall detection have been identified after the reviewing work. The number of studies using context-aware techniques is still increasing but there is a new trend towards the integration of fall detection into smartphones as well as the use of machine learning methods in the detection algorithm. We have also identified challenges regarding performance under real-life conditions, usability, and user acceptance as well as issues related to power consumption, real-time operations, sensing limitations, privacy and record of real-life falls.