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The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, inter-operability and accessibility. Although not new, virtualization and automation are cor features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-defining neither the technology nor the usage scenarios from scratch. Our suggestion is based on certain solutions that have already been implemented and tested for specific cases.
Mobile devices, in the form of smartphones, are endowed with rich capabilities in terms of multimedia, sensors and connectivity. The wide adoption of these devices allows using them across different settings and situations. One area in which mobile devices become more and more prominent is within the field of mobile learning. Here, mobile devices provide rich possibilities for the contextualization of the learner, by using the set of sensors available in the device. On the one hand, the usage of mobile devices enables participation in learning activities independent of time and space. Nevertheless, developing mobile learning applications for the heterogeneity of mobile devices available in the market becomes a challenge. Not only this is a problem related to form factor aspects, but also the large number of different operating systems, platforms and app infrastructures (app stores) are aspects to be considered. In this paper we present our initial efforts with regard to the development of cross-platform mobile applications to support the contextualization of learning content.
Pedestrian movement analysis at airports - videobased analysis across multiple camera systems
(2013)
In this paper, we describe a method to model human clothes for a later recognition by the use of RGB- and SWIR-cameras. A basic model is estimated during people detection and tracking. This model will be refined if the recognition is triggered. For the refining, several saliency maps are used to extract individual features. These individual features are located separately for any human body parts. The body parts are estimated by the use of a silhouette extraction combined with a skeleton estimation. In this way, the model describes the human clothes in a compact manner which allows the use of a simple and fast comparison method for people recognition. Such models can be used in security and service applications.
One of the most stressing challenges in our culture is the demographic change. On the one hand, people become older and older, at the same time less young people are available in order to support the elderly. Currently, this fact already provides a number of social impacts that need to be solved in the near future. This paper concentrates on the integration of mobile devices in scenarios that allow elderly people to age successfully. Here, the term "aging successfully" refers to broad range of aspects from health to social life of elderly people. A special focus of this paper lies in the question whether services deployed to a mobile device provide advantages in the area of aging successfully. In order to answer this question, both technical challenges are explained and solved by example architectures, and scenarios that benefit from services deployed to mobile devices are explained.
MeHRWert Ausgabe 3 Juni 2013
(2013)