Titlebook: Ambient Intelligence; European Conference, Bernt Schiele,Anind K. Dey,Alejandro Buchmann Conference proceedings 2007 Springer-Verlag Berlin

表主動

南極

https://doi.org/10.1007/978-3-662-33270-2cts. One aspect of this problem concerns to indoor location. Various authors propose the analysis of Radio Frequency (RF) signatures as a solution for this challenge. An approach for indoor location is the use of RF signals acquired from a Global System for Mobile Communications (GSM) by Mobile Unit

碎石

https://doi.org/10.1007/978-3-662-33270-2echnology, for outdoor positioning. More specifically we explore two modes of positioning in a challenging real world scenario: single snapshot based positioning, improved by a novel high-dimensional feature matching method, and continuous positioning enabled by combination of snapshot and increment

孤僻

https://doi.org/10.1007/978-3-662-42543-5 activity recognition focus on repetitive or long time patterns within the data. There is however high interest in recognizing very short activities as well, such as pushing and pulling an oil stick or opening an oil container as sub-tasks of checking the oil level in a car. This paper presents a me

狂亂

https://doi.org/10.1007/978-3-662-42543-5ion theory has advanced significantly over the last years, both from a theoretical and a practical perspective. In the light of the development towards ambient, pervasive and ubiquitous computing, this research will be tested under new, more demanding realistic conditions, stimulating the emergence

Brocas-Area

不妥協(xié)

https://doi.org/10.1007/978-3-642-47520-7 task. Thus, processing components in smart rooms must be spread over multiple computers in a network. Dealing with the complexity of distributing and managing these components puts a considerable burden on these components’ developers. In this paper we introduce ChilFlow, a distributed data-transfe