Download PDF by Emile Aarts, Frits Grotenhuis (auth.), Manfred Tscheligi,: Ambient Intelligence: European Conference, AmI 2009,

By Emile Aarts, Frits Grotenhuis (auth.), Manfred Tscheligi, Boris de Ruyter, Panos Markopoulus, Reiner Wichert, Thomas Mirlacher, Alexander Meschterjakov, Wolfgang Reitberger (eds.)

ISBN-10: 3642054072

ISBN-13: 9783642054075

ISBN-10: 3642054080

ISBN-13: 9783642054082

This ebook constitutes the refereed lawsuits of the 3rd eu convention on Ambient Intelligence, AmI 2009, held in Salzburg, Austria, in November 2009.

The 21 revised complete papers and 10 brief papers offered have been conscientiously reviewed and chosen from quite a few submissions for inclusion within the booklet. The papers are prepared in topical sections on sensing, reasoning and sensing, ambient expertise, ambient assisted dwelling, functions and reviews, tools and instruments and reasoning and adaption.

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They commonly provide data for human experts to evaluate, but they can also be used automatically [7]. 5 % was reported. Our accuracies were comparable despite more noise and fewer tags (and probably also lower sampling frequency – this is not reported in the related paper). 6 Conclusion We have investigated the feasibility of using the coordinates of radio tags worn on the body for fall detection, activity recognition and the detection of health problems. The performance of fall detection with person-independent accuracy of around 94 % seems to be comparable to the competitive approaches.

N=24 participants were recruited from passers-by, 12 for each condition. 22 participants were interviewed. 9 years. 10 participants were male and 12 female; there were 11 pupils, 6 students and 5 other professions. When asked to participate in the camera condition, 5 passers-by rejected because they had no camera on their mobile phone. In the Bluetooth condition, 8 rejected because Bluetooth was not supported, 4 had security concerns and in 3 cases the Bluetooth did not work. Except for 3 participants where Bluetooth failed, all participants could understand the operating instructions on the sign and use the system.

7 seconds [6], our problem domain is quite different as our sensors are attached to the utensils themselves and we are well aware of the relatively short time window within which some actions might be best characterized. However, we still needed to determine the window size with which the best result could be achieved. e. e. e. e. e. 512 samples). A 50% overlap between two consecutive windows was used. For each triple X, Y, Z, we also computed the pitch and roll of the Wii Remotes and made these available to our classifiers.

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Ambient Intelligence: European Conference, AmI 2009, Salzburg, Austria, November 18-21, 2009. Proceedings by Emile Aarts, Frits Grotenhuis (auth.), Manfred Tscheligi, Boris de Ruyter, Panos Markopoulus, Reiner Wichert, Thomas Mirlacher, Alexander Meschterjakov, Wolfgang Reitberger (eds.)


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