By Enrico Rukzio, Gregor Broll, Karin Leichtenstern, Albrecht Schmidt (auth.), Bernt Schiele, Anind K. Dey, Hans Gellersen, Boris de Ruyter, Manfred Tscheligi, Reiner Wichert, Emile Aarts, Alejandro Buchmann (eds.)
This e-book constitutes the refereed lawsuits of the 1st eu convention on Ambient Intelligence, AmI 2007, held in Darmstadt, Germany, in November 2007.
The 17 revised complete papers provided including 5 learn stories have been conscientiously reviewed and chosen from forty eight submissions. The papers are equipped in topical sections on mobility and sensing, purposes of AmI, job and placement sensing, AmI and synthetic intelligence, AmI middleware and infrastructure, and interplay with the surroundings.
The booklet is rounded off through a bit on case reviews and classes discovered, featuring a excessive point number of present learn experiences and papers that mirror an important actions of present ambient intelligence research.
Read Online or Download Ambient Intelligence: European Conference, AmI 2007, Darmstadt, Germany, November 7-10, 2007. Proceedings PDF
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Additional resources for Ambient Intelligence: European Conference, AmI 2007, Darmstadt, Germany, November 7-10, 2007. Proceedings
Larson presented a portable wireless sensor to detect object usage in existing homes that (1) is easy to use and easy to install, (2) extends battery life for longitudinal deployments by combining two sensing modalities, and (3) minimizes false positives due to adjacent movement of objects and environmental noise. The sensor parameters suggested err on the side of sensitivity to object usage to minimize false negatives because offline filtering could further reduce false positives. However, the sensor parameters can be modified allowing researchers to trade real vs.
1. 1 Hardware Design The object usage sensor nodes developed in this work are built upon an existing wireless sensing infrastructure . This sensing platform uses a featherweight MAC protocol in combination with a star network topology to save energy, simplify usage, and permit simultaneous reception from high and low sampling rate sensors. More details can be found in . 6). Moreover, the hardware and software principles on which the object usage sensors are based and presented in this work could also be used to improve sensor performance and battery life for sensor nodes using state-of-the-art mesh networking protocols.
These same sensor characteristics will also be desirable once the sensor technology migrates from use in research to use in commercial ubiquitous computing applications. At first glance, the problem of recognizing object usage from object motion might appear trivial. g. 5Hz) motion, vibration, tilt, or accelerometer sensor to a wireless node. The device would transmit an object ID wirelessly when significant movement is observed by simply thresholding the motion, vibration, tilt, or acceleration signal, where the threshold is determined in an object independent manner (since setting object-dependent thresholds in the field increases installation complexity).