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 booklet constitutes the refereed complaints of the 1st ecu convention on Ambient Intelligence, AmI 2007, held in Darmstadt, Germany, in November 2007.
The 17 revised complete papers awarded including 5 examine reviews have been rigorously reviewed and chosen from forty eight submissions. The papers are geared up in topical sections on mobility and sensing, purposes of AmI, job and site sensing, AmI and synthetic intelligence, AmI middleware and infrastructure, and interplay with the surroundings.
The ebook is rounded off through a bit on case reviews and classes discovered, offering a excessive point collection of present learn stories and papers that mirror an important actions of present ambient intelligence research.
Read or Download Ambient Intelligence: European Conference, AmI 2007, Darmstadt, Germany, November 7-10, 2007. Proceedings PDF
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Extra resources for Ambient Intelligence: European Conference, AmI 2007, Darmstadt, Germany, November 7-10, 2007. Proceedings
Health Status Monitoring Through Analysis of Behavioral Patterns. : Inferring Activities from Interactions with Objects. S. Thesis, The Media Laboratory. : Guide: Towards Understanding Daily Life Via Auto-Identification and Statistical Analysis. : Hands-On RFID: Wireless Wearables for Detecting Use of Objects. In: ISWC 2005, pp. 38–41. : Giveaway Wireless Sensors for Large-Group Interaction. In: CHI 2004. Proceedings of The ACM Conference on Human Factors and Computing Systems, pp. 1291–1292.
Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. : Using a Live-In Laboratory for Ubiquitous Computing Research. , Quigley, A. ) PERVASIVE 2006. LNCS, vol. 3968, pp. 349–365.
Installing 200 single-point-of-contact sensors in a home may take as little as 2 manhours of effort, a tolerable amount of time not only for researchers but even possibly for end-users. The main disadvantage of using MEMs accelerometers to detect object usage is their relatively high energy consumption. For example, continuous sampling of the popular ADXL202 biaxial accelerometer (~500μA@3V) at 10Hz using a 3mA microcontroller results in a theoretical battery life of only 46 days from a CR2032 coin cell battery (220mA).