By Twan Basten, Marc Geilen, Harmke de Groot (auth.), Twan Basten, Marc Geilen, Harmke de Groot (eds.)
Hugo de guy Professor Katholieke Universiteit Leuven Senior learn Fellow IMEC The regular evolution of undefined, software program and communications know-how is speedily reworking the computer- and dot.com international into the area of Ambient Intelligence (AmI). This subsequent wave of data expertise is fundam- tally varied in that it makes disbursed stressed out and instant computing and verbal exchange disappear to the heritage and places clients to the foreground. AmI adapts to humans rather than the opposite direction round. it is going to increase our awareness, computer screen our health and wellbeing and protection, advisor us via site visitors and so on. briefly, its final objective is to enhance the standard of our lifestyles by means of a quiet, trustworthy and safe interplay with our social and fabric atmosphere. What makes AmI engineering so attention-grabbing is that its layout starts off from learning individual to global interactions that have to be applied as an int- ligent and self reliant interaction of just about all valuable networked digital intelligence at the globe. it is a new and fascinating measurement for many choose- cal and software program engineers and will allure extra inventive expertise to engineering than natural know-how does. improvement of the major expertise for AmI will in simple terms be successful if the engineering study neighborhood is ready to affix forces on the way to make Mark Weiser’s dream of 1991 come real. this can now not be company as traditional by means of simply doubling transistor count number or clock velocity in a microprocessor or expanding the bandwidth of communication.
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Additional info for Ambient Intelligence: Impact on Embedded Sytem Design
Ducatel‚ M. Bogdanowicz‚ F. Scapolo‚ J. Leijten‚ and J-C. Burgelman. Scenarios for ambient intelligence in 2010. IST Advisory Group final report‚ 2002.  K. Goossens‚ J. Dielissen‚ J. van Meerbergen‚ P. Poplavko‚ A. Radulescu‚ E. Rijpkema‚ E. Waterlander‚ and P. Wielage. ” In A. Jantsch and H. Tenhunen‚ editors‚ Networks on Chip‚ pages 61–82. Kluwer Academic Publishers‚ 2003.  R. Harwig and E. Aarts. ” Proceeding of the 2002 International Interconnect Technology Conference‚ pages 3–5‚ 2002.
Furthermore‚ truly scalable computation must be cheap‚ reliable and energy-efficient. To address the scalability challenge in view of technology and design complexity limitations‚ hardware architectures for AmI will assume widely varying characteristics . Pursuing a biological analogy‚ we grouped AmI architectures in three classes‚ which roughly match the node type classification introduced in : workhorses‚ top-of-the line processors powering the high-speed fixed network backbone‚ exceeding l0 Gb/s performance and 100W power consumption; hummingbirds‚ complex systems-on-chip (SoCs) for high-bandwidth wireless networking and multimedia‚ with l0Mb/s performance and l00mW power consumption; butterflies‚ highly integrated wireless micro-sensor nodes for pervasive sensor networks‚ with l0Kb/s performance and power consumption.
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