By Twan Basten, Marc Geilen, Harmke de Groot
Hugo de guy Professor Katholieke Universiteit Leuven Senior examine Fellow IMEC The regular evolution of undefined, software program and communications expertise is quickly remodeling the computer- and dot.com global into the realm 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 conversation disappear to the history and places clients to the foreground. AmI adapts to humans rather than the wrong way round. it is going to increase our awareness, video display our future health and safeguard, advisor us via site visitors and so forth. in brief, its final aim is to enhance the standard of our lifestyles through a quiet, trustworthy and safe interplay with our social and fabric setting. What makes AmI engineering so interesting is that its layout begins from learning individual to global interactions that must be applied as an int- ligent and self reliant interaction of just about all beneficial networked digital intelligence at the globe. it is a new and intriguing measurement for many pick- cal and software program engineers and should allure extra inventive expertise to engineering than natural know-how does. improvement of the best know-how for AmI will basically be successful if the engineering study neighborhood is ready to affix forces to be able to make Mark Weiser’s dream of 1991 come real. this may no longer be enterprise as ordinary via simply doubling transistor count number or clock pace in a microprocessor or expanding the bandwidth of conversation.
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Extra info for Ambient Intelligence Impact on Embedded System Design
They are big footprint devices that can efficiently process large software stacks that implement sophisticated computational intelligence algorithms. The network that connects the devices is rather straightforward from a functional point view just allowing data communication‚ possibly at high bit rates. In the opposed view of ambient intelligence outside the terminals may be small footprint devices just allowing for the data communication that is required to generate output or to take new input.
Roughly half of the power is dissipated in “switching logic”‚ which includes caches. The chip contains 221M transistors‚ and only 25M is dedicated to computational logic. Hence‚ the vast majority of transistors are in memories. Even though‚ memory power density is notoriously smaller than logic power density‚ such a disproportion between memory transistors and logic transistors leads us to conjecture that at least half of the “switching logic” power is consumed in memories and memory buses. Furthermore‚ 33% of the total power is consumed by clock generation and distribution‚ and another 8% is consumed by global repeaters and I/O drivers.
Such constraint is further enforced by even more stringent size and weight constraints. In fact‚ the ambient intelligence paradigm envisions micro-sensors no larger than a few cubic millimeters‚ and no heavier than a few grams. These size and weight ranges automatically rule out the possibility of adopting conventional power sources: any type of battery would be too large and heavy. Furthermore‚ the sensors will not necessarily be located in fixed positions‚ and their tiny size may even make impossible to physically handle them.