AmIware Hardware Technology Drivers of Ambient Intelligence by Rick Harwig (auth.), Satyen Mukherjee, Ronald M. Aarts, Raf

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By Rick Harwig (auth.), Satyen Mukherjee, Ronald M. Aarts, Raf Roovers, Frans Widdershoven, Martin Ouwerkerk (eds.)

Ambient Intelligence is without doubt one of the new paradigms within the improvement of knowledge and conversation know-how, which has attracted a lot consciousness over the last years. the purpose is the to combine expertise into humans setting in any such means that it improves their day-by-day lives by way of overall healthiness, creativity, and productiveness. Ambient Intelligence is a multidisciplinary suggestion, which seriously builds on a few primary breakthroughs which have been accomplished within the improvement of recent options over the last years. New insights in nano and micro electronics, packaging and interconnection know-how, large-area electronics, strength scavenging units, instant sensors, low strength electronics and computing systems permit the belief of the heaven of ambient intelligence by way of overcoming the hell of physics. in keeping with contributions from top technical specialists, this booklet provides a few key issues on novel advancements, hence delivering the reader an excellent perception into the actual foundation of ambient intelligence. It additionally shows key study demanding situations that needs to be addressed sooner or later.

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1–3b plots the change in DRV value versus the magnitude of variations in an SRAM cell. Local mismatch among transistors results in substantial DRV increase. Based on a 0:13 mm technology model, with 3s local Vth mismatch, the DRV is 70 mV higher than the ideal case with perfect matching. Global parameter shifting has a much weaker impact on DRV. 2. 1–4b) to verify the DRV model and explore the potential of leakage suppression using this method. 1–4a, the SRAM supply rails are connected to the standard and standby VDD through power switches.

Receiver sensitivity for a 12 dB SNR was measured at À78 dBm up to 40 kbps. As discussed above, the agility of the receiver is crucial in a wireless sensor network application. The enable-to-data latency of the receiver was measured to be 10 ms, much less than one symbol period. The total receiver current consumption is 3 mA with both channels enabled. To further reduce the power consumption of the receiver, a superregenerative architecture was explored. The design and implementation is beyond the scope of this chapter.

Energy scavenging [12]. 2 with Moore’s law. For the lowest bit rates, standby power (typically 50 mW) is again a limiting factor. Of course, a lot can be gained by proper system optimization. For example, microsystems can be provided with a ‘‘sleep mode’’, so that they consume power only intermittently, whereas energy scavenging is functional continuously. Yet, it can be concluded safely that with real smart dust type devices relying on energy scavenging or on a single nonreplaceable battery, very limited computing and communication is possible.

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