One class of smart-dust consists of very low power, low cost applications involving one or two sensors. The dust motes track some statistics about the values of those sensors and can be queried for those values. Perhaps the simplest of these is the "milk sensor" -- a device which tracks the maximum temperature of some refrigerated food product, such as milk, so that the consumer is guaranteed (s)he is buying a non-spoiled product.
Such an architecture can be built today using off the shelf parts, although the sizes of these parts are still 1-2 orders of magnitude larger than the 1mm^2 envisioned for smart dust. Consider the following design:
This PDF describes a simple temperature sensor which reads out to an LCD display. Modification of this approach to modulate the maximum temperature over a CCR periodically should be straightforward.
Here's a proposed algorithm:
Assume the CCR and passive components draw 2uW. The power consumption of the processor depends on the amount of time spent executing vs. sleeping. Steps 1-3 above require order 100 cycles (based on code given in PDF above), which at 300 ns/cycle is 30us. The CCR sends 10kbit/sec, so an 8 bit temperature will require about 1ms to transmit. Thus, the execution time per iteration of the loop is about 1ms. At 10 iterations/s (probably a large number), that's 10ms of execution and 990ms of sleep time per second. The total power consumption is thus:
2uW + ((10ms/1000ms/s)*400uA + (990ms/1000s)*1.5ua)*3V = 18.45uW Total.
Given a hearing-aid class battery gives 33mAh storage at 1.4V , that's 2504 hours (assuming no loss of power for voltage scaling) or more than three months of continuous operation.
This solution has not been scaled to smart dust sizes -- the microprocessor and battery are each order 100mm^2 (in packages). There's no reason to believe, however, that the microprocessor can't be scaled down using a smaller circuit process and package. Battery technology scaling needs to be investigated.
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This page last updated 3.19.2000 Sam Madden