Looking forward to learning how low you can go in obtaining vision information.Wondering if anything is within reach of microcontrollers, or if it needs a multi-chip solution.
It is definitely possible to do some simple vision processing on a microcontroller. It all depends on your data rate (resolution x frame rate) and the complexity of your algoriths. If you just wanted to do face detection at close range, for example, and could tolerate latency of perhaps one second, that would likely be doable on an MCU. Most vision functions will require more processing power, however. Also, interfeacing image sensors to MCUs can be a challenge.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.