Eric Gregori is a Senior Software Engineer and Embedded Vision Specialist with Berkeley Design Technology, Inc. (BDTI), the industry's most trusted source of analysis, advice, and engineering for embedded processing technology and applications. He is a robot enthusiast with over 17 years of embedded firmware design experience. His specialties are computer vision, artificial intelligence, and programming for Windows Embedded CE, Linux, and Android operating systems. Eric authored the Robot Vision Toolkit and developed the RobotSee Interpreter. He is working towards his Masters in Computer Science and holds 10 patents in industrial automation and control.
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.