That's certainly true, Rick. I was just at ITS World Congress in Tokyo. It was clear that every carmaker is in need of "purpose built" SoCs for autoomtive vision that sees and analyze the situation faster and better. (and at low power!)
This technology will get big fast. Since TI does manufacture chips for auotomotive, they have a leg up on the qualification requirements. Not all semiconductor companies can meet the automotive requirements.
"Further, 93 percent of traffic accidents in the United States are estimated to be due to human error."
I would have thought that number to be closer to 100 percent. I wonder, for example, if that stat includes less than ideal response to a sudden contingency, where a more expert, or perhaps automated reponse, could have avoided an accident. Things like skidding on ice, sudden tire failure, that sort of thing, where the blame is usually put on the mechanical problem rather than the response.
Very timely article. And if these vision systems are going to be a major component of the V2I solution, scanning signs and so on, there's going to be even more demand on the algorithms. Pretty exciting stuff, I'd say.
No doubt, this is a hot field that's growing fast, I think.
Until several years ago, a lot of machine vision stuff was done on a sheer compute power basis. Purpose-built ADAS SoCs by comanies like Cognive, TI, Freescale and ST will definitely change the landscape for automotive vision.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.