Being one of the engineers that worked on the initial development of this technology, it's amusing to read some of the comments from people who have little knowledge of what has already been implemented. The standard for airbag crash sensing systems is 0.99995 with 95% reliability - and you can imagine the amount of testing that is required to achieve that standard. In the early days of electronic crash sensing, when the technology was evolving from electromechanical sensing, engineers needed field data to validate the crash sensing algorithms, and to datamine relevant data for further algorithm development. The technology was developed to record only deployment events and near-deployment events, and to lock the data securely after a deployment event. The data was passively collected from barrier tests, taxi cab, police car, and rental car fleets and was used to validate the system before it ever got approval for use in passenger vehicles. Our families ride in the vehicles with the systems we design.
I guess in your line of engineering, design validation and continuous improvement by collection of field data is to be considered "crap"? Remind me what products you develop so I can avoid them.
That being said, once the technology is developed, the toothpaste is out of the tube, and bean counters and polticians abusing it can only be prevented by informed and active citizens. The government has no business using this data to incriminate individuals a priori, and should only be made available as subject to a warrant as provided in our 4th Amendment protections, until that goes away along the lines that the 9th, 10th, and 2nd Amendments are being assaulted today.
In 2012, 2.2 million people pledged $319 million to kick-start more than 18,000 of its projects on Kickstarter.com. Here's a look at some of the most inspired ideas from the ultimate crowdfunding platform.
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.