@sharthappens

http://www.twitter.com/sharthappens

TampaMarc: Lord grant me the serenity to accept the things I cannot change, the courage… Aww never mind. Just give me a gun. I’ll take it from there.

TampaMarc: The meaning of life escapes me, but I’m pretty sure it has something to do with cheesy nachos!

TampaMarc: @Sarahglitter Easy on the breakfast Punkin. Every time you have eggs, they end up fertilized! I KILL ME!!!

TampaMarc: I think Twitter should add a button just above ‘Follow’ and call it ‘Stalk’. Or something more PC like ‘Stealth Admire’.

TampaMarc: Just realized what a great tool twitter can be for assassins… Attention Assassins: I “WILL NOT” be at Caddy’s or Hula Bay Club today!

TampaMarc: @queenoftroops Due to budget cuts, the glass slipper’s been replaced w/ a pleather sneaker. Oh, and we had to let Prince Charming go…

TampaMarc: Learned to speak text tonight. For instance; “lol rotfl ttyl mwah” translates to “you’re a tool if you know what this means”!!!

TampaMarc: I’m calling it now… Swine flu = bedazzled surgical masks by summer. Ed Hardy, are you listening?

TampaMarc: I’m watching the dog watch me, but it makes me wonder… Doesn’t this bitch have anything better to do?

TampaMarc: Is a “Ninja Assassin” a ninja who is an assassin, or someone who assassinates ninjas? Do you hire a ninja assassin to assassinate a ninja?

Second, I don’t think it would require as much data as you might at first think it would require. Often in complex situations like multi-car collisions people get confused by a glut of information and think that a lot of data is important when the reality is that most of it isn’t really contributing to the issue.

Malcolm Gladwell talks about this in his book Blink that was on the NY Times best seller list. One of the examples was detecting heart attacks in the ER. It turns out that doctors tended to gather quite a lot of information to decide if a particular patient was having a heart attack and detection was poor. What dramatically improved detection was in fact reducing the amount of information they used, restricting it to just 4 variables. That improved detection quite a bit, bringing it up if I remember correctly from around 60-ish percent to around 90-ish percent.

So I think what we might start to see is an extension of the OnStar system that would just count neighboring cars on a GPS grid, compare that to a very short list of common causes of traffic collisions, and then alert the driver with an easily recognizable signal that “this situation merits a little extra caution”.

So as an example, you’re driving down the freeway, the system notices a vehicle behind you that’s weaving through traffic at a speed faster than the surrounding traffic. The car pops on the “caution” light and sounds a small bell. And a moment later you see the guy weave in front of you on his way to wherever. It doesn’t prevent people from doing dumb things, but it gives everyone a little heads up.

The same system could similarly detect the pattern of traffic swerving around a foreign object in the road ahead, without knowing what the object is, just by following the GPS signatures of the cars.

The eye data might still be useful, but probably primarily for the purpose of alerting drivers who are too drowsy to drive. Studies have shown that driving drowsy is actually much more dangerous than driving drunk. And in the case of drunk or drowsy eratic drivers we might even see the same system dispatch a police cruiser to the scene in some cases to help keep folks safe.

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My wife sent me the NYT article on you. Take a look at our website and let me know if you are intersted in learning more about ECAP or any of our clean tech companies.

Regards,

Bill Gildea