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The increasing hazards of texting while driving are creating quite a stir amongst lawmakers. Understandably, texting being a pretty involved activity, many States in the US have laws against sending SMS while driving. But inspite of tough rules texting is to addictive for young drivers to let go that easily.
Technically it is highly possible to have your text message send through the internet. A proof of concept lying with
Have the contacts feed in to the application making them a easy 'One touch' select, A Voice to Text for the message and one final "Send" to send the message.
Receiving messages both to the phone as well as the application isn't a technical ordeal. Giving ability to the user, that he may choose to "Hear" the message after being Notified with a Voice Notification "You have a message from ABC" using Text to Voice technology.
Proof of concept lies with SMS Servers, for instance on verizon the SMS server is:

Loooking forward to your feedbacks.
Idea submitted: 01.07.2010
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member since: 16.06.2010
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Hi VisteonIntern! Thanks for your critical comment and your interest on my app! I will try to explain you my thoughts :-) The first thing is i didn't use k-means which is a clustering technique which clusters a set of datapoints in a predefinded number of clusters and you are absolutely right that it is hard to determine the number of clusters before. Instead I used k-nearest neighbour classifier (I admit that the two names can esily be confound). Since I don't know if you are familiar with the concept of classifiers I will give you a short introduction: A classifier works as follows: 1. Step: trainig phase - in the training phase let me say you have to create the "world" with its elements the classifier should know. Let me give you an example: If you want to classify music acording to genre and you have four genres (classical, jazz, rock, rap), then you have to tell the classifier what are the characteristics of the different genres. So you will take many music clips (samples), calculate some features (beats, onsets, pitch, timbre ..) and train the classifier 2. Step: classification phase: now you will show the classifier a new music piece (sample) which he has never seen before. This peace will be compared with the peaces that were used in the training phase. According to the operation mode the classifier will then find the genre class to which the new peace belongs by mathematical calculations. In case of k-nearest neighbour the euclidean distance from the new sample to all samples from the training phase is calculated. According to the choosen number of "K" the k nearest samples from the training phase to the new sample are considered. If the new sample is mostly e.g. near class "classical" the classifier wil return class classical as result for the new sample. ---- now to your approach to use fuzzy logic. I think fuzzy logic is also a classification technique, but I must admit that I am not so familiar with it but I know that fuzzy logic is mostly used when there is no mathematical description of the "world" but a verbally like in speech recognition or automation of technical processes. -- I hope I could clarifiy your doubts a little bit ;-) if not feel free to ask me again or to tell me what you think is wrong with my approach! User2858
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