Big Data Assets series – Man-2-Machine Data
More and more the wearable technology is entering the realm of our daily lives. I’m sure almost everybody has already watched the Google head-up display (HUD) glasses promotional video. Do you think it’s something from a very distant future? Well, according to Google, you could buy a pair early next year for only 1500$… And Google is not the first one coming up with this HUD glasses idea. Vuzix started providing their augmented reality glasses long ago.
But you don’t have to wear any device to generate man-2-machine data… You just can do it with something you most probably have right now in your pocket: you smartphone.
According to comScore, the smartphone penetration in Europe reached 45% and in USA topped 50% the last March. More and more people are carrying devices in their pockets, capable of registering sensorial and geo-location data.
Apps like sleepcycle decides the best time to wake you up based on the sensorial inputs your smartphone collects from you during the night. A series of apps designed to assist you in your fitness activity, like Runkeeper for your running or myfitnesspal to keep track on the calories you consume start gathering interesting volumes of information that could enable the idea of a community driven lab for researchers, as explained in the post What if I told you, your data can save lives
What brings more hope to this idea is the fact that this technology is still in its infancy but on the main hurdles, the interface man 2 machine going beyond the mere sensorial information gathering, is being cleared.
Almost all top devices nowadays allow for a voice-based interaction (see SIRI, Dragon software, modern windows OS versions, advance Android devices, etc), and implement together with speech recognition techniques, natural language processing and semantic categorization techniques Turing’s dream: you are closer and closer to ignore the fact that you are interacting with a machine…
Maybe the usage of Big Data techniques can finally make this dream come true.
(This post is part of the Big Data Assets series, check them all!)