> First, we can combine sensor readings (if light reading is sub x then phone is not outdoors, for instance) and second, given appropriate volume we can arrive at valid averages – an answer that gets to the heart of what Big Data really means.
Even with volume I think this is a bigger problem than the article makes it out to be. The first thing that came to mind was a denser city area, in fact, density aside I think there is a significant number of people indoors (house, car, bus, train) at any given point in time. This data can be very helpful during the winter and summer to get a better idea of the RealFeel temp outside but during the winter people's phones are usually in their coats. Maybe there is some magic Big Data sauce that can be used alongside officially reported data but I'm a bit skeptical and curious at the same time.
As far as noisy data goes, I'd venture to classify this as very noisy.
Even with volume I think this is a bigger problem than the article makes it out to be. The first thing that came to mind was a denser city area, in fact, density aside I think there is a significant number of people indoors (house, car, bus, train) at any given point in time. This data can be very helpful during the winter and summer to get a better idea of the RealFeel temp outside but during the winter people's phones are usually in their coats. Maybe there is some magic Big Data sauce that can be used alongside officially reported data but I'm a bit skeptical and curious at the same time.
As far as noisy data goes, I'd venture to classify this as very noisy.