Researchers at IMDEA Networks Institute, together with European partners, have found that tire pressure sensors in modern cars can unintentionally expose drivers to tracking. Over a ten-week study, they collected signals from more than 20,000 vehicles, revealing a hidden privacy risk and highlighting the need for stronger security measures in future vehicle sensor systems. Most...
Yes and no, I think. It isn’t really huge amounts of data, and the patterns aren’t super complex, so a neural network would pick up a lot. But, given how far the signals travel, the intermittent nature of the signals, and how little they can initially be associated with a particular vehicle, I think in most environments associating a particular set of signals with a particular car would require some human field work. Sure, there are circumstances where automated pairing would be trivial (like at a toll booth), but catching signals in the wild and processing by neural net alone might be ok for analyzing traffic patterns while not being enough for surveillance.
Yes and no, I think. It isn’t really huge amounts of data, and the patterns aren’t super complex, so a neural network would pick up a lot. But, given how far the signals travel, the intermittent nature of the signals, and how little they can initially be associated with a particular vehicle, I think in most environments associating a particular set of signals with a particular car would require some human field work. Sure, there are circumstances where automated pairing would be trivial (like at a toll booth), but catching signals in the wild and processing by neural net alone might be ok for analyzing traffic patterns while not being enough for surveillance.