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Algorithm performance is investigated in the scenario of mobile tracking using signals of opportunity from digital TV (DTV) network.
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Mobile phone-based mobility tracking used to model traffic pollution contributions to both individual chronic and acute exposure can open new fields of research.
This paper suggests a novel algorithm for mobile object tracking using wireless sensor networks (WSNs).
This likelihood function is the key component of a track-before-detect scheme providing initial state estimates for mobile transmitter tracking using a particle filtering technique.
Single-target tracking using mobile sensor networks has been studied for a variety of different scenarios [12 14].
Owing in part to the increasing popularity of location tracking using cell phones, mobile providers dealt with a staggering 1.3 million requests in the past year.
Ess et al. [22] presented an approach of multiperson tracking using a stereo rig mounted on a mobile platform.
Consider mobile tracking by use of distance measurements in a cellular network or a wireless sensor network.
While encrypted messaging services such as WhatsApp are unaffected, SMS messages and calls placed across the mobile phone network can be listened in to, read and recorded, while the location of the phone can be tracked using the mobile network's location services independent of GPS or other location technologies on the phone.
Advertisers using the new mobile tracking methods include Ford Motor, American Express, Fidelity, Expedia, Quiznos and Groupon.
At the recent All Things Digital Conference, Google Executive Chairman and former CEO Eric Schmidt said that his company "built that technology and we withheld it," adding that he was concerned that "the union of mobile tracking and face recognition" could be used "in a very bad way" including by an "evil dictator".
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