Entity

Time filter

Source Type

Santa Clara, CA, United States

Patent
Polaris Wireless Inc. | Date: 2012-05-22

An illustrative system and method for detecting a wireless terminal in a wireless network by ascertaining information about the wireless terminals location, thus enabling individualized surveillance and tracking of certain wireless terminals. In some embodiments, the detection is triggered by a signal that is compliant with the Customized Applications for Mobile networks Enhanced Logic (CAMEL) protocol. Several kinds of mobile-telecommunications events can trigger detection, including events that do not involve call origination. Advantages include bypassing the home location register when obtaining a location estimate for the wireless terminal and when determining whether a wireless terminal is of interest.


A technique is disclosed for estimating the location of a wireless terminal at an unknown location in a geographic region. The technique is based on a two-part recognition, the first part being that there are certain lighting and acoustic characteristics that are present in some environments while not being present in others, such as lighting flicker and sound reverberation. The second part of the recognition is that a correlation exists between the presence of flicker and reverberation in the vicinity of a wireless terminal and whether the wireless terminal is indoors or not. Under certain environmental conditions, flicker and reverberation are often present indoors but not outdoors. By accounting for flicker and reverberation being detected or not being detected in the vicinity of the wireless terminal, the disclosed technique is able to estimate whether the wireless terminal is indoors, which the technique also uses to improve the location estimate.


A technique is disclosed for estimating the location of a wireless terminal at an unknown location in a geographic region. The technique is based on a two-part recognition, the first part being that there are certain optical and acoustic characteristics that are present in some environments while not being present in others, such as lighting flicker and sound reverberation. The second part of the recognition is that a correlation exists between the presence of flicker and reverberation in the vicinity of a wireless terminal and whether the wireless terminal is indoors or not. Under certain environmental conditions, flicker and reverberation are often present indoors but not outdoors. By accounting for flicker and reverberation being detected or not being detected in the vicinity of the wireless terminal, the disclosed technique is able to estimate whether the wireless terminal is indoors, which the technique also uses to improve the location estimate.


Patent
Polaris Wireless Inc. | Date: 2012-08-01

An illustrative behavior analysis system and a corresponding method are designed to analyze telecommunications-event records and other relevant records associated with wireless terminals to infer whether a wireless users pattern of behavior is substantially similar or even identical to the pattern of behavior of another user, possibly a known actor, A pattern of behavior typically comprises call-related and location attributes over a period of time. Accordingly, the illustrative embodiment infers an identity or a substantial similarity as between two seemingly distinct users of wireless terminals, based on: (i) how precisely a candidates pattern of behavior matches a pre-defined pattern of behavior, and/or (ii) how precisely a candidates pattern of behavior matches another candidates pattern of behavior.


Patent
Polaris Wireless Inc. | Date: 2012-09-27

Methods and systems populate a speech signature database with unique speech signatures that are associated with one or more speaker identities and are further associated with one or more mobile stations and/or telephone numbers. Real-time voice signals are compared to the speech signatures in the speech signature database. When a match is found, the mobile station from which the voice signal originated is located in real-time. Further, the associations in the speech signature database are leveraged to find other relevant mobile stations or users and to generate additional associations and to also locate associated users and mobile stations.

Discover hidden collaborations