Abstract: A method for performing contact tracing. An analysis system performing the method receives geo-temporal data comprising location data points for various wireless terminals, including the wireless terminal being used by a person diagnosed as having a specified disease and the wireless terminals of people who possibly have come in contact with the infected person. Based on filtering the geo-temporal data, the analysis system generates relatively-condensed mobility profiles that are representative of each person's locations and movements, and analyzes the mobility profiles. Through careful selections of various parameters based on the disease that is being analyzed, the mobility profiles are used instead of the relatively large amounts of geo-temporal data, to represent users of wireless terminals and to determine their interactions in regard to disease transmission.

Abstract: A method for performing contact tracing. An analysis system performing the method receives geo-temporal data comprising location data points for various wireless terminals, including the wireless terminals being used by people diagnosed as having a specified disease and the wireless terminals of others, one of whom having possibly infected those diagnosed with the disease. Based on filtering the geo-temporal data, the analysis system generates relatively-condensed mobility profiles that are representative of each person's locations and movements, and analyzes the mobility profiles. Through careful selections of various parameters based on the disease that is being analyzed, the mobility profiles are used instead of the relatively large amounts of geo-temporal data, to represent users of wireless terminals and to determine their interactions in regard to disease transmission.

Abstract: A method for estimating the location of a wireless terminal at an unknown location, such as within a building. A location engine using the disclosed method receives and uses samples of barometric pressure measured by the wireless terminal to generate a characterization of a pressure wave in the vicinity of the wireless terminal. The location engine generates an estimate of the location of the wireless terminal based on the characterization of the pressure wave and, in some cases, the location of the source of the pressure wave, such as a building's door that is opening or closing. The location engine also bases the estimate of the wireless terminal's location on a propagation characteristic of the pressure wave, such as its speed of propagation.

Abstract: A location engine that generates an estimate of the measurement bias of the pressure sensor in a wireless terminal. The estimate is determined from a probability distribution characterized as having a flat top with exponentially decaying sides. The probability distribution is generated by inferring i) a range of elevations within which the wireless terminal is most likely present, wherein the elevations have associated barometric pressures, and ii) a corresponding range of measurement biases based on an inferred range of the barometric pressures. The location engine updates the probability distribution over time. The location engine makes a single estimate of measurement bias available by determining a mean of the updated probability distribution, such as an average of the low and high endpoints that define the flat top. Subsequently, the location engine generates an estimate of the elevation of the wireless terminal by accounting for the estimate of measurement bias.

Abstract: A technique 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 a transient in atmospheric pressure attributed to a particular source, such as an entry door of a building opening and closing, is detectable in some environments while not being present in others. The second part of the recognition is that a correlation exists between i) the presence of a transient in the characterization of a pressure wave in the vicinity of a wireless terminal and ii) whether the wireless terminal is indoors or not. Transients in pressure waves are often present indoors but not outdoors. By accounting for the transients 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.

Abstract: A system and method according to the principles of the invention identifies mobile phone aliases. The system processes mobile location data and call event data to generate mobility profiles. The profiles indicate a mobile's geographic zone history over a specified time. To produce a mobility profile, the system aggregates location data into zones and associates the zones with times of day, week or month. Particular zones for different mobiles can be compared according to weighting algorithms to provide data indicating whether the mobiles belong to the same user.

Abstract: A system and method for ray launching in electromagnetic wave propagation modeling. A data-processing system receives a dataset that is representative of a plurality of structures within an environment. The plurality of structures is defined in the dataset as having a plurality of surfaces. The system then partitions each surface in the plurality of surfaces into a plurality of tiles. The system pre-computes whether i) the reference point of each corresponding tile in each plurality of tiles of each surface is visible or not from ii) the reference point of each possible spawning tile in each other plurality of tiles. The system then projects a first set of ray tubes based on the pre-computed visibility. The system evaluates the incidence of bounced ray tubes at a predetermined receive point within the environment and then presents a propagation result that is based on the evaluated incidence of the bounced ray tubes.

Abstract: A location engine that estimates the barometric pressure measurement bias of a wireless terminal, resulting in an improved estimate of elevation of the wireless terminal. The location engine generates an estimate of measurement bias by comparing the barometric pressure measured by the wireless terminal while at that elevation and the barometric pressure that corresponds to an estimated elevation of the wireless terminal when it made the pressure measurement (i.e., the expected pressure). The estimated elevation is based on an inferred above-ground height and the local terrain elevation, and the expected pressure is based on the measurement of barometric pressure at the pressure reference and the estimated elevation. The location engine infers the height based on various techniques disclosed herein. The location engine can use the measurement bias to adjust subsequent pressure measurements reported by the wireless terminal, in order to generate an improved estimate of elevation of the wireless terminal.

Abstract: A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.

Abstract: A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.

Abstract: A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.

Abstract: A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.

Abstract: A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.

Abstract: A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.

Abstract: A data-processing system that estimates the particular building floors that are present in a particular building based on differences in barometric pressure measurements provided by wireless terminals. A wireless terminal can report one or more barometric pressure measurements at the ground floor of a building and one or more pressure measurements at one or more above- or below-ground floors, or “non-ground” floors. The data-processing system receives the pressure measurements and uses the difference in the pressure measurements to determine a change in height between the ground floor and a non-ground floor. When the system collects enough data from many wireless terminals, it is able to identify the floors that are present in a particular building and their non-ground heights. Then, when an estimate of the vertical location of a wireless terminal is provided to a location application, the system is able to provide the estimate in terms of building floor.

Abstract: A location engine that generates an estimate of the measurement bias of the pressure sensor in a wireless terminal. The estimate is determined from a probability distribution characterized as having a flat top with exponentially decaying sides. The probability distribution is generated by inferring i) a range of elevations within which the wireless terminal is most likely present, wherein the elevations have associated barometric pressures, and ii) a corresponding range of measurement biases based on an inferred range of the barometric pressures. The location engine updates the probability distribution over time. The location engine makes a single estimate of measurement bias available by determining a mean of the updated probability distribution, such as an average of the low and high endpoints that define the flat top. Subsequently, the location engine generates an estimate of the elevation of the wireless terminal by accounting for the estimate of measurement bias.

Abstract: A system and method according to the principles of the invention identifies mobile phone aliases. The system processes mobile location data and call event data to generate mobility profiles. The profiles indicate a mobile's geographic zone history over a specified time. To produce a mobility profile, the system aggregates location data into zones and associates the zones with times of day, week or month. Particular zones for different mobiles can be compared according to weighting algorithms to provide data indicating whether the mobiles belong to the same user.

Abstract: A technique for the estimation of the location of a wireless terminal. The disclosed technique considers boundaries that are represented in a geographic information system (GIS) database in combination with a first, unenhanced estimate of location, in order to generate a second, enhanced estimate of location. To do so, the technique generates a point cloud based on the first estimate of location. At least some of the data points in the point cloud are then removed, depending on their positions in relation to certain boundaries stored in the GIS database, such as the exterior walls of buildings and other structures. By considering these boundaries, the disclosed technique can increase the probability that the estimated location is within an area that is occupiable by a person, thereby providing a more reasonable result. The technique generates the second, enhanced estimate based on the distribution of the remaining data points.

Abstract: A technique for developing a stack-effect compensation model that is representative of a structure, such as a particular building, and of generating an estimate of the elevation of a wireless terminal inside the structure by using the model. The technique includes estimating information related to one or more neutral pressure planes within the structure, at which the difference between the indoor barometric pressure and the outdoor barometric pressure is essentially zero. The technique leverages pressure and temperature measurements that are provided by one or more wireless terminals that are regularly present in the building. The stack-effect compensation model includes a parameter that represents, for each of a plurality of uncompensated elevations, the height of the particular uncompensated elevation above a neutral pressure plane. The location engine uses this height-information parameter from the compensation model, in order to develop the estimate of the elevation of the wireless terminal.

Abstract: A system and method for graphical representation of spatial data. A disclosed video display system is capable of presenting a layout of graphics objects as part of a displayed image. The system provides in the displayed image i) a first graphical representation in a first display area of a display and ii) a diagrammatic representation in a second display area. The diagrammatic representation features superimposed graphical elements that are dependent on the first graphical representation. The video display system can provide, for example, a pie chart as the first graphical representation and a map of a geographic area as the diagrammatic representation. The pie chart graphically represents, for example, a breakdown of members by organization, wherein each slice in the pie chart corresponds to a different organization. Superimposed on the map are elements of a bar chart, which is another example of a graphical representation.