Abstract: A technique for detecting the occurrence of an event, and for estimating other event-related information, by analyzing the barometric pressure in the vicinity of one or more wireless terminals. The disclosed detection technique is based on the recognition that the barometric sensor on various wireless terminals, such as smartphones, is capable of measuring very subtle changes in the atmospheric pressure. The disclosed detection technique is also based on the additional recognition of how some of the changes in the atmospheric pressure, as measured by a wireless terminal, correlate to various events that occur within a building or other defined area. For example, the disclosed technique can detect an entry door opening or closing by analyzing a resultant pressure wave having a particular transient that is perceptible by one or more wireless terminals in the area and analyzed by a detection engine.

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 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.

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 location engine that estimates the barometric pressure measurement bias of a pressure station reference, such as an airport pressure station, resulting in an improved estimate of the elevation of a wireless terminal. The location engine generates the estimate of bias of barometric pressure by comparing i) the outdoor barometric pressure measured by the airport pressure station at its unknown height above mean sea level (MSL) and ii) the expected outdoor barometric pressure derived from the pressure measurements from an already-calibrated pressure station, while accounting for the known height of the already-calibrated pressure station. The expected outdoor measurements correspond to a derived height above MSL of the airport pressure station. Subsequently, the location engine generates an estimate of the elevation of the wireless terminal by accounting for the estimate of measurement bias of the airport pressure station.

Abstract: A technique for detecting the occurrence of an event, and for estimating other event-related information, by analyzing the barometric pressure in the vicinity of one or more wireless terminals. The disclosed detection technique is based on the recognition that the barometric sensor on various wireless terminals, such as smartphones, is capable of measuring very subtle changes in the atmospheric pressure. The disclosed detection technique is also based on the additional recognition of how some of the changes in the atmospheric pressure, as measured by a wireless terminal, correlate to various events that occur within a building or other defined area. For example, the disclosed technique can detect an entry door opening or closing by analyzing a resultant pressure wave having a particular transient that is perceptible by one or more wireless terminals in the area and analyzed by a detection engine.

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 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.

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 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 method for estimating the location of a wireless terminal is disclosed that is based on using: the known location of one or more devices, empirical data that indicates the relative position of the wireless terminal to the devices, and empirical data that indicates the relative position of the wireless terminal (which is at an unknown location) relative to other wireless terminals that are also at unknown locations.

Abstract: An improved technique for the estimation of the location of a wireless terminal. A disclosed location engine is capable of utilizing a service set identifier (SSID) or a media access control (MAC) address, or both, received from a reporting wireless terminal, in order to improve the estimate of the wireless terminal's location. The location engine generates a first hypothesis for the location of the wireless terminal based on evidence of the location of the wireless terminal, such signal strength measurements, wherein the evidence is independent of the SSID and MAC addresses. The location engine also generates a second hypothesis for the location based on the SSID or a third hypothesis for the location based on the MAC address, or both. An estimate of location of the wireless terminal is based on a combination of the first, second, and third hypotheses. The estimate can then be used in a location-based application.

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 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: An improved technique for the estimation of the location of a wireless terminal. A disclosed location engine is capable of utilizing a service set identifier (SSID) or a media access control (MAC) address, or both, received from a reporting wireless terminal, in order to improve the estimate of the wireless terminal's location. The location engine generates a first hypothesis for the location of the wireless terminal based on evidence of the location of the wireless terminal, such signal strength measurements, wherein the evidence is independent of the SSID and MAC addresses. The location engine also generates a second hypothesis for the location based on the SSID or a third hypothesis for the location based on the MAC address, or both. An estimate of location of the wireless terminal is based on a combination of the first, second, and third hypotheses. The estimate can then be used in a location-based application.

Abstract: A location engine that estimates the barometric pressure measurement bias of a pressure station reference, such as an airport pressure station, resulting in an improved estimate of the elevation of a wireless terminal. The location engine generates the estimate of bias of barometric pressure by comparing i) the outdoor barometric pressure measured by the airport pressure station at its unknown height above mean sea level (MSL) and ii) the expected outdoor barometric pressure derived from the pressure measurements from an already-calibrated pressure station, while accounting for the known height of the already-calibrated pressure station. The expected outdoor measurements correspond to a derived height above MSL of the airport pressure station. Subsequently, the location engine generates an estimate of the elevation of the wireless terminal by accounting for the estimate of measurement bias of the airport pressure station.

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 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 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: An improved technique for the estimation of the location of a wireless terminal. A disclosed location engine is capable of utilizing a service set identifier (SSID) or a media access control (MAC) address, or both, received from a reporting wireless terminal, in order to improve the estimate of the wireless terminal's location. The location engine generates a first hypothesis for the location of the wireless terminal based on evidence of the location of the wireless terminal, such signal strength measurements, wherein the evidence is independent of the SSID and MAC addresses. The location engine also generates a second hypothesis for the location based on the SSID or a third hypothesis for the location based on the MAC address, or both. An estimate of location of the wireless terminal is based on a combination of the first, second, and third hypotheses. The estimate can then be used in a location-based application.