A vehicle control system includes a vehicle positional information obtaining unit, a user terminal positional information obtaining unit, a relative distance recognizing unit recognizing a relative distance between a vehicle and a user terminal based on vehicle positional information and user terminal positional information, a wide-area wireless communication control unit controlling implementation of the wide-area wireless communication in the vehicle, and a narrow-area wireless communication control unit controlling implementation of the narrow-area wireless communication in the vehicle and, if the relative distance is longer than or equal to a first determination distance set based on a communicable distance of the narrow-area wireless communication, restricting implementation of the narrow-area wireless communication in the vehicle.

Exemplary methods, apparatuses, and systems read location data representing a current location of a mobile device. The location data for the mobile device is taken at a first sampling rate. Upon determining that the location data indicates that the mobile device is approaching a geographic area having a history of wireless communication loss, the mobile device is triggered to increase location data sampling from the first sampling rate to a second sampling rate.

Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Also disclosed are various techniques to utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources. Such systems and methods can be applied in both indoor and outdoor settings and in retail or warehouse settings.

Systems are configured for performing GPS-based and sensor-based relocalization. During the relocalization, the systems are configured to obtain radio-based positioning data indicating an estimated position of the system within a mapped environment. The systems are also configured to identify, based on the estimated position, a subset of keyframes of a map of the mapped environment, wherein the map of the mapped environment includes a plurality of keyframes captured from a plurality of locations within the mapped environment, and the plurality of keyframes are associated with anchor points identified within the mapped environment. The systems are further configured to perform relocalization within the mapped environment based on the subset of keyframes.

Techniques for Check-In/Be-out (CiBo) and Be-in/Be-out (BiBo) using mesh networks are disclosed. In one implementation, an access control system includes a mesh network. The mesh network includes a set of mesh nodes disposed proximate to a gate to an access-controlled area and a master mesh node communicatively coupled to the set of mesh nodes. The master mesh node is configured to determine whether a device is near the gate based on a strength of a signal received at one of the set of the mesh nodes from the device. The system further includes a validator communicatively coupled to the master mesh node and a backend system. The validator is configured to: receive an indication from the master mesh node that the device is near the gate, determine, based on the indication, whether the device is authorized to enter or exit through the gate, and transmit a result of the determination of whether the device is authorized to enter or exit through the gate to the backend system.

The present invention discloses, inter alia, a computerized system for building a multisensory location map, the system comprising an interface for receiving multiple multisensory data vectors acquired by multiple mobile devices at multiple locations and accelerometer readings obtained upon movement of at least one device carried by at least one user between the multiple locations; at least a portion of said movement being walking; at least a majority of the multiple locations are located within an area in which an accuracy of global positioning system (GPS) based navigation is below an allowable threshold; and a processor, interconnected with said interface, with accelerometers, a magnetometer and a map calculator, configured for: extracting, out of accelerometer readings, accelerometer information related to multiple walking phases of the walking; for at least two of said multiple walking phases, real-time correcting a currently measured Z vector, and a pitch angle and a roll angle thereof, thereby compensating for horizontal accelerations, thereby obtaining a Z vector pointing toward Earth's center; calculating, from said Z vector pointing toward earth's center, a surface parallel to Earth's face (perpendicular to said Z vector pointing toward earth's center); estimating, from said surface parallel to Earth's face and from a magnetic north measured by at least one built-in magnetometer in said at least one device, an offset selected from a group consisting of: an azimuth offset from magnetic north and a heading offset from geometric north; processing the accelerometer information related to said at least two of said multiple walking phases to determine a direction of propagation of the at least one user and correcting said direction of propagation based on said offset; and estimating, from said corrected direction of propagation, at least one location of said at least one user; and the map calculator calculating, in response to the multiple multisensory data vectors and said at least one estimated location, a location fingerprinting map that comprises multiple grid points; each of the multiple grid points comprising a multisensory grid point fingerprint and grid point location information derivable from said at least one estimated location.

Systems are configured for performing GPS-based and sensor-based relocalization. During the relocalization, the systems are configured to obtain radio-based positioning data indicating an estimated position of the system within a mapped environment. The systems are also configured to identify, based on the estimated position, a subset of keyframes of a map of the mapped environment, wherein the map of the mapped environment includes a plurality of keyframes captured from a plurality of locations within the mapped environment, and the plurality of keyframes are associated with anchor points identified within the mapped environment. The systems are further configured to perform relocalization within the mapped environment based on the subset of keyframes.

Recent decades have brought tremendous advances in communication systems which have given rise to the global proliferation of smartphones and other mobile communication systems. A signal processing system implements technical solutions for determining building footprints from inputs including signal data associated with mobile communication devices.

A method is provided that includes obtaining or causing obtaining radiomap data representing at least a part of a structure. The radiomap data includes radiomap data acquired at least along a part of a first track comprising a first position at a reference altitude and a second position inside of the structure. The method also includes associating or causing associating the radiomap data of the second position with relative altitude information of the structure based on the reference altitude of the first position. A corresponding apparatus and computer program product are also provided.

Corrected User Equipment (UE) positioning is based at least in part on signaling that is associated with UE inertial measurements. Such measurements are used in some embodiments to track UE locations along trajectories of UE movement and develop or obtain a model to subsequently predict UE positioning corrections based on channel estimates of a wireless channel. For example, reference signaling may be transmitted by a UE, and the UE then receives positioning corrections or corrected positioning in response to the reference signaling.