Embodiments of the present invention relate to the field of mobile communications technologies, and in particular, to an indoor positioning method and an apparatus. In this solution, a positioning server obtains floor numbers of floors on which at least one base station is located; the positioning server receives identification information of a first terminal; the positioning server determines the first terminal according to the identification information; and the positioning server determines vertical location information of the first terminal according to the floor numbers of the floors on which the at least one base station is located. When a terminal is located indoors, positioning is meaningful only when a specific floor on which the terminal is located is determined.

A method includes obtaining piece(s) of calendar information indicative of at least one appointment taking place in a space and extracting a set of space identifiers representing space(s) of the venue. The space identifier(s) for one or more spaces are extracted based on an indoor map of the venue. The method also includes determining or triggering determining whether at least a part of the set of space identifiers or one or more spaces of the set of space identifiers match(es) the at least one space as represented by the piece(s) of calendar information; and if a match is found: determining one or more reference location estimates. A respective reference location estimate is indicative of a location of the space that was determined to be a match. A corresponding apparatus, computer program product and system are also provided.

Techniques are described herein for developing a fingerprint map that may be used for 3D indoor localization. In one example, a network server may leverage a building footprint from an open source database with signal measurements taken by probing user devices from signal sources such as access point (AP) devices. The network server may use the signal measurements to remotely calculate corresponding 3D positions of the AP devices in a particular building. Further, the network server may use the building footprint and the calculated 3D positions of the AP devices as references for developing the fingerprint map for 3D indoor localization.

Techniques for suggesting accessory devices controlled by an application executing on a mobile device are disclosed. A method includes measuring one or more sensor values using one or more sensors of a mobile device and the one or more sensor values are determined from one or more signals emitted by a first one or more accessory devices. An area of a physical space for the first one or more accessory devices can be determined based on the one or more sensor values. A second one or more accessory devices associated with the same area as the first one or more accessory devices can be suggested to a user.

Techniques are described herein for developing a fingerprint map that may be used for 3D indoor localization. In one example, a network server may leverage a building footprint from an open source database with signal measurements taken by probing user devices from signal sources such as access point (AP) devices. The network server may use the signal measurements to remotely calculate corresponding 3D positions of the AP devices in a particular building. Further, the network server may use the building footprint and the calculated 3D positions of the AP devices as references for developing the fingerprint map for 3D indoor localization.

A system to assist in monitoring and improving services in hotels, motels and other lodging facilities. The system includes a plurality of fixed-location wireless devices that are situated throughout the facility and each service provider or asset to be monitored or tracked is provided with a cooperating mobile wireless device. The mobile devices may periodically transmit beacons that are received by the fixed location devices. The system may determine location based on evaluation of signal strength across a plurality of fixed devices. The system may include premapped calibration data on signal strength to assist in determining location. The location information may help to assess employee performance, to assist in improving performance and to provide improved services. The system may also interact with an application running on a hotel guest's electronic device to allow the system to track guest location. Guest location information can be used to provide improved guest services.

Location of objects within an identified subspace defined within a predefined master space. The system includes an RF beacon associated with an object, the RF beacon transmitting signals to one or more of RF tags transmitting to an object location system a tag data package including an identification of the signals received by the RF tags from the RF beacon. The system includes a gateway receiving and extracting, from the transmitted tag data package, the identification of signals. The system further includes the location engine accessing an ML model trained by performing a survey of RF signals received from a plurality of RF signal sources during a prior RF master space survey operation and determining a subspace identifier corresponding to a predicted subspace location for the object by comparing the identification of signals included in the received tag data package to a model plurality of signals accessed from the model.

Disclosed are systems, methods, and non-transitory media for performing passive radio frequency (RF) location detection operations. In some aspects, RF data, such as RF signals including channel state information (CSI), can be received from a wireless device. The RF data can be provided to a self-supervised machine-learning architecture that is configured to perform object location estimation.

Techniques for suggesting accessory devices controlled by an application executing on a mobile device are disclosed. A method includes measuring one or more sensor values using one or more sensors of a mobile device and the one or more sensor values are determined from one or more signals emitted by a first one or more accessory devices. An area of a physical space for the first one or more accessory devices can be determined based on the one or more sensor values. A second one or more accessory devices associated with the same area as the first one or more accessory devices can be suggested to a user.

Disclosed are systems, methods, and non-transitory media for performing passive radio frequency (RF) location detection operations. In some aspects, RF data, such as RF signals including channel state information (CSI), can be received from a wireless device. The RF data can be provided to a self-supervised machine-learning architecture that is configured to perform three-dimensional (3D) object location estimation.