A positioning method includes separately sending, by a terminal, a request for obtaining assistance data to a serving base station and a neighboring cell base station; separately receiving, by the terminal, assistance data from the serving base station and the neighboring cell base station; identifying, by the terminal based on the assistance data, reference signals received from the serving base station and the neighboring cell base station; calculating, by the terminal, a time difference of arrival based on times at which the reference signals arrive at the terminal; and sending, by the terminal, the time difference to a server using an application layer protocol, to enable the server to calculate location information of the terminal.

Systems and methods are provided for receiving a request for services in a given location from a client device operated by a user and generating a set of features based on information included in the request for services in the given location. The systems and methods further provide for analyzing the set of features using a machine learning model to predict whether only services that can be instantly booked should be provided in response to the request for services in the given location, analyzing a prediction output by the machine learning model to determine that only services that can be instantly booked should be provided in response to the request for services in the given location, and generating a list with only services that can be instantly booked.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one more processors and perform training a machine learning model based on historical input data for pickups by users that occurred during a historical time period and output data comprising actual wait times that occurred for the pickups by the users; receiving an order from a user for a pickup from a physical store during a selected time slot of a selected date; adding the order to a queue of assembled checked-in orders; determining an estimated arrival time based on geo-tracking; generating an estimated wait time using the machine learning model, as trained, and can be based on input data; and sending the estimated wait time to at least one of the physical store or the mobile device of the user. Other embodiments are disclosed.

A method for estimating a time of arrival of a signal transmitted over a wireless channel, includes receiving the signal by a receiving device; correlating the received signal with a filtered code sequence to create a correlation output, identifying in the correlation output, an observation window associated with a main lobe in the correlation output; and processing the observation window to determine a time of arrival of a first path component in the received signal. The filtered code sequence is formed by incorporating a time of arrival matched filter (TOA-MF) inside predetermined shaped code sequence. The TOA-MF is matched to the predetermined shaped code sequence and is based upon a power delay profile of the wireless channel. The predetermined shaped code sequence is a convolution of a predetermined shaping sequence and a predetermined code sequence.

A roadside positioning method includes: obtaining positioning information of the user terminal, the positioning information being used for indicating a geographic location of the user terminal; obtaining wireless signal information of the user terminal, the wireless signal information being used for indicating wireless signals acquired by the user terminal at the geographic location; and determining a roadside positioning result of the user terminal based on the positioning information and the wireless signal information, the roadside positioning result being used for indicating a roadside on which the user terminal is located.

This application provides example positioning methods and example apparatuses. One example method includes sending, by a positioning management network element, a positioning measurement request to a positioning measurement network element. The positioning measurement request is used to request the positioning measurement network element to feed back channel state information of a terminal device. Then, the positioning management network element receives a positioning measurement response from the positioning measurement network element. The positioning measurement response includes the channel state information of the terminal device. Then, the positioning management network element determines a location of the terminal device based on the channel state information of the terminal device.

Embodiments described herein provide a localization mechanism that blends location data collected from hardware sensors equipped with a personal mobile vehicle and location and/or status data collected from external location source other than the personal mobile vehicle to generate adjusted location data for the personal mobile vehicle.

A personal proximity warning device for warning a user of a rear approach of a person includes a housing that is removably attachable to an item worn by the user. A camera and a sensor attached to the housing capture an image of and sense motion within an area proximate to the user. A battery, a transceiver, and a microprocessor are positioned in the housing. The microprocessor selectively actuates the camera and the transceiver to capture and transmit the image of the area, respectively, and actuates the transceiver to transmit an alert. Programming code, which is selectively positionable on an electronic device of the user, enables the electronic device to receive the alert and the image, to override audio to earbuds being worn by the user, and to broadcast the alert to the user via the earbuds.

An orthogonal or multi-dimensional fabric interface is described herein to select and present content to a user. A location is determined and time is selected for the user. The multi-dimensional fabric is accessed for content based the determined location and the selected time. If content is stored in the multi-dimensional fabric at the determined location and the selected time, the user is notified of the content, which can then be presented to the user.

Apparatus and methods for controlling a path of an autonomous mobile device based upon defining a series of origination positions and destination positions, each destination position correlating with position coordinates. A current position of an autonomous vehicle is determined via location automation such as real time communication systems and an approved pathway is generated to guide the autonomous vehicle. The position coordinates may be a set of values that accurately define a position in two dimensional 2D or three-dimensional (3D) space. Position coordinates may include cartesian coordinates.