User location assisted customer-site interactions using user-centric artificial intelligence (AI) agent

Abstract

In some aspects, a device may obtain, via an artificial intelligence (AI) agent, customer- specific information associated with a customer. The device may determine, via the AI agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information. The device may obtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

Description

Qualcomm Ref. No. 2503640WO1 / 55USER LOCATION ASSISTED CUSTOMER-SITE INTERACTIONS USING USER-CENTRIC ARTIFICIAL INTELLIGENCE (Al) AGENTCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present Application for Patent claims priority to Greek Patent Application No.20250100222, entitled “USER LOCATION ASSISTED CUSTOMER-SITE INTERACTIONS USING USER-CENTRIC ARTIFICIAL INTELLIGENCE (Al) AGENT,” filed March 26, 2025, which is assigned to the assignee hereof and expressly incorporated herein by reference in its entirety.BACKGROUND OF THE DISCLOSURE / . Field of the Disclosure

[0002] Aspects of the disclosure relate generally to wireless technologies.2. Description of the Related Art

[0003] Electronic shelf labels (ESLs) are an example of electronic label devices used by retailers for displaying product pricing or other product information to consumers, ESLs typically use electronic paper (e-paper) or liquid crystal display (LCD) to display the current information. E-paper (also referred to as e-ink) is widely used for ESLs, as it provides a sharp display and supports full graphic imaging while only needing power during updates and no power to retain an image.

[0004] ESLs are increasingly being integrated with existing retail technologies, such as electronic article surveillance, digital signage, and people counters. For example, retailers can upload a floor plan of the sales area into the ESL management software. Consumers can then be tracked (in real time) through a network of people-counting devices, or via their personal BLUETOOTH® devices, in order to determine their position within the store at all times. This allow s an individual customer to receive targeted, customized marketing initiatives, such as discounts, individual pricing, etc,SUMMARY

[0005] The following presents a simplified summary relating to one or more aspects disclosed herein. Thus, the following summary should not be considered an extensive overviewQC2503640WOQualcomm Ref. No. 2503640WO2 / 55relating to all contemplated aspects, nor should the following summary be considered to identify key or critical elements relating to all contemplated aspects or to delineate the scope associated with any particular aspect. Accordingly, the following summary has the sole purpose to present certain concepts relating to one or more aspects relating to tire mechanisms disclosed herein in a simplified form to precede the detailed description presented below.

[0006] in some aspects, a device includes one or more memories; one or more transceivers; and one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to: obtain, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and obtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0007] In some aspects, a method of positioning performed by a device includes obtaining, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; determining, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and obtaining a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0008] In some aspects, a non-transitory computer-readable medium stores computer-executable instructions that, when executed by a device, cause the device to: obtain, via an artificial intelligence (Al) agent customer-specific information associated with a customer; determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and obtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0009] In some aspects, a device includes means for obtaining, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; means for determining,QC2503640WOQualcomm Ref. No. 2503640WO3 / 55via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and means for obtaining a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0010] Other objects and advantages associated with the aspects disclosed herein w ill be apparent to those skilled in the art based on the accompanying drawings and detailed description.BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are presented to aid in the description of various aspects of the disclosure and are provided solely for illustration of the aspects and not limitation thereof.

[0012] FIG. 1 illustrates an example electronic shelf label (ESL) system, according to aspects of the disclosure.

[0013] FIG. 2 illustrates example components of an example ESL, according to aspects of the disclosure.

[0014] FIGS. 3A, 3B, and 3C are simplified block diagrams of several sample aspects of components that may be employed in a user equipment (UE), a base station, and a network entity, respectively, and configured to support communications as taught herein.

[0015] FIG. 4 is a diagram illustrating an example electronic shelf label (ESL) deployment scenario, according to aspects of the disclosure.

[0016] FIG. 5 illustrates an example neural network, according to aspects of the disclosure.

[0017] FIG. 6 is a diagram illustrating example interaction between an application, an application service, an operating system (OS), and hardware using various application programming interfaces (APIs), according to aspects of the disclosure.

[0018] FIG. 7 illustrates an example of a system architecture for Al agent-based customer-site interactions, according to aspects of the disclosure

[0019] FIG. 8 illustrates an example method of positioning, according to aspects of the disclosure.DETAILED DESCRIPTIONQC2503640WOQualcomm Ref. No. 2503640WO4 / 55

[0020] Aspects of the disclosure are provided in the following description and related drawings directed to various examples provided for illustration purposes. Alternate aspects may be devised without departing from the scope of the disclosure. Additionally, well-known elements of the disclosure will not be described in detail or will be omitted so as not to obscure the relevant details of the disclosure,

[0021] Various aspects relate generally to location-assisted customer-site interactions. Some aspects more specifically relate to location-assisted customer-site interactions by using a customer-centric artificial intelligence (Al) agent. In some examples, a device (e.g., a user equipment (UE), a server, or a cloud) may obtain, via an Al agent, a customerspecific shopping model of a customer based at least in part on customer-specific information of the customer, determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain an offer associated with one or more items for sale to the customer based at least in part on tire customer¬ specific shopping model, and transmit a notification of the offer to the customer.

[0022] Particular aspects of the subject matter described in this disclosure can be implemented to realize one or more of the following potential advantages. In some examples, by using a customer-centric Al agent for customer-site interactions, the described techniques may be used to facilitate sales by allowing merchants to offer discounts or other incentives tailored to the predicted needs or preferences of the customer,

[0023] Tire words “exemplary” and / or “example” are used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” and / or “example” is not necessarily to be construed as preferred or advantageous over other aspects. Likewise, the term “aspects of the disclosure” does not require that all aspects of the disclosure include the discussed feature, advantage or mode of operation.

[0024] Those of skill in the art will appreciate that the information and signals described below may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description below may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof, depending in part on the particular application, in part on the desired design, in part on the corresponding technology, etc.QC2503640WOQualcomm Ref. No. 2503640WO5 / 55

[0025] Further, many aspects are described in terms of sequences of actions to be performed by, for example, elements of a computing device. It will be recognized that various actions described herein can be performed by specific circuits (e.g., application specific integrated circuits (ASICs)), by program instructions being executed by one or more processors, or by a combination of both. Additionally, the sequence(s) of actions described herein can be considered to be embodied entirely within any form of non- transitory computer-readable storage medium having stored therein a corresponding set of computer instructions that, upon execution, would cause or instruct an associated processor of a device to perform the functionality described herein. Thus, the various aspects of the disclosure may be embodied in a number of different forms, all of which have been contemplated to be within the scope of the claimed subject matter. In addition, for each of the aspects described herein, the corresponding form of any such aspects may be described herein as, for example, “logic configured to” perform the described action.

[0026] As used herein, the terms “user equipment” (UE) and “base station” are not intended to be specific or otherwise limited to any particular radio access technology (RAT), unless otherwise noted. In general, a UE may be any wireless communication device (e.g., a mobile phone, router, tablet computer, laptop computer, consumer asset locating device, wearable (e.g., smartwatch, glasses, augmented reality (AR) / virtual reality (VR) headset, etc,), vehicle (e.g., automobile, motorcycle, bicycle, etc.), Internet of Things (ToT) device, etc.) used by a user to communicate over a wireless communications netw ork. A UE may be mobile or may (e.g., at certain times) be stationary, and may communicate with a radio access netw ork (RAN). As used herein, the term “UE” may be referred to interchangeably as an “access terminal” or “AT,” a “client device,” a “wireless device,” a “subscriber device,” a “subscriber terminal,” a “subscriber station,” a “user terminal” or “LIT,” a “mobile device,” a “mobile terminal,” a “mobile station,” or variations thereof. Generally, UEs can communicate with a core network via a RAN, and through the core network the UEs can be connected with external networks such as the Internet and with other UEs. Of course, other mechanisms of connecting to the core network and / or the Internet are also possible for the UEs, such as over wired access networks, wireless local area network (WLAN) networks (e.g,, based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 specification, etc.) and so on.QC2503640WOQualcomm Ref. No. 2503640WO6 / 55

[0027] Electronic shelf labels (ESLs) are an example of electronic label devices used by retailers for displaying product pricing or other product information to consumers. ESLs typically use electronic paper (e-paper) or liquid crystal display (LCD) to display the current information. E-paper (also referred to as e-ink) is widely used for ESLs, as it provides a sharp display and supports full graphic imaging while only needing power during updates and no power to retain an image.

[0028] ESLs are increasingly being integrated with existing retail technologies, such as electronic article surveillance, digital signage, and people counters. For example, retailers can upload a floor plan of the sales area into the ESL management software. Consumers can then be tracked (in real time) through a network of people-counting devices, or via their personal BLUETOOTH®) devices, in order to determine their position within the store at all times. Tins allows an individual customer to receive targeted, customized marketing initiatives, such as discounts, individual pricing, etc.

[0029] FIG. 1 illustrates an example ESL system 100, according to aspects of the disclosure. An ESL system generally includes three components: label management software (e.g., running on a central management entity 110, such as a local server at the retail location or a cloud-based server), one or more wireless communication access points 120 (e.g., Wi-Fi access points), one or more rail controllers 130, and one or more (usually many) ESLs 140, The label management software is responsible for the configuration of the system, configuration of the properties of the ESLs 140 themselves, and storing the database of information to be displayed by the ESLs 140. The software mainly covers the network management, file systems, and transmission of data. It also processes and packs the data to be displayed into packets of information. Tire data packets are then sent to one or more wireless communication access points 120 via a wireless network (e.g., Wi-Fi) for distribution to the ESLs 140 via the one or more rail controllers 130.

[0030] A wireless communication access point 120 is responsible for the stability and reliability of transmissions from the label management software (on the central management entity 110) to the ESLs 140. There may be multiple wireless communication access points 120 deployed in a single retail location based on the size of the space and / or the number of ESLs 140 deployed.

[0031] A wireless communication access point 120 communicates with one or more rail controllers 130 via a short-range wireless communications protocol, such asQC2503640WOQualcomm Ref. No. 2503640WO7 / 55BLUETOOTH® Low Energy (BLE), A rail controller 130 may therefore include a BLE radio (or other short-range wireless communications protocol radio). A rail controller 130 may be powered by a battery (e.g., a lithium-ion battery) or a wired connection. A rail controller 130 is coupled to, or integrated into, a rail to which multiple ESLs 140 can be “clipped” or otherwise attached. Once clipped to the rail, each ESL 140 has a wired connection to the rail controller 130 (e.g., via a three-wire bus for power, ground, and data).

[0032] An ESL 140 functions as a receiver from the wireless communication access point 120 (via the rail controller 130) to display the information configured from the label management software. The ESL 140 then acts based on the instructions that were provided in the data packets from the label management software. An ESL 140 includes a display and optionally a camera, ESLs 140 generally do not include batteries, as they are typically powered by the rail to which they are attached. In some cases, an ESL 140 may not have a short-range wireless communications radio (e.g., a BLE radio), as it receives data from the wireless communication access point 120 via the wired rail connection to the rail controller 130.

[0033] An ESL application programming interface (API) is included in the current BLUETOOTH® specification and permits a 7-bit group identifier of 8-bit unique ESL identifiers, allowing for a total of 32,640 ESLs 140 to be allocated for one wireless communication access point 120. With those constraints, multiple wireless communication access points 120 may be needed to cover a typical grocery store ESL application.

[0034] FIG. 2 illustrates example components of an example ESL 140, according to aspects of the disclosure. Note that in some cases, rather than an ESL 140 having its own wireless radio (e.g., a BLE radio) as shown in FIG. 2, multiple ESLs 140 may be attached (e.g., clipped) to a rail attached to a retail shelf. In this case, the rail (specifically a rail controller 130) contains the short-range wireless communications radio and the ESLs 140 have just the display. The radio controller 130 in the rail communicates locally to the clipped-on ESLs 140 over a wired protocol (the act of clipping on connects the ESLs 140 to the wires of the rail controller 130), As such, an ESL 140 itself may not have a radio but may connect locally to one (i.e., the rail controller 130).QC2503640WOQualcomm Ref. No. 2503640WO8 / 55

[0035] FIGS, 3A, 3B, and 3C illustrate several example components (represented by corresponding blocks) that may be incorporated into a UE 302 (which may correspond to any of the UEs described herein), a base station 304 (which may correspond to any of the base stations described herein), and a network entity 306 (which may correspond to or embody any of the network functions described herein, including the location server 230 and the LMF 270, or alternatively may be independent from the NG-RAN 220 and / or 5GC 210 / 260 infrastructure depicted in FIGS. 2 A and 2B, such as a private network) to support the operations described herein. It will be appreciated that these components may be implemented in different types of apparatuses in different implementations (e.g., in an ASIC, in a system-on-chip (SoC), etc.). The illustrated components may also be incorporated into other apparatuses in a communication system. For example, other apparatuses in a system may include components similar to those described to provide similar functionality. Also, a given apparatus may contain one or more of the components. For example, an apparatus may include multiple transceiver components that enable the apparatus to operate on multiple carriers and / or communicate via different technologies,

[0036] The UE 302 and the base station 304 each include one or more wireless wide area network (WWAN) transceivers 310 and 350, respectively, providing means for communicating (e.g., means for transmitting, means for receiving, means for measuring, means fortuning, means for refraining from transmitting, etc.) via one or more wireless communication networks (not shown), such as an NR network, an LTE network, a GSM network, and / or the like. The WWAN transceivers 310 and 350 may each be connected to one or more antennas 316 and 356, respectively, for communicating with other network nodes, such as other UEs, access points, base stations (e.g,, eNBs, gNBs), etc., via at least one designated RAT (e.g., NR, LTE, GSM, etc.) over a wireless communication medium of interest (e.g., some set of time / frequency resources in a particular frequency spectrum). Tire WWAN transceivers 310 and 350 may be variously configured for transmitting and encoding signals 318 and 358 (e.g., messages, indications, information, and so on), respectively, and, conversely, for receiving and decoding signals 318 and 358 (e.g., messages, indications, information, pilots, and so on), respectively, in accordance with the designated RAT, Specifically, the WWAN transceivers 310 and 350 include one or more transmitters 314 and 354, respectively, for transmitting and encoding signals 318QC2503640WOQualcomm Ref. No. 2503640WO9 / 55and 358, respectively, and one or more receivers 312 and 352, respectively, for receiving and decoding signals 318 and 358, respectively.

[0037] The UE 302 and the base station 304 each also include, at least in some cases, one or more short-range wireless transceivers 320 and 360, respectively. The short-range wireless transceivers 320 and 360 may be connected to one or more antennas 326 and 366, respectively, and provide means for communicating (e.g., means for transmitting, means for receiving, means for measuring, means for tuning, means for refraining from transmitting, etc.) with other network nodes, such as other UEs, access points, base stations, etc., via at least one designated RAT (e.g., Wi-Fi®, LTE Direct, BLUETOOTH®, ZIGBEE®, Z-WAVE®, PC5, dedicated short-range communications (DSRC), wireless access for vehicular environments (WAVE), near-field communication (NFC), ultra-wideband (UWB), etc.) over a wireless communication medium of interest. Tire short-range wireless transceivers 320 and 360 may be variously configured for transmitting and encoding signals 328 and 368 (e.g., messages, indications, information, and so on), respectively, and, conversely, for receiving and decoding signals 328 and 368 (e.g., messages, indications, information, pilots, and so on), respectively, in accordance with the designated RAT. Specifically, the short-range wireless transceivers 320 and 360 include one or more transmitters 324 and 364, respectively, for transmitting and encoding signals 328 and 368, respectively, and one or more receivers 322 and 362, respectively, for receiving and decoding signals 328 and 368, respectively. As specific examples, the short-range wireless transceivers 320 and 360 may be Wi-Fi® transceivers, BLUETOOTH® transceivers, ZIGBEE® and / or Z-WAVE® transceivers, NFC transceivers, UWB transceivers, or vehicle-to-vehicle (V2V) and / or vehicle-to- everything (V2X) transceivers.

[0038] The UE 302 and the base station 304 also include, at least in some cases, satellite signal interfaces 330 and 370, which each include one or more satellite signal receivers 332 and 372, respectively, and may optionally include one or more satellite signal transmitters 334 and 374, respectively, in some cases, the base station 304 may be a terrestrial base station that may communicate with space vehicles (e.g., space vehicles 112) via the satellite signal interface 370, In other cases, the base station 304 may be a space vehicle (or other non-terrestrial entity) that uses the satellite signal interface 370 to communicate with terrestrial networks and / or other space vehicles.QC2503640WOQualcomm Ref. No. 2503640WO10 / 55

[0039] The satellite signal receivers 332 and 372 may be connected to one or more antennas 336 and 376, respectively, and may provide means for receiving and / or measuring satellite positioning / communication signals 338 and 378, respectively. Where the satellite signal receiver(s) 332 and 372 are satellite positioning system receivers, the satellite positioning / communication signals 338 and 378 may be global positioning system (GPS) signals, global navigation satellite system (GLONASS) signals, Galileo signals, Beidou signals, Indian Regional Navigation Satellite System (NA VIC), Quasi-Zenith Satellite System (QZSS) signals, etc. Where the satellite signal receiver(s) 332 and 372 are nonterrestrial network (NTN) receivers, the satellite positioning / communication signals 338 and 378 may be communication signals (e.g., carrying control and / or user data) originating from a 5G network. The satellite signal receiver(s) 332 and 372 may comprise any suitable hardware and / or software for receiving and processing satellite positioning / communication signals 338 and 378, respectively. The satellite signal receiver(s) 332 and 372 may request information and operations as appropriate from the other systems, and, at least in some cases, perform calculations to determine locations of the UE 302 and the base station 304, respectively, using measurements obtained by any suitable satellite positioning system algorithm.

[0040] The optional satellite signal transmitter(s) 334 and 374, when present, may be connected to the one or more antennas 336 and 376, respectively, and may provide means for transmitting satellite positioning / communication signals 338 and 378, respectively. Where the satellite signal transmitter(s) 374 are satellite positioning system transmitters, the satellite positioning / communication signals 378 may be GPS signals, GLONASS® signals, Galileo signals, Beidou signals, NA VIC, QZSS signals, etc. Where the satellite signal transmitter(s) 334 and 374 are NTN transmitters, the satellite positioning / communication signals 338 and 378 may be communication signals (e.g., carry ing control and / or user data) originating from a 5G network. The satellite signal transmitter(s) 334 and 374 may comprise any suitable hardware and / or software for transmitting satellite positioning / communication signals 338 and 378, respectively. The satellite signal transmitter(s) 334 and 374 may request information and operations as appropriate from the other systems.

[0041] The base station 304 and the network entity 306 each include one or more network transceivers 380 and 390, respectively, providing means for communicating (e.g., meansQC2503640WOQualcomm Ref. No. 2503640WO11 / 55for transmitting, means for receiving, etc.) with other network entities (e.g., other base stations 304, other network entities 306). For example, the base station 304 may employ the one or more network transceivers 380 to communicate with other base stations 304 or network entities 306 over one or more wired or wireless backhaul links. As another example, the network entity 306 may employ the one or more network transceivers 390 to communicate with one or more base station 304 over one or more wired or wireless backhaul links, or with other network entities 306 over one or more wired or wireless core network interfaces,

[0042] A transceiver may be configured to communicate over a wired or wireless link. A transceiver (whether a wired transceiver or a wireless transceiver) includes transmitter circuitry (e.g., transmitters 314, 324, 354, 364) and receiver circuitry (e.g., receivers 312, 322, 352, 362). A transceiver may be an integrated device (e.g., embodying transmitter circuitry and receiver circuitry in a single device) in some implementations, may comprise separate transmitter circuitry and separate receiver circuitry in some implementations, or may be embodied in other ways in other implementations. The transmitter circuitry' and receiver circuitry of a wired transceiver (e.g., network transceivers 380 and 390 in some implementations) may be coupled to one or more wired network interface ports. Wireless transmitter circuitry (e.g., transmitters 314, 324, 354, 364) may include or be coupled to a plurality of antennas (e.g., antennas 316, 326, 356, 366), such as an antenna array, that permits the respective apparatus (e.g., UE 302, base station 304) to perform transmit “beamforming,” as described herein. Similarly, wireless receiver circuitry (e.g., receivers 312, 322, 352, 362) may include or be coupled to a plurality of antennas (e.g., antennas 316, 326, 356, 366), such as an antenna array, that permits the respective apparatus (e.g., UE 302, base station 304) to perform receive beamforming, as described herein. In an aspect, the transmitter circuitry and receiver circuitry may share the same plurality of antennas (e.g., antennas 316, 326, 356, 366), such that the respective apparatus can only receive or transmit at a given time, not both at the same time. A wireless transceiver (e.g., WWAN transceivers 310 and 350, short-range wireless transceivers 320 and 360) may also include a network listen module (NLM) or the like for performing various measurements.

[0043] As used herein, the various wireless transceivers (e.g., transceivers 310, 320, 350, and 360, and network transceivers 380 and 390 in some implementations) and wiredQC2503640WOQualcomm Ref. No. 2503640WO12 / 55transceivers (e.g., network transceivers 380 and 390 in some implementations) may generally be characterized as “a transceiver,” “at least one transceiver,” or “one or more transceivers.” As such, whether a particular transceiver is a wired or wireless transceiver may be inferred from the type of communication performed. For example, backhaul communication between network devices or servers will generally relate to signaling via a wired transceiver, whereas wireless communication between a UE (e.g., UE 302) and a base station (e.g., base station 304) will generally relate to signaling via a wireless transceiver,

[0044] The UE 302, the base station 304, and the network entity 306 also include other components that may be used in conjunction with the operations as disclosed herein. The UE 302, the base station 304, and the network entity 306 include one or more processors 342, 384, and 394, respectively, for providing functionality relating to, for example, wireless communication, and for providing other processing functionality. The processors 342, 384, and 394 may therefore provide means for processing, such as means for determining, means for calculating, means for receiving, means for transmitting, means for indicating, etc. In an aspect, the processors 342, 384, and 394 may include, for example, one or more general purpose processors, multi-core processors, central processing units (CPUs), ASICs, digital signal processors (DSPs), field programmable gate arrays (FPGAs), other programmable logic devices orprocessing circuitry’, or various combinations thereof.

[0045] The UE 302, the base station 304, and the network entity 306 include memory circuitry implementing memories 340, 386, and 396 (e.g., each including a memory’ device), respectively, for maintaining information (e.g., information indicative of reserved resources, thresholds, parameters, and so on). The memories 340, 386, and 396 may therefore provide means for storing, means for retrieving, means for maintaining, etc. In some cases, the UE 302, the base station 304, and the network entity 306 may include positioning component 348, 388, and 398, respectively. The positioning component 348, 388, and 398 may be hardware circuits that are part of or coupled to the processors 342, 384, and 394, respectively, and are configured to cause the UE 302, the base station 304, and the network entity 306 to perform the functionality described herein. In other aspects, the positioning component 348, 388, and 398 may be external to the processors 342, 384, and 394 (e.g., part of a modem processing system, integrated with another processingQC2503640WOQualcomm Ref. No. 2503640WO13 / 55system, etc,). Alternatively, the positioning component 348, 388, and 398 may be memory modules stored in the memories 340, 386, and 396, respectively, that, when executed by the processors 342, 384, and 394 (or a modem processing system, another processing system, etc.), cause the UE 302, the base station 304, and the network entity 306 to perform the functionality described herein. FIG. 3 A illustrates possible locations of the positioning component 348, which may be, for example, part of the one or more WWAN transceivers 310, the memory 340, the one or more processors 342, or any combination thereof, or may be a standalone component. FIG, 3B illustrates possible locations of the positioning component 388, which may be, for example, part of the one or more WWAN transceivers 350, the memory 386, the one or more processors 384, or any combination thereof, or may be a standalone component. FIG. 3C illustrates possible locations of the positioning component 398, which may be, for example, part of the one or more network transceivers 390, the memory 396, the one or more processors 394, or any combination thereof, or may be a standalone component.

[0046] The UE 302 may include one or more sensors 344 coupled to the one or more processors 342 to provide means for sensing or detecting movement and / or orientation information that is independent of motion data derived from signals received by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, and / or the satellite signal interface 330. By way of example, the sensor(s) 344 may include an accelerometer (e.g., a micro-electrical mechanical systems (MEMS) device), a gyroscope, a geomagnetic sensor (e.g., a compass), an altimeter (e.g., a barometric pressure altimeter), and / or any other type of movement detection sensor. Moreover, the sensor(s) 344 may include a plurality of different types of devices and combine their outputs in order to provide motion information. For example, the sensor(s) 344 may use a combination of a multi-axis accelerometer and orientation sensors to provide the ability to compute positions in two-dimensional (2D) and / or three-dimensional (3D) coordinate systems.

[0047] In addition, the UE 302 includes a user interface 346 providing means for providing indications (e.g., audible and / or visual indications) to a user and / or for receiving user input (e.g., upon user actuation of a sensing device such a keypad, a touch screen, a microphone, and so on). Although not shown, the base station 304 and the network entity 306 may also include user interfaces.QC2503640WOQualcomm Ref. No. 2503640WO14 / 55

[0048] Referring to the one or more processors 384 in more detail, in the downlink, IP packets from the network entity 306 may be provided to the processor 384. The one or more processors 384 may implement functionality for an RRC layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The one or more processors 384 may provide RRC layer functionality associated with broadcasting of system information (e.g., master information block (M1B), system information blocks (SIBs)), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-RAT mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression / decompression, security (ciphering, deciphering, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with the transfer of upper layer PDUs, error correction through automatic repeat request (ARQ), concatenation, segmentation, and reassembly of RLC service data units (SDUs), re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, scheduling information reporting, error correction, priority handling, and logical channel prioritization.

[0049] The transmitter 354 and the receiver 352 may implement Layer-1 (LI) functionality associated with various signal processing functions. Layer-1, which includes a physical (PHY) layer, may include error detection on the transport channels, forward error correction (FEC) coding / decoding of the transport channels, interleaving, rate matching, mapping onto physical channels, modulation / demodulation of physical channels, and MIMO antenna processing. The transmitter 354 handles mapping to signal constellations based on various modulation schemes (e.g., binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), M-phase-shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The coded and modulated symbols may then be split into parallel streams. Each stream may then be mapped to an orthogonal frequency division multiplexing (OFDM) subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and / or frequency domain, and then combined together using an inverse fast Fourier transform (IFFT) to produce a physical channel carrying a time domain OFDM symbol stream. The OFDM symbol stream is spatially precoded to produce multiple spatialQC2503640WOQualcomm Ref. No. 2503640WO15 / 55streams. Channel estimates from a channel estimator may be used to determine the coding and modulation scheme, as well as for spatial processing. The channel estimate may be derived from a reference signal and / or channel condition feedback transmitted by the UE 302. Each spatial stream may then be provided to one or more different antennas 356. The transmitter 354 may modulate an RF carrier with a respective spatial stream for transmission.

[0050] At the UE 302, the receiver 312 receives a signal through its respective antenna(s) 316.The receiver 312 recovers information modulated onto an RF carrier and provides the information to the one or more processors 342. The transmitter 314 and the receiver 312 implement Layer- 1 functionality associated with various signal processing functions. The receiver 312 may perform spatial processing on the information to recover any spatial streams destined for the UE 302, If multiple spatial streams are destined for the UE 302, they may be combined by the receiver 312 into a single OFDM symbol stream. The receiver 312 then converts the OFDM symbol stream from the time-domain to the frequency domain using a fast Fourier transform (FFT), The frequency domain signal comprises a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols on each subcarrier, and the reference signal, are recovered and demodulated by determining the most likely signal constellation points transmitted by the base station 304. These soft decisions may be based on channel estimates computed by a channel estimator. The soft decisions are then decoded and de-interleaved to recover the data and control signals that were originally transmitted by the base station 304 on the physical channel. The data and control signals are then provided to the one or more processors 342, which implements Layer-3 (L3) and Layer-2 (L2) functionality.

[0051] In the downlink, the one or more processors 342 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, and control signal processing to recover IP packets from the core network. The one or more processors 342 are also responsible for error detection.

[0052] Similar to the functionality described in connection with the downlink transmission by the base station 304, the one or more processors 342 provides RRC layer functionality associated with system information (e.g., MIB, SIBs) acquisition, RRC connections, and measurement reporting; PDCP layer functionality associated with header compression / decompression, and security (ciphering, deciphering, integrity protection,QC2503640WOQualcomm Ref. No. 2503640WO16 / 55integrity verification); RLC layer functionality associated with the transfer of upper layer PDUs. error correction through ARQ, concatenation, segmentation, and reassembly of RLC SDUs, re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through hybrid automatic repeat request (HARQ), priority handling, and logical channel prioritization.

[0053] Channel estimates derived by the channel estimator from a reference signal or feedback transmitted by the base station 304 may be used by the transmitter 314 to select the appropriate coding and modulation schemes, and to facilitate spatial processing. The spatial streams generated by the transmitter 314 may be provided to different antenna(s) 316, The transmitter 314 may modulate an RF carrier with a respective spatial stream for transmission.

[0054] The uplink transmission is processed at the base station 304 in a manner similar to that described in connection with the receiver function at the UE 302. The receiver 352 receives a signal through its respective antenna(s) 356. The receiver 352 recovers information modulated onto an RF carrier and provides the information to the one or more processors 384.

[0055] In the uplink, the one or more processors 384 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover IP packets from the UE 302. IP packets from the one or more processors 384 may be provided to the core network. The one or more processors 384 are also responsible for error detection.

[0056] For convenience, the UE 302, the base station 304, and / or the network entity 306 are shown in FIGS. 3A, 3B, and 3C as including various components that may be configured according to the various examples described herein. It will be appreciated, however, that the illustrated components may have different functionality in different designs. In particular, various components in FIGS. 3 A to 3C are optional in alternative configurations and the various aspects include configurations that may vary due to design choice, costs, use of the device, or other considerations. For example, in case of FIG. 3A, a particular implementation of UE 302 may omit the WWAN transceiver(s) 310 (e.g., a wearable device or tablet computer or personal computer (PC) or laptop may have Wi-QC2503640WOQualcomm Ref. No. 2503640WO17 / 55Fi® and / or BLUETOOTH® capability without cellular capability), or may omit the short- range wireless transceiver(s) 320 (e.g., cellular-only, etc.), or may omit the satellite signal interface 330, or may omit the sensor(s) 344, and so on. In another example, in case of FIG. 3B, a particular implementation of the base station 304 may omit the WWAN transceiver(s) 350 (e.g,, a Wi-Fi® “hotspot” access point without cellular capability), or may omit the short-range -wireless transceiver(s) 360 (e.g., cellular-only, etc.), or may omit the satellite signal interface 370, and so on. For brevity, illustration of the various alternative configurations is not provided herein, but would be readily understandable to one skilled in the art.

[0057] The various components of the UE 302, the base station 304, and the network entity 306 may be communicatively coupled to each other over data buses 308, 382, and 392, respectively. In an aspect, the data buses 308, 382, and 392 may form, or be part of, a communication interface of the UE 302, the base station 304, and the network entity 306, respectively. For example, where different logical entities are embodied in the same device (e.g., gNB and location server functionality incorporated into the same base station 304), the data buses 308, 382, and 392 may provide communication between them.

[0058] The components of FIGS. 3A, 3B, and 3C may be implemented in various ways. In some implementations, the components of FIGS. 3A, 3B, and 3C may be implemented in one or more circuits such as, for example, one or more processors and / or one or more ASICs (which may include one or more processors). Here, each circuit may use and / or incorporate at least one memory component for storing information or executable code used by the circuit to provide this functionality. For example, some or all of the functionality represented by blocks 310 to 346 may be implemented by processor and memory component(s) of the UE 302 (e.g., by execution of appropriate code and / or by appropriate configuration of processor components). Similarly, some or all of the functionality represented by blocks 350 to 388 may be implemented by processor and memory component(s) of the base station 304 (e.g., by execution of appropriate code and / or by appropriate configuration of processor components). Also, some or all of the functionality represented by blocks 390 to 398 may be implemented by processor and memory component(s) of the network entity 306 (e.g,, by execution of appropriate code and / or by appropriate configuration of processor components). For simplicity, various operations, acts, and / or functions are described herein as being performed “by a UE,” “byQC2503640WOQualcomm Ref. No. 2503640WO18 / 55a base station,” “by a network entity,” etc. However, as will be appreciated, such operations, acts, and / or functions may actually be performed by specific components or combinations of components of the UE 302, base station 304, network entity 306, etc., such as the processors 342, 384, 394, the transceivers 310, 320, 350, and 360, the memories 340, 386, and 396, the positioning component 348, 388, and 398, etc.

[0059] In some designs, the network entity 306 may be implemented as a core network component. In other designs, the network entity 306 may be distinct from a network operator or operation of the cellular network infrastructure (e.g,, NG RAN 220 and / or 5GC 210 / 260). For example, the network entity 306 may be a component of a private network that may be configured to communicate with the UE 302 via the base station 304 or independently from the base station 304 (e.g., over a non-cellular communication link, such as Wi-Fi®).

[0060] FIG. 4 is a diagram 400 illustrating an example ESL deployment scenario, according to aspects of the disclosure. Specifically, FIG. 4 illustrates a top view of a scenario where ESLs (e.g., ESLs 140) are deployed on both sides of two aisles of shelves in a retail establishment, warehouse, or the like. In the example of FIG. 4, groups of three ESLs are connected to a rail controller (e.g., a radio controller 130) and the rail controllers are spaced Im to 1.5m apart. However, as will be appreciated, this is merely an example configuration and there may be more or fewer ESLs per rail controller spaced closer or further apart.

[0061] In some cases, the ESLs may not be equipped with short-range wireless communications radios (e.g., BLE radios), and instead, the rail controller may include the short-range wireless communications radio for the three ESLs connected to it. In either case, the radio associated with an ESL (whether a component of the ESL of the rail controller to which the ESL is connected) may be referred to as an “ESL radio.”

[0062] Indoor positioning based on BLE beaconing from ESLs is being developed for retail and warehouse applications. In general, the location of a target device is determined based on signal strength measurements (e.g., received signal strength indicator (RSSI)) of beacon signals transmitted by one or more ESLs. Trilateration using RSSI has been observed to be highly unreliable, as the RSSI is very’ susceptible to attenuation, which in turn leads to poor range estimation accuracy. Instead, the weighted centroid algorithm is considered to be much more robust to attenuation and non-line-of-sight (NLOS) effects.QC2503640WOQualcomm Ref. No. 2503640WO19 / 55

[0063] Machine learning may be used to generate models that may be used to facilitate various aspects associated with processing of data. One specific application of machine learning relates to generation of measurement models for processing of reference signals for positioning (e.g., positioning reference signal (PRS)), such as feature extraction, reporting of reference signal measurements (e.g., selecting which extracted features to report), and so on.

[0064] Machine learning models are generally categorized as either supervised or unsupervised.A supervised model may further be sub-categorized as either a regression or classification model. Supervised learning involves learning a function that maps an input to an output based on example input-output pairs. For example, given a training dataset with two variables of age (input) and height (output), a supervised learning model could be generated to predict the height of a person based on their age. In regression models, the output is continuous. One example of a regression model is a linear regression, which simply attempts to find a line that best fits the data. Extensions of linear regression include multiple linear regression (e.g., finding a plane of best fit) and polynomial regression (e.g., finding a curve of best fit).

[0065] Another example of a machine learning model is a decision tree model. In a decision tree model, a tree structure is defined with a plurality of nodes. Decisions are used to move from a root node at the top of the decision tree to a leaf node at the bottom of the decision tree (i.e., a node with no further child nodes). Generally, a higher number of nodes in the decision tree model is correlated with higher decision accuracy.

[0066] Another example of a machine learning model is a decision forest. Random forests are an ensemble learning technique that builds off of decision trees. Random forests involve creating multiple decision trees using bootstrapped datasets of the original data and randomly selecting a subset of variables at each step of the decision tree. The model then selects the mode of all of the predictions of each decision tree. By relying on a “majority wins” model, the risk of error from an individual tree is reduced.

[0067] Another example of a machine learning model is a neural network (NN). A neural network is essentially a network of mathematical equations. Neural networks accept one or more input variables, and by going through a network of equations, result in one or more output variables. Put another way, a neural network takes in a vector of inputs and returns a vector of outputs.QC2503640WOQualcomm Ref. No. 2503640WO20 / 55

[0068] FIG. 5 illustrates an example neural network 500, according to aspects of the disclosure.The neural network 500 includes an input layer T that receives ‘n’ (one or more) inputs (illustrated as “Input 1,” “Input 2,” and “Input n”), one or more hidden layers (illustrated as hidden layers ‘hl,’ ‘h2,’ and ‘h3’) for processing the inputs from the input layer, and an output layer ‘o’ that provides ‘m’ (one or more) outputs (labeled “Output I” and “Output m”). Tire number of inputs ‘n,’ hidden layers ‘h,’ and outputs ‘m’ may be the same or different. In some designs, the hidden layers ‘h’ may include linear fiinction(s) and / or activation function(s) that the nodes (illustrated as circles) of each successive hidden layer process from the nodes of the previous hidden layer.

[0069] In classification models, the output is discrete. One example of a classification model is logistic regression. Logistic regression is similar to linear regression but is used to model the probability of a finite number of outcomes, typically two. In essence, a logistic equation is created in such a w'ay that the output values can only be between ‘0’ and ‘ 1.’ Another example of a classification model is a support vector machine. For example, for two classes of data, a support vector machine will find a hyperplane or a boundary between the two classes of data that maximizes the margin between the two classes. There are many planes that can separate the two classes, but only one plane can maximize the margin or distance between the classes. Another example of a classification model is Naive Bayes, which is based on Bayes Theorem. Other examples of classification models include decision tree, random forest, and neural network, similar to the examples described above except that the output is discrete rather than continuous.

[0070] Unlike supervised learning, unsupervised learning is used to draw inferences and find patterns from input data without references to labeled outcomes. Two examples of unsupervised learning models include clustering and dimensionality reduction.

[0071] Clustering is an unsupervised technique that involves the grouping, or clustering, of data points. Clustering is frequently used for customer segmentation, fraud detection, and document classification. Common clustering techniques include k-means clustering, hierarchical clustering, mean shift clustering, and density-based clustering. Dimensionality reduction is the process of reducing the number of random variables under consideration by obtaining a set of principal variables. In simpler terms, dimensionality reduction is the process of reducing the dimension of a feature set (in even simpler terms, reducing the number of features). Most dimensionality reductionQC2503640WOQualcomm Ref. No. 2503640WO21 / 55techniques can be categorized as either feature elimination or feature extraction. One example of dimensionality reduction is called principal component analysis (PCA). In the simplest sense, PCA involves project higher dimensional data (e.g., three dimensions) to a smaller space (e.g., two dimensions). This results in a lower dimension of data (e.g., two dimensions instead of three dimensions) while keeping all original variables in the model.

[0072] Regardless of which machine learning model is used, at a high-level, a machine learning module (e.g., implemented by a processing system) may be configured to iteratively analyze training input data (e.g., measurements of reference signals to / from various target UEs) and to associate this training input data with an output data set (e.g., a set of possible or likely candidate locations of the various target UEs), thereby enabling later determination of the same output data set when presented with similar input data (e.g., from other target UEs at the same or similar location).

[0073] Application services are a pool of services, such as load balancing, application performance monitoring, application acceleration, autoscaling, micro segmentation, service proxy, service discovery,, etc., needed to optimally deploy, run, and improve applications. Services and applications are both software programs, but they generally have differing traits. Broadly, sendees often target smaller and more isolated functions than applications, and applications often expose and call services, including services in other applications.

[0074] Web services are a type of application service that can be accessed via a web address for direct application-to-application interaction. Web services can be local, distributed, or web-based. Web services are built on top of open standards, such as TCP / IP, hypertext transfer protocol (HTTP), Java, hypertext markup language (HTML), and extensible markup language (XML), and therefore, web sendees are not tied to any one operating system or programming language. As such, software applications written in various programming languages and running on various platforms can use web services to exchange data over computer networks like the Internet in a manner similar to inter¬ process communication on a single computer. For example, a client can invoke a web service by sending an XML message to the web service and waiting for a corresponding XML response.QC2503640WOQualcomm Ref. No. 2503640WO22 / 55

[0075] An application programming interface (API) is an interface that facilitates interaction between different systems (e.g., hardware, firmware, and / or software entities or levels). More specifically, an API is a defined set of rules, commands, permissions, and / or protocols that allow one system to interact with, and access data from, another system. For example, an API may provide an interface for a higher level of software (e.g., an application, a web service, an application sendee, etc.) to access a lower level of software (e.g., a microsendee, the operating system, BIOS, firmware, device drivers, etc.) or a hardware component (e.g,, a universal serial bus (USB) controller, a memory controller, a transceiver, etc.). Since a 'eb senice exposes an application’s data and functionality, every web senice is effectively an API, but not every API is a web se ice.

[0076] One type of API for building microsenices applications is the representational state transfer API, also known as the “REST API” or the “RESTful API.” The REST API is a set of web API architecture principles, meaning that to be a REST API, the interface must adhere to certain architectural constraints. Tire REST API typically uses HTTP commands and secure sockets layer (SSL) encryption. It is language agnostic insofar as it can be used to connect applications and microsenices written in different programming languages. The commands common to the REST API include HTTP PUT, HTTP POST, HTTP DELETE, HTTP GET, and HTTP PATCH. Developers can use these REST API commands to perform actions on different “resources” within an application or senice, such as data in a database. REST APIs can use uniform resource locators (URLs) to locate and indicate the resource on which to perform an action.

[0077] Microsenices are individual small, autonomous, independent sendees and / or functions that together form a larger microsenices-based application. Within the application, each microsenice performs one defined function, such as authenticating users or retrieving a particular type of data. Hie goal of the microsenices, which are typically languageindependent, is to enable them to fit into any type of application and communicate or cooperate with each other to achieve the overall purpose of the larger microsenices-based application. When connecting microservices to create a microsenices-based application, APIs define the rules that prevent and permit the actions of and interactions between individual microsenices. For example, REST APIs may be used as the rules, commands, permissions, and / or protocols that integrate the individual microservices to function as a single application.QC2503640WOQualcomm Ref. No. 2503640WO23 / 55

[0078] Webhooks enable the interaction between web-based applications using custom callbacks. The use of webhooks allows web-based applications to automatically communicate with other web-based applications. Unlike traditional systems where one system (the “subject” system) continuously polls another system (the “observer” system) for certain data, webhooks allow the observer system to push the data to the subject system automatically whenever the event occurs. This reduces a significant load on the two systems, as calls are made between the two systems only when a designated event occurs.

[0079] Webhooks communicate via HTTP and rely on the presence of static URLs that point to APIs in the subject system that should be notified when an event occurs on the observer system. Thus, the subject system needs to designate one or more URLs that will accept event notifications from the observer system.

[0080] FIG. 6 is a diagram 600 illustrating example interaction between an application 610, an application service 620, an operating system (OS) 630, and hardware 640 using various APIs, according to aspects of the disclosure. In some aspects, the application 610, application service 620, operating system 630, and hardware 640 may be incorporated in the same device (e.g., a UE, a base station, etc.).

[0081] As shown in FIG. 6, the application sendee 620 (which may be a web service) comprises two microservices 622a and 622b (collectively microservices 622). As will be appreciated, however, the application sendee 620 may comprise more or fewer than two microservices 622. In some cases, the application 610 may access the individual microsendees 622 directly via their respective APIs 624a and 624b (collectively APIs 624). This is illustrated in FIG. 6 by application 610 invoking microservice 622b via API 624b. Alternatively, the application 610 may invoke the application sendee 620 via an API 624c for the application sendee 620. The application service 620 can then invoke the appropriate microservice(s) 622 via the respective APIs 624. This is illustrated in FIG. 6 by tire application service 620 invoking microsendee 622a via API 624a on behalf of the application 610.

[0082] If invoked by the application 610, the microsen ices 622 can respond to the application 610 via the application’s 610 callback 612, Alternatively, if invoked by the application senice 620, the microsenice 622 can respond to the application senice 620 via the application service’s 620 callback 626c. In either case, the client (either the applicationQC2503640WOQualcomm Ref. No. 2503640WO24 / 55610 or the application service 620) may invoke the microservice(s) 622 by sending, for example, an XML message to the microservice 622 via the respective API 624, and the microservice 622 may respond to the client by sending a corresponding XML response to the callback 612.

[0083] Hie microsendees 622 may access various subsystems within the operating system 630 via the subsystems’ respective APIs. In the example of FIG. 6, the operating system 630 includes a location subsystem 632a and a communications subsystem 632b (collectively subsystems 632), Tire location subsystem 632a may comprise software and / or firmware for determining the location of a mobile device (e.g., a UE). The mobile device being located may be the device that includes the operating system 630 (e.g., a UE calculating its own location, as in the case of UE-based positioning) or another device that does not include the operating system 630 (e.g., where a location server estimates a UE’s location). Tire communications subsystem 632b may similarly comprise software and / or firmware for enabling wireless communications by the device including the operating system 630. For example, the communications subsystem 632b may implement lower layer communication functionality (e.g., MAC layer functionality', RRC layer functionality, etc.).

[0084] The subsystems 632 each expose respective APIs 634a and 634b (collectively APIs 634) to the higher architecture levels. The microservices 622 may invoke the subsystems 632 via their respective APIs 634, and the subsystems 632 may respond to the microservices 622 via the microservices’ 622 callbacks 626a and 626b (collectively callbacks 626). In the example of FIG. 6, the microservice 622a invokes tire location subsystem 632a and the microservice 622b invokes the communications subsystem 632b within the operating system 630. As such, microservice 622a may be a location -related microservice and microservice 622b may be a communications-related microservice. However, as will be appreciated, either microservice 622 may invoke either subsystem 632 via its respective API 634.

[0085] In the example of FIG. 6, the hardware 640 includes a satellite signal receiver 642a, one or more WWAN transceivers 642b, and one or more short-range wireless transceivers 642c (collectively' hardware components 642). The satellite signal receiver 642a may' correspond to, for example, satellite signal receiver 330 or 370 in FIGS. 3A and 3B. The one or more WWAN transceivers 642b may correspond to, for example, the one or moreQC2503640WOQualcomm Ref. No. 2503640WO25 / 55WWAN transceivers 310 or 350 in FIGS, 3A and 3B, The one or more short-range wireless transceivers 642c may correspond to, for example, the one or more short-range wireless transceivers 320 or 360 in FIGS. 3A and 3B.[0086j In the example of FIG. 6, the location subsystem 632a may send commands (e.g., requests for measurements of reference signals, requests to transmit reference signals, etc.) to the satellite signal receiver 642a, the one or more WWAN transceivers 642b, and / or the one or more short-range wireless transceivers 642c via their APIs 644a, 644b, and 644c, respectively. The satellite signal receiver 642a, the one or more WWAN transceivers 642b, and / or the one or more short-range wireless transceivers 642c may send responses (e.g., measurements of reference signals, acknowledgments, etc.) to the commands to the location subsystem 632a via callback 636a. Similarly, the communications subsystem 632b may send information to be transmitted wirelessly (e.g., user data, measurement reports, etc.) to the one or more WWAN transceivers 642b and / or the one or more short- range wireless transceivers 642c via their APIs 644b and 644c, respectively. The one or more WWAN transceivers 642b and / or the one or more short-range wireless transceivers 642c may send information received wirelessly (e.g., user data, location requests, positioning assistance data, etc.) to the communications subsystem 632b via callback 636b.

[0087] As a specific positioning example in the context of FIG, 6, the device incorporating the illustrated architecture may be a mobile device, and the application 610 may be an application that uses the location of the mobile device (e.g., a UE), such as a navigation application (e.g., running locally on the mobile device). The application 610 therefore invokes application service 620 (via API 624c), which invokes microservice 622a (via API 624a), or invokes microservice 622a directly (via API 624a). Tire command from the application 610 indicates that the application 610 is requesting the location of the mobile device, and may include (or additional commands may include) other information related to the requested location fix, such as the requested quality of sendee (QoS) (e.g., accuracy and latency).

[0088] Based on the QoS of the location request, the known capabilities of the mobile device (e.g., available positioning technologies, such as satellite-based, NR-based, Wi-Fi-based, etc.), the available reference signal configurations (e.g., from nearby base stations), and the like, the microservice 622a calls the location subsystem 632a (via API 634a). NoteQC2503640WOQualcomm Ref. No. 2503640WO26 / 55that the microservice 622a may coordinate with other microservices, other application services, other applications, and the like to obtain the information necessary to locate the mobile device. For example, the microservice 622a may need to access another microservice associated with one or more base stations the mobile device is expected to measure in order to perform an NR-based positioning procedure.

[0089] The microservice 622a may select the positioning technology to use to obtain the location of the mobile device based on the known capabilities of the mobile device and the requested QoS. For example, using the satellite signal receiver 642a may provide high accuracy and low latency but it may be turned off. As another example, using the one or more WWAN transceivers 642b may provide low latency, but if the mobile device is indoors, the accuracy may be poor. Based on the selected positioning technology, the microservice 622a sends one or more commands to the location subsystem 632a requesting the location subsystem 632a to invoke the satellite signal receiver 642a, the one or more WWAN transceivers 642b, or the one or more short-range wireless transceivers 642c, Also depending on the type of positioning technology selected, the microservice 622a may provide commands regarding which reference signals to measure, which reference signals to transmit, and the like. In addition, the microservice 622a may indicate the accuracy and latency needed for the positioning measurements.

[0090] Based on the commands from the microservice 622a, the location subsystem 632a invokes the appropriate hardware component(s) (via one or more of APIs 644). For example, if the positioning technology is NR-based, the location subsystem 632a may transmit commands to the one or more WWAN transceivers 642b to measure and / or transmit certain reference signals at certain times and on certain frequencies. In addition, based on the requested accuracy and latency, the location subsystem 632a may increase or decrease the amount of power and / or processing resources allocated to the one or more WWAN transceivers 642b. For example, for a higher accuracy requirement, the location subsystem 632a may dedicate more power and / or processing resources to the one or more WWAN transceivers 642b.

[0091] The location subsystem 632a receives (via callback 636a) positioning measurements (e.g., reception times, transmission times, signal strengths, etc.) from the one or more WWAN transceivers 642b and passes them to the microservice 622a (via callback 626a). The microservice 622a can then calculate the location of the mobile device based on theQC2503640WOQualcomm Ref. No. 2503640WO27 / 55measurements and any other available information (e.g., the location(s) of the base station(s) transmitting the measured reference signals). The microservice 622a provides the calculated location of the mobile device to the application 610 via callback 612 or via application service 620 (depending on which entity invoked the microservice 622a).

[0092] In certain aspects, the application 610 may provide credentials or other authorization to the microsendee 622a indicating that the application 610 is permitted to access the location of the mobile device. Alternatively, upon receiving the request from the application 610, the microservice 622a may determine whether the application 610 is authorized. This check may be performed via another microservice, for example, or by invoking the operating system 630 to determine whether the application 610 has permission to access the mobile device’s location. Similarly, the microservice 622a may need to provide credentials or other authorization to the operating system 630 to indicate that tire microservice 622a is permitted to access the location of the mobile device. Alternatively, upon receiving the request from the microservice 622a, the operating system 630 may determine whether the microsendee 622a is authorized.

[0093] In certain aspects, the application 610 may use a webhook to obtain the location of the mobile device, in that way, the application 610 will be informed whenever the mobile device moves from one location to another. In this case, tire observer system would be the microservice 622a and the subject system would be the application 610. Instead of the application 610 having to periodically call the microservice 622a to check whether the mobile device’s location has changed, a webhook created in the application 610 w ould allow the microservice 622a to push any change in the mobile device’s location to the application 610 automatically through a registered URL. The microservice 622a may periodically perform positioning operations to determine the location of the mobile device in order to report changes to the application 610.

[0094] Similarly, the microservice 622a may use a webhook to obtain changes in the location of the mobile device. In this case, how'ever, because the microservice 622a coordinates location determinations for certain types of positioning technologies (e.g., NR-based, Wi-Fi-based), the webhook may only apply to certain other types of positioning technologies (e.g., satellite-based, sensor-based). For example, if the location subsystem 632a coordinates satellite -based positioning via the satellite signal receiver 642a, it can report any detected change in location to the microservice 622a via the w ebhook.QC2503640WOQualcomm Ref. No. 2503640WO28 / 55

[0095] In some cases, the application 610, the application service 620, the operating system 630, and the hardware 640 may be distributed across multiple devices (e.g., a UE, a web server, a location server, etc.). For example, the application 610 may be running on a location server, the application sendee 620 may be running on a web server, and the operating system 630 and hardware 640 may be incorporated in a UE (e.g., UE 204).

[0096] In some aspects, predictive and / or generative artificial intelligence (Al), machine learning (ML) and / or large language models (LLMs), combined with the implementation of various location-based technologies such as ESLs, Wi-Fi devices, RF sensors and / or cameras at retail stores, may provide the technological framework for advanced interactions between retailers and customers beyond conventional sales techniques (e.g., offering discounts, coupons, etc., without regard to the needs or preferences of individual customers).

[0097] In retail environments that are Al-driven, customer-centric, and equipped with industrial loT (IIoT) devices, merchants (e.g., physical store retailers, online retailers and / or brand name companies) may interact in a competitive or cooperative manner for the attention of current or potential customers directly and in real time. In some aspects, direct interactions with customers may occur through social media via online marketing and e- commerce, and customer engagement by physical store retailers and brand name companies may be achieved by using customer data including, for example, shopping histories, preferences, locations and traveling patterns of customers in retail stores or membership warehouses.

[0098] In some aspects, retailers or brand name companies may notify a customer of an offer for sale or bargaining based on Al agent-assisted customer-site interactions. In some aspects, the customer-site interactions may include obtaining customer-specific information with the aid of location-based technologies at a retail site, including, for example, ESLs, WiFi devices, cameras (e.g., closed circuit televisions (CCTVs)), and / or RF sensors.

[0099] In some aspects, the customer-site interactions may be one-to-one interactions where an Al Agent enables direct interactions between a customer and a site (e.g., a retailer, supplier or brand). In some aspects, the customer-site interactions may be one-to-many interactions where an Al agent enables interactions between a customer and multiple sites (e.g., multiple retail stores, suppliers, and / or brands). In some aspects, the customer-site interactions may be many-to-many interactions w'here a distributed system ofQC2503640WOQualcomm Ref. No. 2503640WO29 / 55interconnected Al agents enable interactions between multiple customers and multiple sites.[0100 J FIG. 7 illustrates an example of a system architecture for Al agent-based customer-site interactions, according to aspects of the disclosure. In the example illustrated in FIG. 7, a plurality of customers (denoted as ‘" Customer 1,” “Customer 2,”.., “Customer K”) may interact with customer-centric Al agents 702, 704 and 706, which may in turn interact with one or more brands 708 and / or one or more stores 710 for potential offers for sales or bargaining. In some implementations, each customer may interact with a single store or brand via a customer-centric Al agent in a one-to-one interaction. For example, Customer 1 may interact with one of the brands 708 or one of the stores 710 via Al agent 702. In some implementations, a customer may interact with multiple stores or multiple brands via a customer-centric Al agent in one-to-many interactions. For example, Customer 1 may interact with multiple brands 708 or multiple stores 710 via Al agent 702.

[0101] In some implementations, multiple customers may interact with multiple stores or multiple brands via multiple Al agents in many-to-many interactions. For example, Customer 1, Customer 2 and Customer K may interact with multiple brands 708 or multiple stores 710 via Al agents 702, 704 and 706, respectively. In some aspects, the Al agents 702, 704 and 706 may interact cooperatively or competitively with each other to provide customized offers for multiple customers. In some aspects, each of the Al agents is a customer-centric model that may reside on a customer device (e.g., a UE), on a dedicated server, on a server that is part of a network, or on a cloud (e.g., through a third- party provider). In some aspects, each Al agent may be tailored to a specific customer regardless of where it resides physically.

[0102] In some aspects, each Al agent is an AI / ML model or an LLM that is tailored to a specific customer. In some aspects, each Al agent may be trained by customer-specific data and may use information supplied directly by the customer as well as customer-specific information supplied by one or more physical retail stores, one or more online retail sites, and / or one or more brand name companies. In some aspects, at least some of the customer-specific information may be obtained from social media interactions of the customer.QC2503640WOQualcomm Ref. No. 2503640WO30 / 55

[0103] In some implementations, the Al agent may be a large core model which may be further fine-tuned or tailored to a specific customer using customer-specific information. In some aspects, the types of customer-specific information available to the Al agent may include the shopping history of the customer, shopping trajectories of the customer in one or more retail stores, which may be available or obtained through store tracking systems, customer preferences for certain products or classes of products, online shopping activities, social media engagements, or the like.

[0104] In some aspects, at least some of the customer-specific information may be obtained from one or more site positioning systems (e.g., Wi-Fi, ESL, etc.) and / or monitoring systems (e.g., CCTV cameras). In some aspects, product inventory or supply status may be provided by a store control center or by store employees in real time. For example, the status of product availability on various shelves in a given store may be provided by various components of an ESL system (e.g., ESL weight sensors, barcode readers, shelf cameras, etc.). In some aspects, the locations and / or trajectories of customers in a given store may be tracked by various components of an ESL system, Wi-Fi devices, CCTV cameras, RF sensors, or the like.

[0105] In some aspects, site or store-based constraints, such as the minimum price for a given item, target sales volume, and / or desired outcome (e.g. the goal of selling out products that are close to expiration dates), may be provided as part of the considerations for offering a sale or discount to the customer. In some aspects, customer-based considerations, such as preferred or desired items for the current shopping session, may be manually provided by the customer in real time through an application on the UE, or automatically predicted for the customer based on past customer behavior (e.g., shopping history, pattern of past purchases, etc.) as well as product supply status at a site or store of interest.

[0106] In some aspects, customer-centric Al agents may be deployed in various manners. In some implementations, customer-centric Al agents may be centrally deployed. For example, the customer-centric Al agent may reside on a dedicated server or a cloud service and the customer may access it through an interface, such as a dedicated application on the UE of the customer. In some aspects, centralized deployment of customer-centric Al agents may be provided by store, site or brand-owned or operated Al services. In some aspects, centralized deployment of customer-centric Al agents may beQC2503640WOQualcomm Ref. No. 2503640WO31 / 55realized by using Al cloud services of a third-party entity' that offers large Al model training services.

[0107] In some aspects, decentralized deployment of customer-centric Al agents may be suitable for certain use cases. For example, in some scenarios, it may be desirable for a customercentric Al agent to reside locally on the UE of the customer for privacy or other reasons. In some scenarios, centralized Al services may not be available or feasible. In some aspects, the Al agent may be deployed as well as trained locally on the UE of the customer.

[0108] In some implementations, decentralized deployment of a customer-centric Al agent on the UE of an individual customer may be achieved in combination with centralized deployment of one or more generic Al models at a server or cloud service. In some aspects, a compressed version of one or more generic Al models may be downloaded and further updated or fine-tuned on the UE of the customer.

[0109] in some implementations, an Al agent may be provided by a third-party service provider in cooperation with retail or brand name companies in various forms of partnership. In some aspects, the Al agent provided by the third-party service provider may become a personal Al assistant and may be integrated as part of a broader personalized Al framework designed to assist customers in purchasing decisions.

[0110] In some scenarios, a customer may interact with a specific store through an Al agent. For example, when a customer is in a store and carries a UE which has a unique identifier (ID) and is connected to a wireless system at the store (e.g., ESL, BLUETOOTH®, Wi-Fi, etc.), the customer-specific Al agent may enable one or more interactions related to the purchase of one or more items at that store.

[0111] For example, the store may offer the customer a special deal on a certain product based on the current location of the customer and his or her preferred items or shopping history'. The offer may be displayed on an application of the UE, or on an ESL display in proximity’ to the current location of the cus tomer. In some aspects, the customer may enter a request for a specific item with further requirements or preferences (e.g., the maximum acceptable price, the minimum amount of time before the expiration date, etc.). In some aspects, the customer may enter such requirements or preferences on the application of the UE or on the touchscreen display of an ESL, for example.QC2503640WOQualcomm Ref. No. 2503640WO32 / 55

[0112] In some scenarios, the store may initiate a bargaining session with the customer instead of offering a direct discount or incentive on a product. For example, the store may offer a discount to the customer on an item with a condition that benefits the store. In an example scenario, the customer may go to a specific location and send RF measurement reports to the store to help the store with mapping, by voluntarily giving up some privacy rights in exchange for a discount.

[0113] in some aspects, the customer-specific Al agent may facilitate interactions between a customer and multiple entities. At a given retail store or site, multiple brands of the same type of items or products may be available. In some aspects, depending on the location and inferred intent of the customer as well as predicted customer behavior, the Al agent may initiate a competition between different brands, thereby giving the customer an opportunity to receive competing offers for the same type of products.

[0114] In some aspects, the Al agent may oversee a competitive offering or bidding process among multiple brands. In some aspects, the Al agent may engage with the customer directly or indirectly. For example, the Al agent may engage with the customer directly in a competitive offering or bidding process by allowing the customer to accept one offer and reject others. The Al agent may also engage with the customer indirectly by inferring the intent of the customer and interact with the merchants accordingly. In one example scenario, a long dwell time at a certain location in the store may indicate indecisiveness on the part of the customer, and the Al agent may notify the competing brands to provide updated offers.

[0115] In some aspects, the Al agent may facilitate customer interactions with multiple sites or stores through an application on the UE of the customer. For example, the customer may be in one of the stores in a plaza or shopping mall with multiple similar stores that sell the same or similar products, The customer may be showing interest in a certain product at one store and this interest may be detected by the Al agent. The Al agent may notify other nearby stores about potential interest from the customer in the same or similar product. One or more stores nearby may offer a better deal to the customer for the same or similar product.

[0116] In some scenarios, the customer may engage in direct bargaining with one or more additional stores for a better price due to additional walking or driving required to reach another store. In some scenarios, the Al agent may engage in interactions withQC2503640WOQualcomm Ref. No. 2503640WO33 / 55geographically distant stores if the customer has indicated a willingness to travel in order to obtain a better discount.

[0117] In some aspects, customer-centric Al agents may facilitate interactions between multiple customers and multiple sites or stores. In some aspects, interactions between multiple customers via their respective Al agents may be either competitive (e.g,, in auctions) or cooperative (e.g., friends, relatives or members of the same family at different locations seeking the same product).

[0118] In some scenarios, competitive interactions between Al agents of multiple customers may occur at the same location (e.g., based on ESL-detected proximity) when they are seeking to purchase the same products with a limited supply. Upon receiving an indication that multiple customers are seeking the same items with a limited supply, the site may initiate an auction for these items. In some aspects, the customers may interact with their respective Al agents via applications on their UEs or via ESL displays and place their offers for these items. In some aspects, the Al agents of these customers may interact with the site in a star topology in a competitive bidding process.

[0119] In some scenarios, cooperative interactions may occur between Al agents of multiple customers. For example, members of a household (e.g., spouses), roommates, friends or relatives may have Al agents coupled to one another if they are seeking to purchase certain products as a group. When one customer is at home and the other customer is at a store, the Al agent at the store may interact with the store and receive an indication that a certain product is on sale. In this scenario, the Al agent at the store may then interact with the Al agent at home and notify the other customer of the opportunity to purchase. The customer at home may then interact with the customer at the store to negotiate the acquisition of that product.

[0120] In some aspects, the customer-centric Al agent for a given customer may be triggered upon the occurrence of one or more conditions. For example, the Al agent may be triggered to interact with a merchant (or an Al agent of another customer) only when a special interface is being used (e.g., an application on the UE of the customer or on an ESL display). In some scenarios, the triggering of the Al agent may be locationdependent (e.g., when the UE earned by the customer is approaching a store or is inside a store). In some scenarios, the Al agent may be triggered upon one or more user- specified conditions. For example, the Al agent may be triggered when a store has aQC2503640WOQualcomm Ref. No. 2503640WO34 / 55general sale, when the price of an item drops below a certain price point, when certain special offers are available, or the like. In some scenarios, the Al agent for one customer may be triggered when a cooperative Al agent for another customer initiates one or more interactions.

[0121] FIG. 8 illustrates an example method 800 of positioning, according to aspects of the disclosure. In some aspects, method 800 may be performed by a device (e.g., any of the UEs 302, base stations 304, or network entities 306 described herein).

[0122] At operation 810, the device may obtain, via an artificial intelligence (Al) agent, customer-specific information associated with a customer.

[0123] In some aspects, where the device is a UE, operation 810 may be performed by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, the one or more processors 332, memory’ 340, and / or positioning component 342, any or all of which may be considered means for performing this operation.

[0124] in some aspects, where the device is a base station or base station component (e.g., as a wireless communications access point), operation 810 may be performed by the one or more WWAN transceivers 350, the one or more short-range wireless transceivers 360, the one or more network transceivers 380, the one or more processors 384, memory 386, and / or positioning component 388, any or all of which may be considered means for performing this operation.

[0125] In some aspects, where the device is a network entity (e.g., a central management entity, an edge server, an over-the-top (OTT) server, a cloud, etc.), operation 810 may be performed the one or more network transceivers 390, the one or more processors 394, memory 396, and / or positioning component 398, any or all of which may be considered means for performing this operation.

[0126] At operation 820, the device may determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information.

[0127] In some aspects, where the device is a UE, operation 820 may be performed by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, the one or more processors 332, memory 340, and / or positioning component 342, any or all of which may be considered means for performing this operation.QC2503640WOQualcomm Ref. No. 2503640WO35 / 55

[0128] In some aspects, where the device is a base station or base station component (e.g,, as a wireless communications access point), operation 820 may be performed by the one or more WWAN transceivers 350, the one or more short-range wireless transceivers 360, the one or more network transceivers 380, the one or more processors 384, memory' 386, and / or positioning component 388, any or all of which may be considered means for performing this operation.

[0129] in some aspects, where the device is a network entity (e.g., a central management entity, an edge server, an over-the-top (OTT) server, a cloud, etc.), operation 820 may be performed the one or more network transceivers 390, the one or more processors 394, memory' 396, and / or positioning component 398, any or all of which may be considered means for performing this operation.

[0130] At operation 830, the device may obtain a notification for the customer, the notification including the offer associated with one or more items for sale to the customer.

[0131] in some aspects, where the device is a UE, operation 830 may be performed by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, the one or more processors 332, memory 340, and / or positioning component 342, any or all of which may be considered means for performing this operation.

[0132] In some aspects, where the device is a base station or base station component (e.g., as a wireless communications access point), operation 830 may be performed by the one or more WWAN transceivers 350, the one or more short-range wireless transceivers 360, the one or more network transceivers 380, the one or more processors 384, memory 386, and / or positioning component 388, any' or all of which may' be considered means for performing this operation,

[0133] In some aspects, where the device is a network entity (e.g., a central management entity, an edge server, an over-the-top (OTT) server, a cloud, etc.), operation 830 may be performed the one or more network transceivers 390, the one or more processors 394, memory 396, and / or positioning component 398, any or all of which may be considered means for performing this operation.

[0134] Method 800 may include additional implementations, such as any single implementation or any combination of implementations described below' and / or in connection with one or more other processes described elsewhere herein.

[0135] In some aspects, the device is a user equipment (UE), a server, or a cloud.QC2503640WOQualcomm Ref. No. 2503640WO36 / 55

[0136] In some aspects, the Al agent is an artificial intelligence / machine learning (AI / ML) model tailored to the customer, or a large language model (LLM) tailored to the customer.

[0137] In some aspects, the customer-specific shopping model is further based at least in part on inventory status of the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, one or more constraints on the one or more items at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, preferring sales outcomes at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, or any combination thereof.

[0138] In some aspects, method 800 includes obtaining, from a user equipment (UE) of the customer, one or more preferred or desired items for a current shopping session.

[0139] In some aspects, method 800 includes predicting, via the Al agent, one or more items preferred or desired to be purchased for a current shopping session based on the customerspecific shopping model.

[0140] In some aspects, the notification is transmitted to the customer via a user equipment (UE), an electronic shelf label (ESL), or both.

[0141] In some aspects, the offer associated with one or more items for sale to the customer is an offer of bargaining to the customer.

[0142] In some aspects, the offer of bargaining is initiated by a retailer based on one or more measurements of a location of the customer.

[0143] In some aspects, method 800 includes determining, via the Al agent, a plurality retailers, a plurality of sites, a plurality of brands, or any combination thereof, to obtain a plurality of offers of competing items for sale to the customer based at least in part on the customerspecific shopping model.

[0144] In some aspects, method 800 includes communicating, via the Al agent, with the customer the plurality of offers of competing items, and recommending, via the Al agent, a recommendation of one or more items among the competing items for purchase.

[0145] In some aspects, method 800 includes recommending, via the Al agent, one or more locations other than a current location of the customer for purchasing one or more recommended items among the competing items for purchase.

[0146] In some aspects, method 800 includes obtaining, via the Al agent, a plural ity of customerspecific shopping models of a plurality of customers based at least in part on customer¬ specific information of the plurality of customers, determining, via the Al agent, the oneQC2503640WOQualcomm Ref. No. 2503640WO37 / 55or more retailers, the one or more sites, the one or more brands, or any combination thereof, to obtain at least one offer associated with one or more items for sale to at least one customer of the plurality of customers based at least in part on the plurality of customer-specific shopping models, and transmitting at least one notification for the at least one customer, the at least one notification including the least one offer associated with the one or more items for sale.

[0147] in some aspects, method 800 includes determining, via the Al agent, the plurality of customers competing for the one or more items, determining, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items, or determining, via the Al agent, the plurality of customers for auctioning of the one or more items.

[0148] Although FIG. 8 shows example blocks of method 800, in some implementations, method 800 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in FIG. 8. Additionally, or alternatively, two or more of the blocks of method 800 may be performed in parallel, or performed in a different sequence from the sequence listed in FIG. 8.

[0149] As will be appreciated, a technical advantage of the method 800 is that, by using a customer-centric Al agent for customer-site interactions, the described techniques may be used to facilitate sales by allowing merchants to offer discounts or other incentives tailored to the predicted needs or preferences of the customer.

[0150] in the detailed description above it can be seen that different features are grouped together in examples. This manner of disclosure should not be understood as an intention that the example clauses have more features than are explicitly mentioned in each clause. Rather, the various aspects of the disclosure may include fewer than all features of an individual example clause disclosed. Therefore, the following clauses should hereby be deemed to be incorporated in the description, wherein each clause by itself can stand as a separate example. Although each dependent clause can refer in the clauses to a specific combination with one of the other clauses, the aspect(s) of that dependent clause are not limited to the specific combination. It will be appreciated that other example clauses can also include a combination of the dependent clause aspect(s) with the subject matter of any other dependent clause or independent clause or a combination of any feature with other dependent and independent clauses. The various aspects disclosed herein expresslyQC2503640WOQualcomm Ref. No. 2503640WO38 / 55include these combinations, unless it is explicitly expressed or can be readily inferred that a specific combination is not intended (e.g., contradictory' aspects, such as defining an element as both an electrical insulator and an electrical conductor). Furthermore, it is also intended that aspects of a clause can be included in any other independent clause, even if the clause is not directly dependent on the independent clause.

[0151] Implementation examples are described in the following numbered clauses:

[0152] Clause 1: A method of positioning performed by a device, comprising: obtaining, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; determining, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and obtaining a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0153] Clause 2: The method of clause 1, wherein the device is: a user equipment (UE); a server;or a cloud.

[0154] Clause 3: The method of any of clauses 1 to 2, wherein the Al agent is: an artificial intelligence / machine learning (AI / ML) model tailored to the customer; a large language model (LLM) tailored to the customer; or a visual LLM tailored to tire customer.

[0155] Clause 4: The method of any of clauses 1 to 3, wherein the customer-specific information includes: one or more preferred items indicated by the customer; a shopping history of the customer; one or more shopping locations of the customer; one or more shopping trajectories of the customer; one or more social media engagements of the customer; or any combination thereof.

[0156] Clause 5: The method of any of clauses 1 to 4, wherein the customer-specific information is further based at least in part on: inventory status of the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; one or more constraints on the one or more items at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; preferred sales outcomes at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; or any combination thereof.QC2503640WOQualcomm Ref. No. 2503640WO39 / 55

[0157] Clause 6: The method of any of clauses 1 to 5, further comprising: obtaining, from a user equipment (UE) of the customer, one or more preferred or desired items for a current shopping session.

[0158] Clause 7: The method of any of clauses 1 to 6, further comprising: predicting, via the Al agent, one or more items preferred or desired to be purchased for a current shopping session based on the customer-specific information.

[0159] Clause 8: The method of any of clauses 1 to 7, wherein the notification is transmitted to the customer via a user equipment (UE), an electronic label device, or both.

[0160] Clause 9: The device of any of clauses 1 to 8, wherein the information associated with one or more items for sale to the customer includes: an offer for sale of the one or more items to the customer; product information associated with the one or more items; or any combination thereof.

[0161] Clause 10: The method of any of clauses 1 to 9, wherein the information associated with one or more items for sale to the customer is an offer of bargaining to the customer.

[0162] Clause 11: The method of any of clauses 1 to 10, wherein the offer of bargaining is initiated by a retailer based on one or more measurements of a location of the customer.

[0163] Clause 12: The method of any of clauses 1 to 11, further comprising: determining, via the Al agent, a plurality retailers, a plurality of sites, a plurality of brands, or any combination thereof, to obtain a plurality of offers of competing items for sale to the customer based at least in part on the customer-specific information.

[0164] Clause 13: The method of any of clauses 1 to 12, further comprising: communicating, via the Al agent, with the customer the plurality of offers of competing items; and recommending, via the Al agent, a recommendation of one or more items among the competing items for purchase.

[0165] Clause 14: The method of any of clauses 1 to 13, further comprising: recommending, via the Al agent, one or more locations other than a current location of the customer for purchasing one or more recommended items among the competing items for purchase.

[0166] Clause 15: The method of any of clauses 1 to 14, further comprising: obtaining, via the Al agent, customer-specific information of a plurality of customers; determining, via the Al agent, the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to at least one customer of the plurality of customers based at least in part on the customer-QC2503640WOQualcomm Ref. No. 2503640WO40 / 55specific information; and obtain at least one notification for the at least one customer, the at least one notification including the information associated with the one or more items for sale.

[0167] Clause 16: The method of any of clauses 1 to 15, further comprising: determining, via the Al agent, the plurality of customers competing for the one or more items; determining, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items; or determining, via the Al agent, the plurality of customers for auctioning of the one or more items.

[0168] Clause 17: A device, comprising: one or more memories; one or more transceivers; and one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to: obtain, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and obtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0169] Clause 18: The device of clause 17, wherein the device is: a user equipment (UE); a server; or a cloud,

[0170] Clause 19: The device of any of clauses 17 to 18, wherein the Al agent is: an artificial intelligence / machine learning (AI / ML) model tailored to the customer; a large language model (LLM) tailored to the customer; or a visual LLM tailored to the customer.

[0171] Clause 20: The device of any of clauses 17 to 19, wherein the customer-specific information includes: one or more preferred items indicated by the customer; a shopping history of the customer; one or more shopping locations of the customer; one or more shopping trajectories of the customer; one or more social media engagements of the customer; or any combination thereof.

[0172] Clause 21: The device of any of clauses 17 to 20, wherein the customer-specific information is further based at least in part on: inventory status of the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; one or more constraints on the one or more items at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; preferred sales outcomes at theQC2503640WOQualcomm Ref. No. 2503640WO41 / 55one or more retailers, the one or more sites, the one or more brands, or any combination thereof; or any combination thereof.

[0173] Clause 22: The device of any of clauses 17 to 21, wherein the one or more processors, either alone or in combination, are further configured to: obtain, from a user equipment (UE) of the customer, one or more preferred or desired items for a current shopping session.

[0174] Clause 23: The device of any of clauses 17 to 22, wherein the one or more processors, either alone or in combination, are further configured to: predict, via the Al agent, one or more items preferred or desired to be purchased for a current shopping session based on the customer-specific information.

[0175] Clause 24: The device of any of clauses 17 to 23, wherein the notification is transmitted to the customer via a user equipment (UE), an electronic label device, or both.

[0176] Clause 25: The device of any of clauses 17 to 24, wherein the information associated with one or more items for sale to the customer includes: an offer for sale of the one or more items to the customer; product information associated with the one or more items; or any combination thereof.

[0177] Clause 26: The device of any of clauses 17 to 25, wherein the information associated with one or more items for sale to the customer is an offer of bargaining to the customer.

[0178] Clause 27: The device of any of clauses 17 to 26, w’herein the offer of bargaining is initiated by a retailer based on one or more measurements of a location of the customer.

[0179] Clause 28: The device of any of clauses 17 to 27, wherein the one or more processors, either alone or in combination, are further configured to: determine, via the Al agent, a plurality’ retailers, a plurality of sites, a plurality of brands, or any combination thereof, to obtain a plurality of offers of competing items for sale to the customer based at least in part on the customer-specific information.

[0180] Clause 29: The device of any of clauses 17 to 28, wherein the one or more processors, either alone or in combination, are further configured to: communicate, via the Al agent, with the customer the plurality of offers of competing items; and recommend, via the Al agent, a recommendation of one or more items among the competing items for purchase.

[0181] Clause 30: The device of any of clauses 17 to 29, wherein the one or more processors, either alone or in combination, are further configured to: recommend, via the Al agent,QC2503640WOQualcomm Ref. No. 2503640WO42 / 55one or more locations other than a current location of the customer for purchasing one or more recommended items among the competing items for purchase.

[0182] Clause 31: The device of any of clauses 17 to 30, wherein the one or more processors, either alone or in combination, are further configured to: obtain, via the Al agent, customer-specific information of a plurality of customers; determine, via the Al agent, the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to at least one customer of the plurality of customers based at least in part on the customerspecific information; and obtain at least one notification for the at least one customer, the at least one notification include the information associated with the one or more items for sale.

[0183] Clause 32: The device of any of clauses 17 to 31, wherein the one or more processors, either alone or in combination, are further configured to: determine, via the Al agent, the plurality of customers competing for the one or more items; determine, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items; or determine, via the Al agent, the plurality of customers for auctioning of the one or more items.

[0184] Clause 33: A device, comprising: means for obtaining, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; means for determining, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and means for obtaining a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0185] Clause 34: The device of clause 33, wherein the device is: a user equipment (UE); a server; or a cloud,

[0186] Clause 35: The device of any of clauses 33 to 34, wherein the Al agent is: an artificial intelligence / machine learning (AI / ML) model tailored to the customer; a large language model (LLM) tailored to the customer a large language model (LLM) tailored to the customer; or a visual LLM tailored to the customer.

[0187] Clause 36: The device of any of clauses 33 to 35, wherein the customer-specific information includes: one or more preferred items indicated by the customer; a shoppingQC2503640WOQualcomm Ref. No. 2503640WO43 / 55history of the customer; one or more shopping locations of the customer; one or more shopping trajectories of the customer; one or more social media engagements of the customer; or any combination thereof.

[0188] Clause 37: The device of any of clauses 33 to 36, wherein the customer-specific information is further based at least in part on: inventory status of the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; one or more constraints on the one or more items at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; preferred sales outcomes at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; or any combination thereof.[0189j Clause 38: The device of any of clauses 33 to 37, further comprising: means for obtaining, from a user equipment (UE) of the customer, one or more preferred or desired items for a current shopping session.

[0190] Clause 39: The device of any of clauses 33 to 38, further comprising: means for predicting, via the Al agent, one or more items preferred or desired to be purchased for a current shopping session based on the customer-specific information.

[0191] Clause 40: The device of any of clauses 33 to 39, wherein the notification is transmitted to the customer via a user equipment (UE), an electronic label device, or both.

[0192] Clause 41: The device of any of clauses 33 to 40, wherein the information associated with one or more items for sale to the customer includes: an offer for sale of the one or more items to the customer; product information associated with the one or more items; or any combination thereof.

[0193] Clause 42: The device of any of clauses 33 to 41, wherein the information associated with one or more items for sale to the customer is an offer of bargaining to the customer.

[0194] Clause 43: The device of any of clauses 33 to 42, wherein the offer of bargaining is initiated by a retailer based on one or more measurements of a location of the customer.

[0195] Clause 44: The device of any of clauses 33 to 43, further comprising: means for determining, via the Al agent, a plurality retailers, a plurality of sites, a plurality of brands, or any combination thereof, to obtain a plurality of offers of competing items for sale to the customer based at least in part on the customer-specific information.

[0196] Clause 45: The device of any of clauses 33 to 44, further comprising: means for communicating, via the Al agent, with the customer the plurality of offers of competingQC2503640WOQualcomm Ref. No. 2503640WO44 / 55items; and means for recommending, via the Al agent, a recommendation of one or more items among the competing items for purchase.

[0197] Clause 46: The device of any of clauses 33 to 45, further comprising: means for recommending, via the Al agent, one or more locations other than a current location of the customer for purchasing one or more recommended items among the competing items for purchase.

[0198] Clause 47: The device of any of clauses 33 to 46, further comprising: means for obtaining, via the Al agent, customer-specific information of a plurality of customers means for determining, via the Al agent, the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to at least one customer of the plurality of customers based at least in part on the customer-specific information; and means for obtaining at least one notification for the at least one customer, the at least one notification including the information associated with the one or more items for sale.

[0199] Clause 48: The device of any of clauses 33 to 47, further comprising: means for determining, via the Al agent, the plurality of customers competing for the one or more items; means for determining, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items; determining, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items; or means for determining, via the Al agent, the plurality of customers for auctioning of the one or more items.

[0200] Clause 49: A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a device, cause the device to: obtain, via an artificial intelligence (Al) agent, customer-specific information associated with a customer; determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; and obtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

[0201] Clause 50: The non-transitory computer-readable medium of clause 49, wherein the device is: a user equipment (UE); a server; or a cloud.QC2503640WOQualcomm Ref. No. 2503640WO45 / 55

[0202] Clause 51: The non-transitory computer-readable medium of any of clauses 49 to 50, wherein the Al agent is: an artificial intelligence / machine learning (AI / ML) model tailored to the customer; a large language model (LLM) tailored to the customer; or a visual LLM tailored to the customer.

[0203] Clause 52: The non -transitory’ computer-readable medium of any of clauses 49 to 51, wherein the customer-specific information includes: one or more preferred items indicated by the customer; a shopping history of the customer; one or more shopping locations of the customer; one or more shopping trajectories of the customer; one or more social media engagements of the customer; or any combination thereof

[0204] Clause 53: The non-transitory computer-readable medium of any of clauses 49 to 52, wherein the customer-specific information is further based at least in part on: inventory status of the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; one or more constraints on the one or more items at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; preferred sales outcomes at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof; or any combination thereof.

[0205] Clause 54: The non-transitory computer-readable medium of any of clauses 49 to 53, further comprising computer-executable instructions that, when executed by the device, cause the device to: obtain, from a user equipment (UE) of the customer, one or more preferred or desired items for a current shopping session.

[0206] Clause 55: The non-transitory computer-readable medium of any of clauses 49 to 54, further comprising computer-executable instructions that, when executed by the device, cause the device to: predict, via the Al agent, one or more items preferred or desired to be purchased for a current shopping session based on the customer-specific information.

[0207] Clause 56: The non-transitory computer-readable medium of any of clauses 49 to 55, wherein the notification is transmitted to the customer via a user equipment (UE), an electronic label device, or both.

[0208] Clause 57: The non-transitory computer-readable medium of any of clauses 49 to 56, wherein the information associated with one or more items for sale to the customer includes: an offer for sale of the one or more items to the customer; product information associated with the one or more items; or any combination thereof.QC2503640WOQualcomm Ref. No. 2503640WO46 / 55

[0209] Clause 58: The non-transitory computer-readable medium of any of clauses 49 to 57, wherein the information associated with one or more items for sale to the customer is an offer of bargaining to the customer.

[0210] Clause 59: The non-transitory computer-readable medium of any of clauses 49 to 58, wherein the offer of bargaining is initiated by a retailer based on one or more measurements of a location of the customer.

[0211] Clause 60: The non-transitory computer-readable medium of any of clauses 49 to 59, further comprising computer-executable instructions that, when executed by the device, cause the device to: determine, via the Al agent, a plurality retailers, a plurality of sites, a plurality of brands, or any combination thereof, to obtain a plurality of offers of competing items for sale to the customer based at least in part on the customer-specific information.

[0212] Clause 61: The non-transitory computer-readable medium of any of clauses 49 to 60, further comprising computer-executable instructions that, when executed by the device, cause the device to: communicate, via the Al agent, with the customer the plurality of offers of competing items; and recommend, via the Al agent, a recommendation of one or more items among the competing items for purchase.

[0213] Clause 62: The non-transitory computer-readable medium of any of clauses 49 to 61, further comprising computer-executable instructions that, when executed by the device, cause the device to: recommend, via the Al agent, one or more locations other than a current location of the customer for purchasing one or more recommended items among the competing items for purchase.

[0214] Clause 63: The non-transitory computer-readable medium of any of clauses 49 to 62, further comprising computer-executable instructions that, when executed by the device, cause the device to: obtain, via the Al agent, customer-specific information of a plurality of customers; determine, via the Al agent, the one or more retailers, the one or more sites, the one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to at least one customer of the plurality of customers based at least in part on the customer-specific information; and obtain at least one notification for the at least one customer, the at least one notification include the information associated with the one or more items for sale.QC2503640WOQualcomm Ref. No. 2503640WO47 / 55

[0215] Clause 64: The non-transitory computer-readable medium of any of clauses 49 to 63, further comprising computer-executable instructions that, when executed by the device, cause the device to: determine, via the Al agent, the plurality of customers competing for the one or more items; determine, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items; or determine, via the Al agent, the plurality of customers for auctioning of the one or more items.

[0216] Those of skill in the art will appreciate that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0217] Further, those of skill in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure,

[0218] The various illustrative logical blocks, modules, and circuits described in connection with the aspects disclosed herein may be implemented or performed with a general purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, aQC2503640WOQualcomm Ref. No. 2503640WO48 / 55plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration,

[0219] The methods, sequences and / or algorithms described in connection with the aspects disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in random access memory (RAM), flash memory, read-only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An example storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, The ASIC may reside in a user terminal (e.g., UE). In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

[0220] In one or more example aspects, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium, For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usuallyQC2503640WOQualcomm Ref. No. 2503640WO49 / 55reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0221] While the foregoing disclosure shows illustrative aspects of the disclosure, it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. For example, the functions, steps and / or actions of the method claims in accordance with the aspects of the disclosure described herein need not be performed in any particular order. Further, no component, function, action, or instruction described or claimed herein should be construed as critical or essential unless explicitly described as such. Furthermore, as used herein, the terms “set,” “group,” and the like are intended to include one or more of the stated elements. Also, as used herein, the terms “has,” “have,” “having,” “comprises,” “comprising,” “includes,” “including,” and the like does not preclude the presence of one or more additional elements (e.g., an element “having” A may also have B). Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Also, as used herein, the term “or” is intended to be inclusive when used in a series and may be used interchangeably with “and / or,” unless explicitly stated otherwise (e.g., if used in combination with “either” or “only one of ’) or the alternatives are mutually exclusive (e.g., “one or more” should not be interpreted as “one and more”). Furthermore, although components, functions, actions, and instructions may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated. Accordingly, as used herein, the articles “a,” “an,” “the,” and “said” are intended to include one or more of the stated elements. Additionally, as used herein, the terms “at least one” and “one or more” encompass “one” component, function, action, or instruction performing or capable of performing a described or claimed functionality and also “two or more” components, functions, actions, or instructions performing or capable of performing a described or claimed functionality in combination.QC2503640WO

Claims

Qualcomm Ref. No. 2503640WO50 / 55CLAIMSWhat is claimed is:

1. A device, comprising:one or more memories;one or more transceivers; andone or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to:obtain, via an artificial intelligence (Al) agent, customer-specific information associated with a customer;determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; andobtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

2. The device of claim 1, wherein the device is:a user equipment (UE);a server; ora cloud.

3. The device of claim 1, wherein the Al agent is:an artificial intelligence / machine learning (AI / ML) model tailored to the customer;a large language model (LLM) tailored to the customer; ora visual LLM tailored to the customer.

4. The device of claim 1, wherein the customer-specific information includes: one or more preferred items indicated by the customer;a shopping history of the customer;one or more shopping locations of the customer;QC2503640WOQualcomm Ref. No. 2503640WO51 / 55one or more shopping trajectories of the customer;one or more social media engagements of the customer;or any combination thereof.

5. The device of claim 1, wherein the customer-specific information is further based at least in part on:inventory status of the one or more retailers, the one or more sites, the one or more brands, or any combination thereof;one or more constraints on the one or more items at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof;preferred sales outcomes at the one or more retailers, the one or more sites, the one or more brands, or any combination thereof;or any combination thereof.

6. The device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to:obtain, from a user equipment (UE) of the customer, one or more preferred or desired items for a current shopping session.

7. Tire device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to:predict, via the Al agent, one or more items preferred or desired to be purchased for a current shopping session based on the customer-specific information,8. The device of claim 1, wherein the notification is transmitted to the customer via a user equipment (UE), an electronic label device, or both.

9. The device of claim 1, wherein the information associated with one or more items for sale to the customer includes:an offer for sale of the one or more items to the customer;product information associated with the one or more items;or any combination thereof.QC2503640WOQualcomm Ref. No. 2503640WO52 / 5510. The device of claim 1, wherein the information associated with one or more items for sale to the customer is an offer of bargaining to the customer.

11. The device of claim 10, wherein the offer of bargaining is initiated by a retailer based on one or more measurements of a location of the customer.

12. The device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to:determine, via the Al agent, a plurality retailers, a plurality of sites, a plurality of brands, or any combination thereof, to obtain a plurality of offers of competing items for sale to the customer based at least in part on the customer-specific information.

13. Tlie device of claim 12, wherein the one or more processors, either alone or in combination, are further configured to:communicate, via the one or more transceivers, via the Al agent, with the customer the plurality of offers of competing items; andrecommend, via the Al agent, a recommendation of one or more items among the competing items for purchase.

14. Tlie device of claim 13, wherein the one or more processors, either alone or in combination, are further configured to:recommend, via the Al agent, one or more locations other than a current location of the customer for purchasing one or more recommended items among the competing items for purchase.

15. Tire device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to:obtain, via the Al agent, customer-specific information of a plurality of customers;determine, via the Al agent, the one or more retailers, the one or more sites, tire one or more brands, or any combination thereof, to obtain information associated withQC2503640WOQualcomm Ref. No. 2503640WO53 / 55one or more items for sale to at least one customer of the plurality of customers based at least in part on the customer-specific information; andobtain at least one notification for the at least one customer, the at least one notification including the information associated with the one or more items for sale.

16. Tire device of claim 15, wherein the one or more processors, either alone or in combination, are further configured to:determine, via the Al agent, the plurality of customers competing for the one or more items;determine, via the Al agent, the plurality of customers cooperating in one or more purchases of the one or more items; ordetermine, via the Al agent, the plurality of customers for auctioning of the one or more items.

17. A method of positioning performed by a device, comprising:obtaining, via an artificial intelligence (Al) agent, customer-specific information associated with a customer;determining, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; andobtaining a notification for the customer, the notification including the information associated with one or more items for sale to the customer.

18. The method of claim 17, wherein the device is:a user equipment (UE);a server; ora cloud.

19. The method of claim 17, wherein the Al agent is:an artificial intelligence / machine learning (AI / ML) model tailored to the customer;QC2503640WOQualcomm Ref. No. 2503640WO54 / 55a large language model (LLM) tailored to the customer; ora visual LLM tailored to the customer.

20. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a device, cause the device to:obtain, via an artificial intelligence (Al) agent, customer-specific information associated with a customer;determine, via the Al agent, one or more retailers, one or more sites, one or more brands, or any combination thereof, to obtain information associated with one or more items for sale to the customer based at least in part on the customer-specific information; andobtain a notification for the customer, the notification including the information associated with one or more items for sale to the customer.QC2503640WO

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