US-12619262-B2 - Methods and systems for real-time enhanced learning services and intelligent on-demand task-based services

US12619262B2US 12619262 B2US12619262 B2US 12619262B2US-12619262-B2

Abstract

Aspects of the subject disclosure may include, for example, receiving a user selection relating to a course, transmitting a request to a controller in a vehicle for information regarding capabilities of available devices onboard the vehicle, wherein the available devices include uncrewed aerial vehicles (UAVs), based on the transmitting, obtaining, from the controller, the information regarding the capabilities, responsive to the obtaining, sending a command to the controller to facilitate deployment of one or more of the UAVs to collect data for the course, and after the sending, receiving the data from the controller and incorporating the data into the course for delivery to one or more users onboard the vehicle. Other embodiments are disclosed.

Inventors

Zhi Cui
Paul Edward Smith, JR.
Venson Shaw

Assignees

AT&T INTELLECTUAL PROPERTY I, L.P.

Dates

Publication Date: 20260505
Application Date: 20240329

Claims (20)

1 . A device, comprising: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising: receiving a user selection relating to a course; transmitting a request to a controller in a vehicle for information regarding: capabilities of available devices onboard the vehicle, wherein the available devices include uncrewed aerial vehicles (UAVs); based on the transmitting, obtaining, from the controller, the information regarding the capabilities; responsive to the obtaining, deploying one or more UAVs and collecting, with the one or more UAVs, data for the course; and receiving the data from the controller and incorporating the data into the course for delivery to one or more users onboard the vehicle.
2 . The device of claim 1 , wherein the vehicle comprises a cruise ship, a spaceship, a train, or a bus.
3 . The device of claim 1 , wherein the operations further comprise communicating, via the controller, with a service management and orchestration system (SMO) to coordinate network connectivity for the one or more UAVs.
4 . The device of claim 1 , wherein the course is included in a catalog of courses available for study.
5 . The device of claim 1 , wherein the operations further comprise facilitating delivery of the course to one or more users that are not onboard the vehicle.
6 . The device of claim 1 , wherein the data for the course comprises video data, image data, audio data, or a combination thereof.
7 . The device of claim 1 , wherein the data for the course comprises physical samples.
8 . The device of claim 1 , wherein the user selection is received from a user device that is distinct from the controller.
9 . The device of claim 1 , wherein the available devices include one or more video output devices, one or more audio output devices, or a combination thereof.
10 . The device of claim 9 , wherein the delivery of the course involves utilization of the one or more video output devices, the one or more audio output devices, or the combination thereof.
11 . A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system of a vehicle including a processor, facilitate performance of operations, the operations comprising: receiving, from a learning system, a request for information regarding: capabilities of available devices onboard the vehicle, wherein the request relates to a course, and wherein the available devices include uncrewed aerial vehicles (UAVs); based on the request, transmitting, to the learning system, the information regarding the capabilities; responsive to the transmitting, receiving, from the learning system, a command to deploy one or more UAVs to collect data for the course; based on the command, causing deploying the one or more UA Vs and collecting, with the one or more UAVs, the data for the course; and receiving the collected data by the one or more UAVs and sending the collected data to the learning system for assembling, editing, and providing the collected data into the course for delivery to a user device onboard the vehicle.
12 . The non-transitory machine-readable medium of claim 11 , wherein the operations further comprise sending the data to the learning system for incorporation into the course.
13 . The non-transitory machine-readable medium of claim 11 , wherein the deploying the one or more UAVs further comprises communicating with a service management and orchestration system (SMO) to coordinate network connectivity for the one or more UAVs.
14 . The non-transitory machine-readable medium of claim 11 , wherein the collected data comprises video data, image data, audio data, or a combination thereof.
15 . The non-transitory machine-readable medium of claim 11 , wherein the course is selected by a user onboard the vehicle.
16 . The non-transitory machine-readable medium of claim 11 , wherein the available devices include one or more video output devices, one or more audio output devices, or a combination thereof.
17 . A method, comprising: receiving, by a processing system, from an Internet-of-Things (IoT) device including a processor, information regarding one or more conditions of a room or area of a vehicle; and analyzing, by the processing system, the information regarding the one or more conditions of the room or area of the vehicle, to determine one or more tasks that are needed to address the one or more conditions of the room or area, and to assign the IoT device or one or more other IoT devices to perform the one or more tasks for the room or area; receiving, by the processing system, from a learning system, a request for information regarding: capabilities of available devices onboard the vehicle, wherein the request relates to a course, and wherein the available devices include uncrewed aerial vehicles (UAVs); based on the request, transmitting, by the processing system, to the learning system, the information regarding the capabilities; responsive to the transmitting, receiving, by the processing system, from the learning system, a command to deploy one or more UAVs to collect data for the course; based on the command, deploying, by the processing system, the one or more UAVs and collecting, by the processing system, with the one or more UAVs, the data for the course; and receiving, by the processing system, the collected data by the one or more UAVs and sending, by the processing system, the collected data to the learning system for assembling, editing, and providing the collected data into the course for delivery to a user device onboard the vehicle.
18 . The method of claim 17 , wherein the receiving involves use of one or more sensors to obtain sensor data.
19 . The method of claim 18 , wherein the one or more sensors comprise an image sensor, an audio sensor, an environmental sensor, or a combination thereof.
20 . The method of claim 17 , further comprising obtaining, by the processing system, data that includes environmental information, local custom information associated with a current location of the vehicle, or rules associated with the current location of the vehicle, and configuring the IoT device or the one or more other IoT devices to customize one or more rooms or areas of the vehicle based on the data.

Description

FIELD OF THE DISCLOSURE The subject disclosure relates to real-time (or near real-time) enhanced learning services and/or intelligent on-demand task-based services. BACKGROUND People generally spend time enjoying a variety of activities while on a voyage. A cruise ship, for instance, may offer numerous venues and entertainment options for passengers onboard to choose from. Throughout a journey, as passengers go about their activities, the facilities of the vessel, including passenger rooms and common areas, also undergo cleaning and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS Reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein: FIG. 1 is a block diagram illustrating an exemplary, non-limiting embodiment of a communications network in accordance with various aspects described herein. FIG. 2A is a block diagram illustrating an example, non-limiting embodiment of a system functioning within, or operatively overlaid upon, the communications network of FIG. 1 in accordance with various aspects described herein. FIG. 2B is a block diagram illustrating an example, non-limiting embodiment of another system functioning within, or operatively overlaid upon, the communications network of FIG. 1 and/or the system of FIG. 2A, in accordance with various aspects described herein. FIG. 2C depicts an illustrative embodiment of a method in accordance with various aspects described herein. FIG. 2D depicts an illustrative embodiment of a method in accordance with various aspects described herein. FIG. 3 is a block diagram illustrating an example, non-limiting embodiment of a virtualized communications network in accordance with various aspects described herein. FIG. 4 is a block diagram of an example, non-limiting embodiment of a computing environment in accordance with various aspects described herein. FIG. 5 is a block diagram of an example, non-limiting embodiment of a mobile network platform in accordance with various aspects described herein. FIG. 6 is a block diagram of an example, non-limiting embodiment of a communication device in accordance with various aspects described herein. DETAILED DESCRIPTION It is believed that opportunities for passengers to learn subjects/topics while onboard a cruise are presently lacking. Further, maintenance/cleaning of rooms or common areas on a cruise ship is typically performed according to a fixed standard protocol, which can be inefficient and ineffective since the conditions of different rooms or areas may be different and thus demand different levels of care. Some or all of these issues can negatively impact guest experience and increase costs for the cruise ship operator. The subject disclosure describes, among other things, illustrative embodiments of a learning system that is capable of providing enhanced, real-time (or near real-time) learning services. In exemplary embodiments, the system may be an on-demand study on the cruise (ODSC) system that provides such services to users onboard a vessel (e.g., passengers on a cruise) and/or elsewhere. In various embodiments, the ODSC system may facilitate course delivery to users (e.g., students or others interested in learning about a subject or topic) based on user request and/or requirements. In some embodiments, the ODSC system may communicate with cruise lines to identify capabilities, offers, requirements, etc. of corresponding cruise ships and/or equipment onboard. In one or more embodiments, the ODSC system may communicate with smart cruise controllers (SCCs) located onboard cruise ships. As will be described in more detail below, an SCC may facilitate procurement of content (e.g., videos, images, audio, etc.) for incorporation into a course or as part of modules of a course. Packaging and/or delivery of course content may be tailored to meet individual requests. The subject disclosure also describes illustrative embodiments of a task-based system that is capable of providing (e.g., on-demand) maintenance/cleaning services. In exemplary embodiments, the task-based system may be implemented across an SCC, smart room controller(s) (SRCs), and Internet-of-Things (IoT) devices, such as, for instance, cleaning bots. In various embodiments, the task-based system may provide dynamic detection of room/area conditions and learn to optimize or improve the cleaning process. In some embodiments, cleaning bots may be equipped with sensors (e.g., cameras, etc.) for detecting the conditions of a given room, may provide information regarding the conditions to the task-based system, and may receive corresponding instructions from the task-based system to conduct/adapt the cleaning process. In one or more embodiments, the SCC may generally manage the cleaning bots and use data from the sensors to continually optimize or improve the cleaning process. In certain embodiments, the task-based system may be adaptive to the location or changing conditions. In these embodiments, the task-bas