SCALABLE ASSISTIVE DATA GENERATION AND DELIVERY

1 . A method in a server of generating assistive data, the method comprising:

receiving, at the server from a client device, a request for assistive data, the request including (i) client contextual data, and (ii) a type indicator corresponding to a first request type or a second request type;

selecting between an automated response mechanism, when the type indicator corresponds to the first request type, and a manual response mechanism when the type indicator corresponds to the second request type;

responsive to selecting the automated response mechanism, retrieving automated assistive data from a repository based on the client contextual data; and

returning the automated assistive data to the client device.

2 . The method of claim 1 , wherein the client contextual data includes audio and video data captured by the client device; and wherein the automated assistive data includes at least one of video overlay and audio instructions.

3 . The method of claim 1 , wherein retrieving the automated assistive data from the repository includes applying a classification model to the client contextual data.

4 . The method of claim 3 , further comprising:

responsive to selecting the manual response mechanism, routing the request to an expert computing device;

receiving manual assistive data from the expert computing device; and

returning the manual assistive data to the client device.

5 . The method of claim 4 , further comprising:

providing the manual assistive data and the client contextual data to a training module as a positive training sample; and

generating an updated classification model using the training module.

6 . The method of claim 5 , further comprising: deploying the updated classification model to a subset of a plurality of client devices.

7 . The method of claim 6 , further comprising: storing a list of at least the subset of client devices at the server.

8 . The method of claim 3 , further comprising:

responsive to returning the automated assistive data to the client device, receiving a further request including a type indicator corresponding to the second request type; and

providing the automated assistive data and the client contextual data to a training mechanism as a negative training sample.

9 . A server, comprising:

a memory storing a repository of assistive data;

a communications interface; and

a processor configured to:

receive, from a client device, a request for assistive data, the request including (i) client contextual data, and (ii) a type indicator corresponding to a first request type or a second request type;

select between an automated response mechanism, when the type indicator corresponds to the first request type, and a manual response mechanism when the type indicator corresponds to the second request type;

responsive to selection of the automated response mechanism, retrieve automated assistive data from the repository based on the client contextual data; and

return the automated assistive data to the client device.

10 . The server of claim 9 , wherein the client contextual data includes audio and video data captured by the client device; and wherein the automated assistive data includes at least one of video overlay and audio instructions.

11 . The server of claim 9 , wherein the processor is configured, in order to retrieve the automated assistive data from the repository, to apply a classification model to the client contextual data.

12 . The server of claim 11 , wherein the processor is further configured to:

responsive to selection of the manual response mechanism, route the request to an expert computing device via the communications interface;

receive manual assistive data from the expert computing device; and

return the manual assistive data to the client device.

13 . The server of claim 12 , wherein the processor is further configured to:

provide the manual assistive data and the client contextual data to a training module as a positive training sample; and

generate an updated classification model using the training module.

14 . The server of claim 13 , wherein the processor is further configured to: deploy the updated classification model to a subset of a plurality of client devices.

15 . The server of claim 14 , wherein the memory stores a list of at least the subset of client devices at the server.

16 . The server of claim 11 , wherein the processor is further configured to:

responsive to returning the automated assistive data to the client device, receive a further request including a type indicator corresponding to the second request type; and

provide the automated assistive data and the client contextual data to a training mechanism as a negative training sample.

17 . A system, comprising:

a client computing device configured to transmit a request for assistive data; and

a server, comprising:

a memory storing a repository of assistive data;

a communications interface; and

a processor configured to:

receive, from a client device, a request for assistive data, the request including (i) client contextual data, and (ii) a type indicator corresponding to a first request type or a second request type;

select between an automated response mechanism, when the type indicator corresponds to the first request type, and a manual response mechanism when the type indicator corresponds to the second request type;

responsive to selection of the automated response mechanism, retrieve automated assistive data from the repository based on the client contextual data; and

return the automated assistive data to the client device.

18 . The system of claim 17 , wherein the client device includes a head-mounted display.

19 . The system of claim 18 , wherein the head-mounted display includes a camera and a microphone controllable to capture the client contextual data.