METHOD AND SYSTEM FOR AUTOMATICALLY DETECTING AND RESOLVING ACCIDENTAL EMERGENCY CALLS

• US 20190325288A1
• Filed: 04/24/2018
• Published: 10/24/2019
• Est. Priority Date: 04/24/2018
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: Motorola Solutions, Inc.
• Inventors: OYENAN, WALAMITIEN H., FANG, ZHENG, BONDAREVA, MARIYA
• Granted Patent: US 11,093,814 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/006 based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G10L 25/63 for estimating an emotional state
• CPC Class Codes: H04M 2242/04 for emergency applications
• CPC Class Codes: H04M 3/42195 Arrangements for calling back a calling subscriber when the wanted subscriber ceases to be busy H04M3/48
• CPC Class Codes: H04M 3/5116 for emergency applications

Abstract

An example method and apparatus for processing accidental emergency calls is provided herein. The example method includes monitoring an emergency call with an active learning artificial intelligence (AI) bot implemented by a processor. The example method further includes determining, by the AI bot, that the emergency call was disconnected prior to a call taker resolving the emergency call. The example method additionally includes providing, by the AI bot, a score indicative of the likelihood that the emergency call was an accidental call, wherein the call may be based on real-time and historical data. The example method also includes recommending, by the AI bot, a response to the emergency call based upon the score.

Claims

1. A method for processing accidental emergency calls comprising:

monitoring an emergency call with an active learning Artificial Intelligence (AI) bot implemented by a processor;

determining, by the AI bot, that the emergency call was disconnected prior to a call taker resolving the emergency call;

providing, by the AI bot, a score indicative of the likelihood that the emergency call was an accidental call, wherein the score is based on real-time and historical data; and

recommending, by the AI bot, a response to the emergency call based upon the score.

2. The method of claim 1, further comprising:

attempting at least one automated call back by the AI bot based on the score.

3. The method of claim 1, further comprising:

providing a confidence level of the emergency call being accidental based on at least the score and historical data.

4. The method of claim 1, further comprising:

providing an indication that the emergency call was or was not an accidental call, wherein the AI bot updates the historical data based on the indication in order to actively learn from each emergency call.

5. The method of claim 1 wherein real-time data comprises:

duration of the emergency call;

natural language content of emergency call conversation; and

caller location.

6. The method of claim 1 wherein real-time data comprises:

emergency call background noise.

7. The method of claim 1 wherein historical data comprises:

caller accidental call history;

crime history in the vicinity of caller'"'"'s location; and

computer aided dispatch information.

9. The medium of claim 1, further comprising instructions to:

attempt at least one automated call back by the AI bot based on the score.

10. The medium of claim 1, further comprising instructions to:

provide a confidence level of the emergency call being accidental based on at least the score and historical data.

11. The medium of claim 1, further comprising instructions to:

provide an indication that the emergency call was or was not an accidental call, wherein the AI bot updates the historical data based on the indication in order to actively learn from each emergency call.

12. The medium of claim 1 wherein real-time data comprises:

duration of the emergency call;

natural language content of emergency call conversation; and

caller location.

13. The medium of claim 1 wherein real-time data comprises:

emergency call background noise.

14. The medium of claim 1 wherein historical data comprises:

caller accidental call history;

crime history in the vicinity of caller'"'"'s location; and

computer aided dispatch information.

16. The system of claim 1, further comprising instructions to:

attempt at least one automated call back by the AI bot based on the score.

17. The system of claim 1, further comprising instructions to:

provide a confidence level of the emergency call being accidental based on at least the score and historical data.

18. The system of claim 1, further comprising instructions to:

provide an indication that the emergency call was or was not an accidental call, wherein the AI bot updates the historical data based on the indication in order to actively learn from each emergency call.

19. The system of claim 1 wherein real-time data comprises:

duration of the emergency call;

natural language content of emergency call conversation; and

caller location.

20. The system of claim 1 wherein historical data comprises:

caller accidental call history;

crime history in the vicinity of caller'"'"'s location; and

computer aided dispatch information.

8. A non-transitory processor readable medium containing a set of instructions thereon which when executed by a processor cause the processor to:

monitor an emergency call with an active learning Artificial Intelligence (AI) bot;

determine, by the AI bot, that the emergency call was disconnected prior to a call taker resolving the emergency call;

provide, by the AI bot, a score indicative of the likelihood that the emergency call was an accidental call, wherein the score is based on real-time and historical data; and

recommend, by the AI bot, a response to the emergency call based upon the score.

15. A system for processing accidental emergency calls comprising:

a processor; and

a memory containing instructions which when executed by the processor cause the processor to;

monitor an emergency call with an active learning Artificial Intelligence (AI) bot;

determine, by the AI bot, that the emergency call was disconnected prior to a call taker resolving the emergency call;

provide, by the AI bot, a score indicative of the likelihood that the emergency call was an accidental call, wherein the score is based on real-time and historical data; and

recommend, by the AI bot, a response to the emergency call based upon the score.