Smart sensor-based consumer service optimization

Patent metadata

Field	Value
Publication number	US-11663682-B2
Application number	US-201916538580-A
Country	US
Kind code	B2
Filing date	Aug 12, 2019
Priority date	Jan 9, 2017
Publication date	May 30, 2023
Grant date	May 30, 2023

Abstract

A method, computer program product, and system includes a processor(s) determining, based on obtaining data from the one or more sensors over the wireless communications connection, that individuals are within a given vicinity. The processor(s) queries personal computing devices associated with the individuals to determine an identity of each individual in the given vicinity. The processor(s) assigns a service provider(s) to a portion of the identified individuals. The processor(s) obtains preference information related to the portion and determines environmental information related to an environment experienced by the portion by locating at least one sensor within a predetermined distance of the portion, and communicating, over the wireless communications connection, with the at least one sensor. The processor(s) generate simulations for providing services to the portion that include temporal parameters and selects an optimal simulation. The processor(s) communicates instructions to achieve aspects of the optimal simulation to the service provider(s).

First claim

What is claimed is:

1. A computer-implemented method, comprising:
updating, by one or more processors, a machine learning algorithm, wherein the machine learning algorithm generates patterns related to service levels of one or more service providers, based on obtaining data related to service experiences of individuals serviced by the one or more service providers and updating the machine learning algorithm based on the data;
determining, by the one or more processors, based on obtaining data from one or more sensors over a wireless communications connection, that individuals are within a given vicinity, based on communicating, over a wireless connection, for each individual or the individuals, with a device selected from the group consisting of: a computing device utilized by an individual and a static hardware sensor within the given vicinity of the individual;
querying, by one or more processors, via the wireless communications connection, personal computing devices associated with the individuals within the given vicinity to determine an identity of each individual in the given vicinity based on unique identifiers associated with the personal computing devices;
assigning, by the one or more processors, one or more service providers to a portion of the identified individuals, wherein the assigning comprises generating workloads for the one or more service providers;
obtaining, by the one or more processors, from computing resources accessible over the wireless communications connection, wherein the computing resources comprise the personal computing devices, preference information related to the portion of the identified individuals, wherein the preference information comprises historical data accessible based on monitoring the personal computing devices;
determining, by the one or more processors, environmental information related to an environment experienced by the portion of the identified individuals, wherein the environmental information is selected from the group consisting of: time, temperature, humidity, vibrations, motion, light, pressure, and altitude, wherein the determining comprises locating at least one sensor of the one or more sensors, and wherein the at least one sensor is within a predetermined distance of the portion of the identified individuals, and communicating, over the wireless communications connection, with the at least one sensor;
based on the preference information and the environmental information, generating, by the one or more processors, simulations for providing services to the portion of the identified individuals, wherein the simulations comprise temporal parameters for providing the services, wherein generating the simulations comprises applying, by the one or more processor, the updated machine learning algorithm, wherein applying the updated machine learning algorithm comprises:
generating, by the one or more processors, the one or more patterns related to the service levels of the one or more service providers, and
based on determining that a service provider of the one or more service providers can perform within a pre-defined level of confidence, utilizing the preference information and the environmental information to determine an optimized timing related to the service provider performing the services;

selecting, by the one or more processors, an optimal simulation; and
changing, by the one or more processors, the workloads of the one or more service providers, wherein the changing comprises communicating, by the one or more processors, via the wireless communications connection, instructions to achieve aspects of the optimal simulation to the one or more service providers, wherein the communicating comprises populating the instructions on one or more graphical user interfaces of one or more mobile computing devices of the one or more service providers, based on the temporal parameters.

2. The computer-implemented method of claim 1 , wherein the preference information comprises an expected level of service, and wherein generating simulations comprises:
determining, by the one or more processor, by executing a simulation, if the assigned one or more service providers can serve the portion of the identified individuals at the expected level of service; and
based on the determining, updating, by the one or more processor, the assigned one or more service providers, wherein the updating is selected from the group consisting of: retaining the assigned one or more service providers and changing to a new one or more service providers.

3. The computer-implemented method of claim 1 , further comprising:
assigning, by the one or more processors, the one or more service providers to a second portion of the identified individuals; and
obtaining, by the one or more processors, from personal computing devices, preference information related to the second portion of the identified individuals;
determining, by the one or more processors, environmental information related to an environment experienced by the second portion of the identified individuals, wherein the determining comprises locating at least one sensor of the one or more sensors, wherein the at least one sensor is within a predetermined distance of the second portion of the identified individuals, and communicating, over the wireless communications connection, with the at least one sensor;
based on the preference information and the environmental information, generating, by the one or more processors, simulations for providing services to the second portion of the identified individuals, wherein the simulations comprise temporal parameters for providing the services;
selecting, by the one or more processors, a second optimal simulation; and
communicating, by the one or more processors, via the wireless communications connection, additional instructions to achieve aspects of the second optimal simulation, to the one or more service providers, wherein the communicating comprises populating the additional instructions on the one or more graphical user interfaces of the one or more mobile computing devices of the one or more service providers, based on the temporal parameters.

4. The computer-implemented method of claim 3 , further comprising:
optimizing, by the one or more processor, a service schedule for the one or more service providers, by the one or more processors, the optimizing comprising integrating the instructions and the additional instructions into the service schedule.

5. The computer-implemented method of claim 1 , further comprising:
monitoring, by the one or more processors, the at least one sensor of the one or more sensors;
receiving, by the one or more processors, an indication of a change in environmental information; and
based on the change, updating, by the one or more processor, the simulations;
re-generating, by the one or more processors, the simulations, based on the updating;
selecting, by the one or more processors, a new optimal simulation; and
communicating, by the one or more processors, via the wireless communications connection, new instructions to achieve aspects of the new optimal simulation to the one or more service providers, wherein the communicating comprises replacing the instructions with the new instructions on the one or more graphical user interfaces of the one or more mobile computing devices.

6. The computer-implemented method of claim 5 , wherein the new instructions comprise a directive to take an immediate action.

7. The computer-implemented method of claim 1 , wherein the environmental information is selected from the group consisting of: time, temperature, humidity, vibrations, motion, light, pressure, and altitude.

8. The computer-implemented method of claim 1 , further comprising:
receivi

Assignees

• IBM

Inventors

• Bender Michael
• Childress Rhonda L
• Shute Michael P

Classifications

• H04W84/18

  Self-organising networks, e.g. ad-hoc networks or sensor networks · CPC title

• G06Q30/0611

  Request for offers or quotes · CPC title

• G06Q30/0635

  replenishment orders; recurring orders · CPC title

• G08B21/02

  Alarms for ensuring the safety of persons · CPC title

• G06Q30/0641

  utilising user interfaces specially adapted for shopping · CPC title