Prioritizing shelf-oriented tasks

1. A system for processing images captured in a retail store and automatically addressing detected conditions within the retail store, the system comprising:

at least one processor configured to:

receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves;

retrieve reference data specifying a desired state of the retail store;

use the reference data to detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products;

use the reference data to detect in the plurality of images an indicator of a second service-improvement condition relating to the plurality of products;

determine a first product-related task for addressing the first service-improvement condition;

determine a second product-related task for addressing the second service-improvement condition;

access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and

assign the first product-related task to the first employee and assign the second product-related task to the second employee.

2. The system of claim 1 , wherein the first service-improvement condition and the second service-improvement condition each include at least one of: a need for cleaning, a need for product restocking, a need for product rearrangement, a need for product re-orienting, a need for product recall, a need for labeling, a need for updated pricing, a promotion-related need, an identified misplaced product, and an occlusion event.

3. The system of claim 2 , wherein, when the first service-improvement condition and the second service-improvement condition include identified misplaced products, the at least one processor is configured to assign the first product-related task to the first employee and the second product-related task to the second employee based on product categories associated with the identified misplaced products.

4. The system of claim 2 , wherein, when the first service-improvement condition and the second service-improvement condition are occlusion events, the at least one processor is configured to assign the first product-related task to the first employee and the second product-related task to the second employee based on occlusion categories associated with the occlusion events.

5. The system of claim 2 , wherein, when the first service-improvement condition is a need for cleaning, and the second service-improvement condition is a need for product rearrangement, the at least one processor is configured to assign the first product-related task to a robot employee and assign the second product-related task to a human employee.

6. The system of claim 1 , wherein, when the first employee is a robot employee, the at least one processor is further configured to determine that the first service-improvement condition can be resolved by the robot employee, before assigning the first product-related task to the first employee.

7. The system of claim 6 , wherein the at least one processor is further configured to: obtain data indicative of a current physical condition of the robot employee for determining that the first service-improvement condition can be resolved by the robot employee.

8. The system of claim 1 , wherein the at least one processor is further configured to: receive location data indicative of current locations of the first employee and the second employee within the retail store; and

assign the first product-related task to the first employee and the second product-related task to the second employee based on the received location data and identified locations of the first service-improvement condition and the second service-improvement condition.

9. The system of claim 1 , wherein the at least one processor is further configured to access pending assignment data indicative of product-related tasks assigned to the first employee and the second employee; and

assign the first product-related task to the first employee and the second product-related task to the second employee based on at least one pending product-related task previously assigned to the first employee and at least one pending product-related task previously assigned to the second employee.

10. The system of claim 1 , wherein the at least one processor is further configured to access employment data indicative of skill sets associated with each of the first and second employees; and

assign the first product-related task to the first employee and the second product-related task to the second employee based on the skill sets of the first employee and the second employee and a type of the first service-improvement condition and a type of the second service-improvement condition.

11. The system of claim 1 , wherein the at least one processor is further configured to access employment ranking data associated with past performances of the first employee and the second employee; and

assign the first product-related task to the first employee and the second product-related task to the second employee based on the employment ranking data.

12. The system of claim 1 , wherein the at least one processor is further configured to:

determine prioritization of the first product-related task and the second product-related task based on urgency of the first service-improvement condition and the second service-improvement condition; and

assign the first product-related task to the first employee and the second product-related task to the second employee based on the determined prioritization of the first product-related task and the second product-related task.

13. The system of claim 1 , wherein the at least one processor is further configured to:

after assigning the first product-related task to the first employee first, analyze the plurality of images to determine that there is a need for a third product-related task to resolve a third service-improvement condition;

based on the plurality of images, determine that the third service-improvement condition is more urgent than the first service-improvement condition;

assign the third product-related task to the first employee; and

inform the first employee that the third product-related task has priority over the first product-related task.

14. The system of claim 1 , wherein the at least one processor is further configured to:

analyze the plurality of images to determine that the first service-improvement condition had been resolved prior to the arrival of the first employee; and

inform the first employee that the first product-related task has been cancelled.

15. The system of claim 1 , wherein the at least one processor is further configured to:

analyze the plurality of images to identify that the first product-related task has been completed by the first employee; and

update a repository of product-related tasks associated with the first employee based on the identification of the completion of the first product-related task.

16. The system of claim 15 , wherein the at least one processor is further configured to:

analyze the plurality of images to determine a performance quality level associated with the completion of the first product-related task; and

update a performance record associated with the first employee based on the determined performance quality level.

17. A method for processing images captured in a retail store and for automatically addressing detected conditions within the retail store, the method comprising:

receiving a plurality of images depicting a plurality of products displayed on a plurality of store shelves;

retrieving reference data specifying a desired state of the retail store;

using the reference data to detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products;

using the reference data to detect in the plurality of images an indicator of a second service-improvement condition relating to the plurality of products;

determining a first product-related task for addressing the first service-improvement condition;

determining a second product-related task for addressing the second service-improvement condition;

accessing a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and

assigning the first product-related task to the first employee and assign the second product-related task to the second employee.

18. The method of claim 17 , wherein:

when the first service-improvement condition and the second service-improvement condition include identified misplaced product, the method further comprises: assigning the first product-related task to the first employee and the second product-related task to the second employee based on product categories associated with the identified misplaced products;

when the first service-improvement condition and the second service-improvement condition are occlusion events, the method further comprises: assigning the first product-related task to the first employee and the second product-related task to the second employee based on occlusion categories associated with the occlusion events; and

when the first service-improvement condition is a need for cleaning and the second service-improvement condition is a need for rearrangement, the method further comprises: assigning the first product-related task to a robot employee and assigning the second product-related task to a human employee.

19. The method of claim 17 , wherein, when the first employee is a robot employee, the method further comprises:

obtaining data indicative of a current status of the robot employee for determining that the first service-improvement condition can be resolved by the robot employee; and

based on the obtained data, determining that the first service-improvement condition can be resolved by the robot employee, before assigning the first product-related task to the first employee.

20. A computer program product for processing images captured in a retail store and for automatically addressing detected conditions within the retail store, the computer program product being embodied in a non-transitory computer-readable medium and being executable by at least one processor, the computer program product including instructions for causing the at least one processor to execute a method comprising:

receiving a plurality of images depicting a plurality of products displayed on a plurality of store shelves;

retrieving reference data specifying a desired state of the retail store;

using the reference data to detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products;

using the reference data to detect in the plurality of images an indicator of a second service-improvement condition relating to the plurality of products;

determining a first product-related task for addressing the first service-improvement condition;

determining a second product-related task for addressing the second service-improvement condition;

accessing a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and

assigning the first product-related task to the first employee and assign the second product-related task to the second employee.