Systems and methods for item management
An apparatus including one or more cameras, a deposit region, one or more processors, and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform certain operations. The operations include receiving image data of one or more items inserted into the deposit region by a user, the image data captured by the one or more cameras when the one or more items are in the deposit region. The operations also include classifying the one or more items as one or more types based at least on the image data. The operations additionally include determining a compensation offer based at least on the one or more types of the one or more items. The operations further include presenting the compensation offer to the user. The operations additionally include, when the user accepts the compensation offer, compensating the user according to the compensation offer. The operations further include, when the user declines the compensation offer and chooses to dispose the one or more items, disposing the one or more items. Other embodiments are described.
1. An apparatus comprising:
one or more cameras;
a deposit region;
one or more processors; and
one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising:
receiving image data of one or more items inserted into the deposit region by a user, the image data captured by the one or more cameras when the one or more items are in the deposit region;
classifying the one or more items as one or more types based at least on the image data;
determining a compensation offer based at least on the one or more types of the one or more items;
presenting the compensation offer to the user;
when the user accepts the compensation offer, compensating the user according to the compensation offer; and
when the user declines the compensation offer and chooses to dispose the one or more items, disposing the one or more items.
2. The apparatus of claim 1 , wherein determining the compensation offer further comprises:
determining one or more assigned values corresponding to the one or more items based at least on the one or more types; and
determining the compensation offer based at least on the one or more assigned values corresponding to the one or more items.
3. The apparatus of claim 2 , wherein the one or more assigned values are determined based at least on a social value or a market value.
4. The apparatus of claim 2 , wherein the one or more assigned values are determined based at least on a regression analysis.
5. The apparatus of claim 1 , wherein classifying the one or more items as the one or more types further comprises:
classifying the one or more items as the one or more types based at least on the image data using a convolutional recurrent neural network.
6. The apparatus of claim 1 , wherein the operations further comprise:
receiving user identifying data; and
identifying the user based on the user identifying data and stored user data for the user.
7. A computer-implemented method comprising:
receiving image data of one or more items inserted into a deposit region by a user, the image data captured by one or more cameras when the one or more items are in the deposit region;
classifying the one or more items as one or more types based at least on the image data;
determining a compensation offer based at least on the one or more types of the one or more items;
presenting the compensation offer to the user;
when the user accepts the compensation offer, compensating the user according to the compensation offer; and
when the user declines the compensation offer and chooses to dispose the one or more items, disposing the one or more items.
8. The computer-implemented method of claim 7 , wherein determining the compensation offer further comprises:
determining one or more assigned values corresponding to the one or more items based at least on the one or more types; and
determining the compensation offer based at least on the one or more assigned values corresponding to the one or more items.
9. The computer-implemented method of claim 8 , wherein the one or more assigned values are determined based at least on a social value or a market value.
10. The computer-implemented method of claim 8 , wherein the one or more assigned values are determined based at least on a regression analysis.
11. The computer-implemented method of claim 7 , wherein classifying the one or more items as the one or more types further comprises:
classifying the one or more items as the one or more types based at least on the image data using a convolutional recurrent neural network.
12. The computer-implemented method of claim 7 further comprising:
receiving user identifying data; and
identifying the user based on the user identifying data and stored user data for the user.
13. The computer-implemented method of claim 12 further comprising:
determining a user compensation preference for the user based on the stored user data.
14. One or more non-transitory computer-readable media comprising computing instructions that, when executed on one or more processors, cause the one or more processors to perform operations comprising:
receiving image data of one or more items inserted into a deposit region by a user, the image data captured by one or more cameras when the one or more items are in the deposit region;
classifying the one or more items as one or more types based at least on the image data;
determining a compensation offer based at least on the one or more types of the one or more items;
presenting the compensation offer to the user;
when the user accepts the compensation offer, compensating the user according to the compensation offer; and
when the user declines the compensation offer and chooses to dispose the one or more items, disposing the one or more items.
15. The one or more non-transitory computer-readable media of claim 14 , wherein determining the compensation offer further comprises:
determining one or more assigned values corresponding to the one or more items based at least on the one or more types; and
determining the compensation offer based at least on the one or more assigned values corresponding to the one or more items.
16. The one or more non-transitory computer-readable media of claim 15 , wherein the one or more assigned values are determined based at least on a social value or a market value.
17. The one or more non-transitory computer-readable media of claim 15 , wherein the one or more assigned values are determined based at least on a regression analysis.
18. The one or more non-transitory computer-readable media of claim 14 , wherein classifying the one or more items as the one or more types further comprises:
classifying the one or more items as the one or more types based at least on the image data using a convolutional recurrent neural network.
19. The one or more non-transitory computer-readable media of claim 14 , wherein the operations further comprise:
receiving user identifying data;
identifying the user based on the user identifying data and stored user data for the user; and
determining a user compensation preference for the user based on the stored user data.
20. The apparatus of claim 6 , wherein the operations further comprise:
determining a user compensation preference for the user based on the stored user data.