CPC G06Q 50/02 (2013.01) [G01W 1/10 (2013.01); G05D 1/0214 (2013.01); G06F 3/0482 (2013.01); G06F 9/451 (2018.02); G06N 20/00 (2019.01); G06Q 10/06315 (2013.01); G06Q 10/087 (2013.01); G06Q 10/0832 (2013.01); G06Q 10/0833 (2013.01); G06Q 10/0836 (2013.01); G06Q 10/08345 (2013.01); G06Q 10/08355 (2013.01); G06Q 30/0202 (2013.01); G06Q 30/0206 (2013.01); G06Q 30/0283 (2013.01); G06Q 30/0605 (2013.01); G06Q 30/0641 (2013.01); G06Q 40/04 (2013.01); G06V 20/188 (2022.01); G08G 1/096805 (2013.01); G06Q 50/30 (2013.01); G16Y 10/05 (2020.01)] | 42 Claims |
1. A method for training and applying a machine-learned model in an online agricultural system comprising:
generating, for each of a set of crop producers, a crop product listing within an online agricultural system for a crop product type, the crop product listing including a reported quality specification of the crop product, a quantity of the crop product, and a location of the crop product;
generating a training set of data comprising remote sensor data corresponding to the crop product type and associated historic quality specification data corresponding to the crop product type;
training a machine-learned model configured to predict a quality specification for the crop product type based on remote sensor data corresponding to the crop product type using the training set of data;
receiving, from a prospective acquiring entity, a request to acquire the crop product, the request including a quantity requirement of the crop product, a quality requirement of the crop product, and a delivery location for the crop product; and
in response to identifying one or more crop product listings that satisfy the quality requirement included within the received request:
accessing remote sensing data from one or more remote sensors corresponding to the locations included within the identified crop product listings;
applying the trained machine-learned model to the accessed remote sensing data to verify the reported quality specification included within the identified crop product listings;
for each of the identified crop product listings, calculating a supplier trustworthiness based on a difference between the reported quality specification included within the identified crop product listing and a corresponding verified quality specification; and
in response to the supplier trustworthiness score for each of the identified crop product listings being above a threshold score, modifying an interface of a device of the prospective acquiring entity to display the identified crop product listings.
|