Abstract: A high-demand product processing system may include a seller device associated with a prospective seller, and a high-demand product marketplace server to store historical product data for a given product. The historical product data may include historical product prices and quantities at different times. The server may operate a web crawler to crawl e-commerce websites for current product data for the given product. The current product data may include current product prices and quantities at each of the e-commerce websites. The server may operate a machine learning algorithm to predict whether the given product will be a high-demand product based upon the historical product data and the current product data, and when so, generate an offer-to-purchase the high-demand product, communicate the offer-to-purchase to the seller device, and operate a marketplace to sell the high-demand product at a sales price higher than an offer price associated with the offer-to-purchase.

Abstract: A product reclamation system may include a mobile device associated with a given user. The mobile device may be configured to obtain an image of a product to be discarded. The system may also include a reclamation server configured to obtain the image of the product from the mobile device, and apply image recognition techniques to the obtained image to determine if the product is a reclaimable product. The server is configured to, when the product is determined to be a reclaimable product, operate a machine learning algorithm to determine a reclamation value for the reclaimable product, communicate the reclamation value to the mobile device, and prompt the given user, via the mobile device, to send the reclaimable product to a reclamation facility in exchange for the reclamation value, and generate and communicate a digital promotion to the mobile device based upon sending the product to the reclamation facility.

Abstract: A returned goods processing system may include a camera configured to acquire human pose image data of a given user while processing a returned item. The system may also include a returned goods processing server configured to store reference human pose image data of sample users while processing returned items. The stored human pose image data may be indicative of compliance with an acceptable return processing procedure. The returned good processing server may also be configured to compare the acquired human pose image data with the stored reference human pose image data to determine compliance with the acceptable return processing procedure, and generate a notification based upon the comparing. The returned goods processing server may also be configured to perform machine learning to update the stored reference human pose image data based upon the acquired human pose image data.