Abstract: An enhanced system and methods implement intelligent decision making autonomous control of Unit Load Devices (ULDs) within a prescribed airport perimeter, such as an airport. An Intelligent Autonomous ULD Control Tower (IAUCT) receives demands for ULDs, maintains a ULD repository data store, and controls ULDs within the prescribed airport perimeter. The IAUCT identifies at least a ULD state and a specific ULD position for the ULD within a prescribed airport perimeter, and stores the ULD state and specific ULD position in a ULD repository data store. The IAUCT selects a next action for the ULD based upon the demand for ULDs and based upon the ULD state and specific ULD position and the demand for ULDs within the perimeter area. The IAUCT dynamically identifies an optimized route for moving the ULD within the prescribed airport perimeter based upon the selected next action.

Abstract: Logistics are optimized for delivering a product within a product distribution network. A computer receives order data, the order data includes order information and a delivery location of a product ordered by a user. The order data further includes an order history of the user including order returns or cancelations. Using data analytics, the order data is analyzed to determine a logistics plan for the delivery of the product. A probability of return of the product is calculated, and a probability of re-order of the product is calculated. As part of the logistics plan and based on the analyzing of the order data, a recommended storage facility is generated for a second delivery location resulting from a re-routing of the delivery of the product, in response to the order being canceled.

Abstract: Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.

Abstract: Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.