Determining item mortality based on tracked environmental conditions during transit

A method for determining item mortality by a processor based on tracked environmental conditions during transit, the method comprising:

• receiving, by the processor, first sensor data from a first sensor for a first environmental condition experienced by a plurality of items during transit, the first sensor mounted to an outer transport container;
• receiving, by the processor, second sensor data for a second environmental condition experienced by the plurality of items during transit and different from the first environmental condition, the second sensor mounted to an inner transport container housed within the outer transport container;
• creating, by the processor, a neural net training data set by pairing historical data from the first and second sensor data and historical mortality data associated with each of a plurality of components of an item of the plurality of items;
• training, by the processor, a neural net using the neural net training data;
• generating, by the processor, a tiered mortality model for the item of the plurality of items using the neural net;
• generating, by the processor, mortality data for the item by comparing, using the generated tiered mortality model, the first sensor data to a first damage threshold and the second sensor data to a second damage threshold to determine whether a first component of the item in the plurality of items has degraded or failed and whether a second component of the item in the plurality of items has degraded or failed;
• based at least on the generated mortality data for the item in the plurality of items and disposition rules, determining, by the processor, an expected remaining lifespan for the item in the plurality of items;
• and
• based at least on the determined expected remaining lifespan for the item in the plurality of items, generating, by the processor, a disposition recommendation for the item in the plurality of items.

One or more computer storage devices media having computer-executable instructions stored thereon for determining item mortality based on tracked environmental conditions during transit, which, on execution by a computer, cause the computer to perform operations comprising:

• receiving first sensor data from a first sensor for a first environmental condition experienced by a plurality of items during transit, the first sensor mounted to an outer transport container;
• receiving second sensor data from a second sensor for a second environmental condition experienced by the plurality of items during transit and different from the first environmental condition, the second sensor mounted to an inner transport container housed within the outer transport container;
• creating a neural net training data set by pairing historical data from the first and second sensor data and historical mortality data associated with each of a plurality of components of an item of the plurality of items;
• training a neural net using the neural net training data;
• generating a tiered mortality model for the item of the plurality of items using the neural net;
• generating mortality data for the item by comparing, using the generated tiered mortality model, the first sensor data to a first damage threshold and the second sensor data to a second damage threshold to determine whether a first component of the item in the plurality of items has degraded or failed and whether a second component of the item in the plurality of items has degraded or failed;
• based at least on the generated mortality data for the item in the plurality of items and disposition rules, determining an expected remaining lifespan for the item in the plurality of items;
• and
• based at least on the determined expected remaining lifespan for the item in the plurality of items, generating a disposition recommendation for the item in the plurality of items.