TITLE: A Time-Temperature Dataset for the Strawberry Cold Chain Across Multiple Shipments and Locations 

ABSTRACT: This article describes location aware temperature profiles from six
strawberry shipments across the continental United States. Three pallets were
instrumented in each shipment with three vertically placed loggers to take a
longitudinal and latitudinal snapshot of 9 strategically different locations
(including the top, middle and bottom layers of the pallets placed in the back,
middle and the front of the shipping container) for a combined 54 measurement
points across shipments of varying lengths. The sensors were instrumented in
the field, right at the point of harvest, recorded temperatures every every 5
to 10 minutes depending on the shipment, and uploaded their data periodically
via cellular radios on each device. The data is a result of significant
collaboration between stakeholders from farmers to distributors to retailers to
academics, which can play an important role for researchers and educators in
food engineering, cold-chain, machine learning, and data mining, as well as in
other disciplines related to food and transportation.
This article describes location aware temperature profiles from six
strawberry shipments across the continental United States. Three pallets were
instrumented in each shipment with three vertically placed loggers to take a
longitudinal and latitudinal snapshot of 9 strategically different locations
(including the top, middle and bottom layers of the pallets placed in the back,
middle and the front of the shipping container) for a combined 54 measurement
points across shipments of varying lengths. The sensors were instrumented in
the field, right at the point of harvest, recorded temperatures every every 5
to 10 minutes depending on the shipment, and uploaded their data periodically
via cellular radios on each device. The data is a result of significant
collaboration between stakeholders from farmers to distributors to retailers to
academics, which can play an important role for researchers and educators in
food engineering, cold-chain, machine learning, and data mining, as well as in
other disciplines related to food and transportation.
A Time-Temperature Dataset for the Strawberry Cold Chain Across Multiple Shipments and Locations
http://arxiv.org/abs/2103.12895v1