ULD & dangerous goods check

ULD build up
flight staging and loading monitoring
live built up ULD tracking
IOT sensor integrations
data integrations
airport performance data
IOT integrations
weather data
location history

Inspiration

We integrated data from the following challenges to build an end-to-end user journey of a shipment.

1) Jettainer ULD - mock data from ULD tracker & IOT sensors on the shipment level 2) DG autocheck

What it does

1) handles build up: verifies shipment DG 2) cross checks temp requirement between shipments in a ULD 3) integrates with awb data 4) removes false positives (IOT sensors tend to generate 80% false positives) 5) integrates weather data

How we built it

build physics engine to predict excursions in temperature
integrate with DG-autocheck API
build rule engine for recommended actions based on SHC and ULD type

Challenges we ran into

making sure physics prediction engine is accurate
many false positives on IOT sensors

Accomplishments that we're proud of

prediction engine
one-record compliant data models
using location data to understand scope of responsibility (when a shipment is in the possession of an airline, and when it isn't)