We envision an AI based solution to proactively manage irregular operations in the logistics supply chain. Cargo logistics are heavily dependent on information supplied by various key players. This model has not changed in decades. Relevant information, while useful, is often fragmented and requires a measure of expertise to piece together a summary of what happened – flight delayed by weather, missing cargo due to missed connecting flights, and the list goes on
What it does
Enter Air J.A.R.V.I.S. (Java-based automated rebooking visual integrated system) an AI based solution to help the airline and forwarder understand precisely where the shipment is and when it will arrive at destination. From an administrative POV Air J.A.R.V.I.S. centralizes flight information, shipment adjustments and communication to all participants. This solution fully addresses challenge #1 by updating Track and Trace on the customer side when action is taken by Air J.A.R.V.I.S. The Air J.A.R.V.I.S. data models contain: • Weather information • Historical flight information • Booking behavior • Live flight GPS information • Air waybill information Air J.A.R.V.I.S automates rebooking on behalf of the airline and notifies all OneRecord subscribers of the change. The system also provides a percentage score for probability of success using the data points. If a downline station is experiencing serious weather problems, Air J.A.R.V.I.S. will suggest a new route. If a connecting flight is missed, Air J.A.R.V.I.S. is on the job determining the best path to the destination.
How I built it
The system was built using Java backend, Angular front end and contains: • OneRecord API • Aviation-Edge API for flight GPS tracking • Google maps API • Openweathermap API
Challenges I ran into
Time constraints prevented a full implementation of an AI model.
Accomplishments that I'm proud of
The great thing about this system is the simplified interface with heavy lifting happening in the background. The notification system to OneRecord subscribers and push notifications to customers is a great benefit as well. In an environment that is seeing reduced resources due to COVID-19, this system alleviates the additional workload on call centers.
What I learned
Collaborative efforts between time zones can be challenging in a virtual environment. Coffee is great and small pockets of sleep can increase your efficiency and creativity.
What's next for AIR J.A.R.V.I.S.
- Collaborate with other airlines to confirm we are capturing the right data points.
- Run a pilot project