FLYTR

Team HIT IT

Inspiration

The complexity of air cargo tracking inspired us to create a solution that brings clarity and efficiency to the process. With carriers, ground handlers, and ramp agents working in isolated systems, we saw the need for real-time visibility and streamlined data sharing. We wanted to revolutionize the way cargo is tracked, reducing delays and manual work, while making the entire logistics chain more transparent and efficient.

What it does

FLYTR simplifies air cargo tracking by providing carriers with real-time visibility and actionable insights across the entire shipment journey. It leverages IATA’s ONE Record standard for seamless data sharing between stakeholders and incorporates Cargo IQ’s Flight Route Map to monitor every stage of the shipment process. With FLYTR, users can track performance milestones, ensure compliance with industry standards, and predict potential delays, all in one platform.

How we built it

FLYTR uses the Flight Route Map of Cargo IQ MOP for tracking shipment and flight status. The milestones of the framework are added to the solution as tracking steps. These milestones represent the actions of various stakeholders, including carriers, ground handlers, and ramp agents. Each operation is recorded as an event on the ONE Record server. As new actions are performed, the data is updated, and when all conditions are met, the shipment progresses through the Flight Route Map. Key messages, such as UWS and MVT, which change the flight status, are mapped to the ONE Record data model and stored on the server.

FLYTR is programmed in Java, built with Maven, and managed through GitHub for code storage and version control.

Challenges we ran into

We faced technical difficulties with internet access at the beginning of the Hackathon, which prevented us from accessing critical resources for coding and editing our video. Fortunately, the issue was resolved, allowing us to resume development without losing much time. Additionally, integrating different data standards and ensuring smooth communication between disparate systems required careful design and testing to ensure accuracy.

Mapping the XML and AHM messages to the ONE Record data model proved to be a technical challenge. These message formats are complex, and ensuring they aligned with ONE Record's modern data-sharing standard required precise mapping and testing. Integrating different data formats to maintain accuracy in the system was crucial but challenging, especially when considering the various stakeholders involved.

Accomplishments that we're proud of

One of our proudest accomplishments is successfully building FLYTR despite the technical challenges and time constraints. We’re particularly proud of integrating Cargo IQ’s Flight Route Map and mapping XML and AHM messages to the ONE Record data model. This required navigating through complex data formats and ensuring seamless communication between different stakeholders, which wasn’t easy.

Another key achievement was how we worked together as a team during the hackathon, especially managing to solve critical issues while working under pressure and with minimal sleep. We pushed through those sleepless nights, and seeing our solution come together in the end was incredibly rewarding.

What we learned

Throughout the development of FLYTR, we gained a deeper understanding of the complexities involved in the Cargo iQ MOP and the importance of standardized data models like ONE Record. We also learned how critical seamless communication and real-time visibility are to improving operational efficiency.

What's next for FLYTR

Moving forward, we would want to expand FLYTR scope by including more or all of the Cargo iQ MOP. This way, tracking for flights and shipments can be more precise and according to industry standards. With the broader scope FLYTR can include more stakeholders of the air freight business.

Another way of improving the solution would be to integrate machine learning to offer more precise predictive insights, allowing carriers to anticipate potential delays and optimize their operations even further.