SkyOps
When Sky makes you wait, we make a way for you.
The problem SkyOps solves
SkyOps is designed to optimize airline operations by addressing key challenges in tail assignment, fuel efficiency, real-time decision-making, cost reduction, and passenger experience. One of the major problems it solves is the tail assignment problem, where aircraft (tails) must be allocated to flights while considering factors like maintenance schedules, crew availability, and delays. By leveraging AI-driven optimization, SkyOps ensures efficient aircraft utilization, reduces delays, and minimizes fuel consumption.
Additionally, the project focuses on fuel and emission optimization by integrating AI-powered flight scheduling and routing. This reduces unnecessary fuel burn and helps airlines track CO₂ emissions for regulatory compliance, contributing to sustainability goals. Real-time data analytics, powered by Firebase, enable dynamic adaptation to disruptions such as weather changes or flight delays, ensuring seamless operations.
From a financial and operational perspective, SkyOps helps airlines reduce costs by minimizing flight cancellations, optimizing aircraft allocation, and implementing predictive maintenance to prevent unnecessary grounding. Finally, by improving tail assignment and scheduling, the system enhances the passenger experience by reducing delays and ensuring better flight connectivity. By integrating AI, Django, and Firebase, SkyOps creates a smart, sustainable, and efficient airline management system that enhances both operational efficiency and environmental responsibility.
Challenges we ran into
SkyOps faced several challenges, particularly in 3D/VR integration, tail assignment optimization, and flight delay handling.
Integrating 3D and VR for flight visualization and maintenance simulations required high-performance rendering and seamless backend integration. Ensuring smooth interactions, device compatibility, and real-time updates was challenging, requiring optimization through WebGL, Three.js, and Unity WebXR.
Solving the tail assignment problem was complex due to factors like maintenance schedules, crew availability, and fuel efficiency. A static allocation approach wouldn’t work, so we developed an adaptive AI algorithm using graph-based scheduling and reinforcement learning to dynamically optimize aircraft assignments.
Handling flight delays involved predicting and minimizing disruptions caused by weather, technical faults, or congestion. Using real-time Firebase data streaming and AI-driven forecasting, we developed a decision-support system to suggest optimal recovery strategies and prevent cascading delays.
Despite these challenges, SkyOps successfully integrates Django, Firebase, AI-driven optimization, and 3D/VR to create a smart, efficient, and sustainable airline management solutions.
Tracks Applied (2)
AI in Airline Operations
IBS Software
Sustainability
Technologies used