Flight Delay Prediction and Turnaround Optimisation Dashboard for Indian Airports

Objective: To develop an intelligent dashboard that predicts flight delays and optimises turnaround times at Indian airports, improving operational efficiency.

Problem & Context: Flight delays and inefficient turnaround processes are significant operational challenges in Indian aviation, impacting passenger satisfaction, airline profitability, and airport congestion. Factors such as weather, resource allocation, and regulatory constraints exacerbate these issues at major Indian airports like Delhi and Mumbai.

Approach & Methodology: The project will use historical flight data, real-time inputs, and predictive analytics to model delay causes and turnaround bottlenecks. The team will gather datasets from DGCA, airport sources, and open repositories, employ statistical and machine learning techniques, and design a user-friendly dashboard for operations managers.

Deliverables & Analysis: Key outputs include a delay prediction model, turnaround optimisation algorithms, and an interactive dashboard (using Power BI/Tableau) visualising actionable insights. Analysis will cover root causes, risk factors, and simulated scenarios to recommend operational improvements.

Business Impact & Decision: The dashboard will enable airline and airport operations teams to proactively manage delays, allocate resources efficiently, and improve turnaround time, informing real-time decisions and strategic planning for India's growing aviation sector.