Airspace Monitoring Around Airports Using Neural Network-Based Systems and Analysis of Predictive Capabilities and Real-Time Data Integration

Airspace monitoring is a crucial aspect of aviation safety and efficiency, focusing on the continuous observation and management of aircraft within controlled airspace to prevent collisions, optimizing flight paths, and ensuring smooth operations. Traditional airspace monitoring systems, which rely on radar and automatic dependent surveillance-broadcast technology, face challenges in managing the increasing volume of air traffic, signal interference, and the integration of diverse data sources such as weather information and flight plans. In response to these challenges, this research explores the development of a neural network-based system aimed at enhancing airspace monitoring around airports and improving overall aviation safety and efficiency.