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SOURCE: AFI

Scientists from the Indian Space Research Organisation’s Space Applications Centre (ISRO-SAC), in collaboration with a partner institute, have successfully developed and tested an AI-based data model for a comprehensive airport monitoring system. The system is designed to automate aircraft tracking and enhance surveillance capabilities, representing a major leap forward in aviation monitoring and management.

The project involved analyzing air traffic at key Indian airports, including Ahmedabad, Mumbai, and Pune. To train their advanced data models, the research team utilized global datasets such as the CosmiQ Works RarePlanes dataset, which includes airports from 22 countries, the Airbus Aircraft Detection dataset, and imagery from Indian remote sensing satellites.

The research team employed YOLOv5 and YOLOv7, cutting-edge models from the “You Only Look Once (YOLO)” family of deep learning frameworks. These models are renowned for their speed and accuracy in object detection, including applications like identifying aircraft in satellite imagery.

The new AI-powered system offers transformative benefits for aviation monitoring, airport management, and security. According to the project report, it has the potential to Streamlined operations through real-time aircraft tracking and monitoring. Improved surveillance capabilities to address potential threats and ensure national security.

“This innovation has far-reaching implications for citizens,” an ISRO official explained. “It not only ensures improved airport operations but also contributes to national security and environmental sustainability.”

The research team aims to implement this AI solution across Indian airports, marking a significant step toward automated aviation management in the country. By leveraging Indian expertise in satellite imagery and AI, the system is set to revolutionize airport operations and enhance India’s standing in advanced aerospace and monitoring technologies.






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