The importance of effective and precise Military Airports Detection is crucial in modern defense planning and strategies where timely information can be critical in times of increased tension. The present project goes about advancing the detection of Military airports in the Indian Subcontinent by incorporating YOLO v9 architecture and Satellite images on the edge to utilize the Military airports detection. Manual methods of Military Airports can be detected slow and also very costly. This process also prone to error. Time consumed to identify the effect of enemy attacks. Overcoming such constraints, this project intends to build an automated system which makes use of high-resolution satellite images form Google Earth Pro with advance object detecting algorithms. In such an integrated framework, a high-resolution image trained YOLO v9 model will be embedded in an edge device Nvidia jetson nano enables fast detection of Military airports and is less vulnerable to errors. High-resolution satellite imagery acquired from the Google Earth Pro offers the ability to train the YOLO v9 model. By addressing the inefficiencies in the conventional detection of Military airports, the present project seeks to improve accuracy, efficiency, and cost-effectiveness in Military airport detection.