DESIGN AND IMPLEMENTATION OF A PROTOTYPE COMPUTER VISION-BASED OMNIDIRECTIONAL DRONE DETECTION SYSTEM
Drones (Unmanned Aerial Vehicles, UAVs) are increasingly utilized across various sectors due to their benefits and ease of use. However, they also pose safety and security risks to the public and violate airspace. Additionally, drones are difficult to detect with radar because of their small size...
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| Format: | Final Project |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/82173 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Drones (Unmanned Aerial Vehicles, UAVs) are increasingly utilized across various
sectors due to their benefits and ease of use. However, they also pose safety and
security risks to the public and violate airspace. Additionally, drones are difficult
to detect with radar because of their small size and their typically non-metal
composite materials. This research aims to develop a drone detection system using
computer vision. The method involves creating a cost-effective and modular drone
detector prototype for massive application. This research successfully developed a
drone detection system using SSD MobileNetv2 on TensorFlow Lite, Raspberry Pi
4B, and a multi-camera. The system can be built cost-effectively and can effectively
perform real-time omnidirectional detection with a precision of 0.53, a confidence
score of 0.57, an FPS of 0.40, and a display delay of 3.70 seconds, detecting drones
with a minimum bounding box size of 40x30 pixels. The results of this research can
be used as a basis for developing affordable and efficient anti-drone technology. |
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