Military Grade FPV Drone for Enemy Recognition: Precision
An FPV (First Person View) drone is a remotely piloted aircraft that provides the operator with a real-time view of the drone's flight through a video transmission. This offers a more immersive and engaging experience, as the operator can feel as though they are flying the drone themselves. FPV drones are commonly used in various industries, including photography, videography, agriculture, and search and rescue. They are also popular among hobbyists who enjoy the thrill of racing and performing aerial acrobatics. This paper aims to develop a military-grade FPV drone system for enemy recognition using OpenCV algorithms. The system uses video feeds from the drone's cameras and processes them in real-time to identify potential threats based on predefined criteria. The drone's purpose is to support military operations with real-time aerial surveillance and reconnaissance. Operators can view the drone's surroundings in real-time thanks to a high definition camera that sends live video footage to a base station. The drone also has cutting-edge GPS hardware, which enables it to carry out autonomous tasks including pre-planned flight patterns and automatic return to base operations. The drone is perfect for quick and effective reconnaissance operations due to its ability to fly at high altitudes and speeds. The drone's sturdy construction guarantees its resilience and durability in the face of adverse weather and collisions. Furthermore, the drone's encrypted communication lines shield against unauthorized access and hacking attempts.
Authors
- Kumari Jyoti
- Ankit Garg (ORCID: https://orcid.org/0000-0001-5377-8519)
- Poornima Arya
- Nandini Prasad K S
- Mandar Jatkar (ORCID: https://orcid.org/0000-0003-2109-9487)
- Prajjwal Kumar
Institutions
- Dr. Hari Singh Gour University (IN)
Publication Details
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1109/emergin63207.2024.10961345
- Citations
- 2
- Primary Topic
- Infrared Target Detection Methodologies
- Type
- article
- Field-Weighted Citation Impact
- 2.60