TY - GEN
T1 - AI-Driven Efficient and Reliable Anti-UAV Monitoring System Using Sensor Data Fusion
T2 - 9th International Conference on Soft Computing: Theories and Applications, SoCTA 2024
AU - Verma, Sourabh
AU - Verma, Om Prakash
AU - Gupta, Himanshu
AU - Sharma, Tarun Kumar
AU - Agarwal, Saurabh
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - The rising use of unmanned aerial vehicles (UAVs) has introduced benefits across industries and significant threats like espionage, smuggling, and airspace violations, necessitating effective anti-drone solutions. This study explores acoustic, RF, radar, vision-based, and multi-modal approaches for drone detection, each with unique strengths and challenges. Multi-modal sensor fusion addresses individual limitations, enhancing detection accuracy, robustness, and real-time tracking. Advanced machine learning algorithms and diverse datasets further improve system reliability, tackling issues like environmental interference and stealth drone detection. This work provides a deep study for scalable and efficient anti-drone systems, ensuring public safety and securing critical infrastructure in evolving UAV scenarios.
AB - The rising use of unmanned aerial vehicles (UAVs) has introduced benefits across industries and significant threats like espionage, smuggling, and airspace violations, necessitating effective anti-drone solutions. This study explores acoustic, RF, radar, vision-based, and multi-modal approaches for drone detection, each with unique strengths and challenges. Multi-modal sensor fusion addresses individual limitations, enhancing detection accuracy, robustness, and real-time tracking. Advanced machine learning algorithms and diverse datasets further improve system reliability, tackling issues like environmental interference and stealth drone detection. This work provides a deep study for scalable and efficient anti-drone systems, ensuring public safety and securing critical infrastructure in evolving UAV scenarios.
UR - https://www.scopus.com/pages/publications/105016244486
UR - https://www.scopus.com/pages/publications/105016244486#tab=citedBy
U2 - 10.1007/978-981-96-5955-5_52
DO - 10.1007/978-981-96-5955-5_52
M3 - Conference contribution
AN - SCOPUS:105016244486
SN - 9789819659548
T3 - Lecture Notes in Networks and Systems
SP - 613
EP - 623
BT - Soft Computing
A2 - Kumar, Rajesh
A2 - Verma, Ajit Kumar
A2 - Verma, Om Prakash
A2 - Rajpurohit, Jitendra
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 27 December 2024 through 29 December 2024
ER -