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IECE Transactions on Intelligent Systematics, 2024, Volume 1, Issue 2: 69-78

Free Access | Research Article | 23 September 2024
1 Interdisciplinary Research Centre for Aviation and Space Exploration (IRCASE), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Kingdom of Saudi Arabia
2 Electronic Engineering Department, Maynooth International Engineering College (MIEC), Maynooth University, Maynooth, Co. Kildare, Ireland
3 Aerospace Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Kingdom of Saudi Arabia
* Corresponding author: Ghulam E Mustafa Abro, email: [email protected]
Received: 13 september 2024, Accepted: 21 September 2024, Published: 23 September 2024  

Abstract
A Novel simulation framework using self-governing drones is used to locate and reduce unauthorized drones in interior environments. The recommended method uses Received Signal Strength Indicator (RSSI) to identify an alien agent drone, which has different signal characteristics than the approved swarm of UAVs. Real-time threat detection is possible with this technology. After detecting the drone, the swarm organizes itself to encircle and besiege it for 10 seconds, making it inert before returning to their original positions. This unique solution uses RSSI to quickly identify and mitigate enclosed area concerns. It provides a reliable and effective indoor drone security solution. The simulation results show that the approach works in delicate environments including warehouses, laboratories, and other indoor facilities. This study advances unmanned aerial system (UAS) autonomous swarm intelligence and security procedures.

Graphical Abstract
Signal Strength-Based Alien Drone Detection and Containment in Indoor UAV Swarm Simulations

Keywords
Autonomous Drone Swarms
RSSI
Indoor Security
Unmanned Aerial Vehicle (UAVs) and Mitigation

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Cite This Article
APA Style
Abro, G., E., M., Ali, Z., A. & Abdallah, A., M. (2024). Signal Strength-Based Alien Drone Detection and Containment in Indoor UAV Swarm Simulations. IECE Transactions on Intelligent Systematics, 1(2), 69-78. https://doi.org/10.62762/TIS.2024.807714

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