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

    Free to Read | Research Article | 23 September 2024
    Signal Strength-Based Alien Drone Detection and Containment in Indoor UAV Swarm Simulations
    by
    IECE Author Ghulam E Mustafa Abro 1 *
    IECE Author Zain Anwar Ali 2
    IECE Author Ayman M Abdallah 1,3
    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 protected]
    DOI: https://doi.org/10.62762/TIS.2024.807714
    Received: 13 september 2024, Accepted: 21 September 2024, Published: 23 September 2024  
    Cited by: 1  (Source: Google Scholar)
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    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
    Funding
    The authors express gratitude for the assistance rendered by the Interdisciplinary Research Centre (IRC) for Aviation and Space Exploration at King Fahd University of Petroleum and Minerals (KFUPM) in advancing this research. The project is financed by IRC for Aviation and Space Exploration as part of an internally sponsored initiative under the cost centre INAE2408.
    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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    IECE Transactions on Intelligent Systematics

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