Acoustic Based Drone Identification and Classification

Drones have emerged as a gadget of the common man these days. Sectors ranging from agriculture, security, home delivery cinema industry, etc. are using drones to optimize their performance in respective domains. Such a wide and easy accessibility of drones have made them accessible to the users for...

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Bibliographic Details
Published in2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) Vol. 1; pp. 1 - 5
Main Authors Agarwal, Anchal, Dhoundiyal, Praveen, Sharma, Vikrant, Vats, Satvik
Format Conference Proceeding
LanguageEnglish
Published IEEE 29.08.2024
Subjects
Acoustics
Computational modeling
Computers
Convolutional Neural Network (CNNs)
Deep learning
Distance measurement
Drone audio
Drones
Electromagnetics
Machine Learning
Motion pictures
Neural networks
Object recognition
Security
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Summary:Drones have emerged as a gadget of the common man these days. Sectors ranging from agriculture, security, home delivery cinema industry, etc. are using drones to optimize their performance in respective domains. Such a wide and easy accessibility of drones have made them accessible to the users for illegal and malicious use as well. Moreover, there are certain areas which are sensitive from a security point of view therefore the entry of drones to such religions is restricted legally. But it is a challenging task to detect intruder drones in a sensitive region. A drone being a significantly small flying object is difficult to visually locate and identify manually. However, there are acoustics, thermal and electromagnetic signatures, which if detected can be used to mark their presence in the nearby region. In this article we have proposed an audio-based model for drone identification which can identify the presence of a drone in the vicinity if humming audio of the drone is found in the acoustics of nature.
DOI:10.1109/ICEECT61758.2024.10739288