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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP9009

Gesture Control Drone:Using Gloves

Stream/Area:

-

Subject:

-

Paper ID:

IJSREMWP9009

Volume:

9 |

2 |

Feb 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

aF

ariz Faki1

Rs

Raiyyan shaikh2

MH

Mansoori Hanzala3

KS

Khan Sarah4

RW

Rahul Wargadhe5

ZS

Zuber Shaikh6

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Abstract

Gesture-controlled drones represent a significant advancement in human-computer interaction, allowing users to operate drones using simple hand movements without the need for traditional controllers. This technology utilizes computer vision, machine learning, and sensor-based systems to interpret gestures and translate them into drone commands such as takeoff, landing, movement, and hovering. A typical gesture-controlled drone employs a combination of cameras, accelerometers, gyroscopes, and deep learning models to recognize predefined gestures in real-time. Image processing techniques, such as OpenCV and deep neural networks, enhance the accuracy of gesture recognition, ensuring seamless communication between the user and the drone.

KEYWORDS

Gesture Recognition Drone Control Computer Vision.

Cite This Article

ariz Faki1, Raiyyan shaikh2, Mansoori Hanzala3, Khan Sarah4, Rahul Wargadhe5, Zuber Shaikh6, "Gesture Control Drone:Using Gloves," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 2, Feb 2025.

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Publication Date

8/1/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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