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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah Mikrotek Jurnal Simantec REKAYASA Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) International Journal of Science, Engineering and Information Technology Journal of Technology and Informatics (JoTI) Jurnal Informatika: Jurnal Pengembangan IT Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Dafid, Ach
Program Studi Teknik Mekatronika, Fakultas Teknik, UniversitasTrunojoyo Madura Jl. Raya Telang, PO BOX 2, Kamal, Bangkalan - 69162
Aerospace Engineering Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics Public Health Social Sciences Other

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A Real-Time Human-Drone Interaction System for Cornfield Perimeter Monitoring Using Hand Gesture Control Fadzillah Akbar Subkhi; Muhammad Fuad; Sri Wahyuni; Achmad Imam Sudianto; Vivi Tri Widyaningrum; Ach. Dafid
Journal of Technology and Informatics (JoTI) Vol. 8 No. 1 (2026): Vol. 8 N. 1 (2026)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v8i1.1314

Abstract

Perimeter monitoring in agricultural fields is essential for maintaining security and ensuring continuous observation of field conditions. This study develops a real-time human–drone interaction system using hand-gesture recognition based on MediaPipe Hands and a Support Vector Machine (SVM) classifier. A custom dataset of 24,000 images across 12 gesture classes was collected and converted into 42 hand landmarks (x, y, z), normalized relative to the wrist point. The SVM model with an RBF kernel was trained using an 80:20 split and achieved a testing accuracy of 99.18%. The system operates at 109 FPS with an average latency of 9.16 ms, enabling rapid and reliable drone responses to gesture commands. Field testing in a cornfield with FPV camera visualization demonstrated that the system consistently recognized gestures in varying outdoor lighting, allowing drones to execute precise perimeter checks and maneuvers. These results highlight the significant potential of integrating gesture recognition with drone control, providing a practical, real-world solution that advances smart farming, increases agricultural efficiency, and supports technological progress toward Sustainable Development Goals. The proposed system thus offers a lightweight, responsive, and impactful tool for modern agricultural perimeter monitoring.
Co-Authors Achmad Fiqhi Ibadillah Achmad Imam Sudianto Adi Kurniawan Adi Kurniawan Saputro Andharini Dwi Cahyani Andriansyah, Adi Doni Abdul Fatah Fadzillah Akbar Subkhi Faikul Umam Fifin Ayu Mufarroha Firmansyah Adiputra Firmansyah Adiputra Hairil Budiarto Hairil Budiarto Hairil Budiarto Ibnu Irawan Ika Oktavia Suzanti irni ri'khah juliarti Izzuddin Khusnul Fatimah Kukuh Winarso Kurniawan, Denni M Latif Maolana, Firman Morshed, Md Monzur Morshed, Md. Monzur Muhammad Fuad Ponco Siwindarto Rullie Annisa Sholeh, Mahrus Siswojo, Bambang Sitepu Debora , Ribka Sri Wahyuni Sri Wahyuni Sudianto, Achmad Imam Sukri, Hanifudin Sulaiman, Yoga Aulia Sumarto SUTIKNO Thinakaran, Rajermani Triwidyaningrum, Vivi Vivi Tri Widyaningrum Weny Findiastuti WENY FINDIASTUTI, WENY Yuli Panca Asmara Yusuf, Ahcmad Ziyyad Yassar