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All Journal Warta Penelitian Perhubungan Journal of Innovation and Technology Journal of Applied Science, Engineering and Technology (J. ASET)
Arifianto, Ony
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Intelligent Eyes on the Battlefield: Developing an AI-Vision Based Military Vehicle and Infantry Detection System Wibowo, Pasha R A; Ummah , Khairul; Arifianto, Ony; Widagdo, Djarot; Riszal, Akhmad; Arif, Yanuar Zulardiansyah
Journal of Applied Science, Engineering and Technology Vol. 3 No. 2 (2023): December 2023
Publisher : INSTEP Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/jaset.v3i2.63

Abstract

The importance of accurate, real-time intelligence in modern warfare is crucial, especially in reconnaissance and surveillance operations. Currently, drones are widely used for reconnaissance, but generally rely only on the operator's ability to monitor operation targets. This research is aimed at developing an AI vision assistance system to enhance the ability to detect military vehicles and infantry. The method used is computer vision trained to recognize and differentiate several military objects. The YOLO model is used to detect and distinguish objects. To improve detection capabilities, the YOLO v8 model was retrained with an additional dataset sourced from battle recordings on the battlefield. The results show a detection accuracy rate of 95% in detecting vehicles and infantry under normal visual conditions. The model from this research can be used to enhance the capabilities of reconnaissance drones and the effectiveness of monitoring operations.
Intelligent Eyes on the Battlefield: Developing an AI-Vision Based Military Vehicle and Infantry Detection System Wibowo, Pasha R A; Ummah, Khairul; Arifianto, Ony; Widagdo, Djarot; Riszal, Akhmad; Arif, Yanuar Zulardiansyah; Sadono, Mahardi
Jurnal Inovasi Teknologi Vol 5 No 1 (2024): April
Publisher : Engineering Forum of Western Indonesian Government Universities Board (Forum Teknik, BKS-PTN Wilayah Barat) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The importance of accurate, real-time intelligence in modern warfare is crucial, especially in reconnaissance and surveillance operations. Currently, drones are widely used for reconnaissance, but generally rely only on the operator's ability to monitor operation targets. This research is aimed at developing an AI vision assistance system to enhance the ability to detect military vehicles and infantry. The method used is computer vision trained to recognize and differentiate several military objects. The YOLO model is used to detect and distinguish objects. To improve detection capabilities, the YOLO v8 model was retrained with an additional dataset sourced from battle recordings on the battlefield. The results show a detection accuracy rate of 95% in detecting vehicles and infantry under normal visual conditions. The model from this research can be used to enhance the capabilities of reconnaissance drones and the effectiveness of monitoring operations.
Analisis Risiko Bird Strike dengan Metode Sowden dan Metode MOORA di Bandara Internasional XYZ Nursani, Ima; Arifianto, Ony
Warta Penelitian Perhubungan Vol. 35 No. 2 (2023): Warta Penelitian Perhubungan
Publisher : Sekretariat Badan Penelitian dan Pengembangan Perhubungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/warlit.v35i2.2311

Abstract

Bandara XYZ merupakan bandara yang memiliki habitat alam yang sangat ramai akan keberadaan satwa liar, terutama burung. Interaksi antara pesawat dan burung dapat menimbulkan berbagai permasalahan, seperti bird strike, perubahan perilaku migrasi, dan ancaman terhadap kelestarian populasi jenis tertentu. Oleh karena itu, pengelolaan satwa liar dan operasional penerbangan merupakan isu yang kompleks dan penting untuk diatasi. Dalam melakukan penilaian risiko, digunakan tiga metode, yaitu metode Sowden di mana penilaian berdasarkan ukuran berat badan burung dan karakteristik sosial, metode MOORA yang merupakan metode penghitungan dengan mempertimbangkan lokasi burung berada, kemampuan terbang burung dan jumlah burung pada saat pengamatan. Berdasarkan analisa penghitungan dengan metode Sowden dan metode MOORA, yang kemudian dibuat analisis lanjutan dengan risk assessment, maka dapat diambil kesimpulan bahwa kemungkinan risiko bird strike di Bandara XYZ sangat tinggi karena beberapa jenis burung, seperti burung kuntul kerbau, cangak abu, cangak merah, dan blekok sawah banyak ditemukan di area airside dan landside. Hal ini ditunjukkan dengan adanya spesies burung yang memiliki skor tingkat bahaya sangat tinggi untuk pada penghitungan dengan kedua metode tersebut. Kemudian jika spesies tersebut mengalami tabrakan dengan pesawat, maka akan mengakibatkan dampak yang signifikan.
Co-Authors Arif, Yanuar Zulardiansyah DJAROT WIDAGDO, DJAROT Khairul Ummah Mahardi Sadono, Mahardi Nursani, Ima Riszal, Akhmad Ummah , Khairul Wibowo, Pasha R A