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All Journal Diksa : Jurnal Pendidikan Bahasa dan Sastra Indonesia INTEGRITAS : Jurnal Pengabdian REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) SPIN: Jurnal Kimia & Pendidikan Kimia Jurnal Abdimas Kartika Wijayakusuma Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) Kajian Sastra Nusantara Linggau ( KASTRAL) Internet of Things and Artificial Intelligence Journal Jurnal Penelitian Pendidikan Indonesia
Puspita, Heni
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Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Other

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Journal : Internet of Things and Artificial Intelligence Journal

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360-degree Image Processing on NVIDIA Jetson Nano Satyawan, Arief Suryadi; Utomo, Prio Adjie; Puspita, Heni; Wulandari, Ike Yuni
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.722

Abstract

A wide field of vision is required for autonomous electric vehicles to operate object-detecting systems. By identifying objects, it is possible to imbue the car with human intelligence, similar to that of a driver, so that it can recognize items and make decisions to prevent collisions with them. Using a 360-degree camera is a wonderful idea because it can record events surrounding the car in a single shot. Nevertheless, 360º cameras produce naturally skewed images. To make the image appear normal but have a bigger capture area, it is required to normalize it. In this study, NVIDIA Jetson Nano is used to construct software for 360-degree image normalization processing using Python. To process an image in real-time, first choose the image shape mapping that can give information about the entire item that the camera collected. Then, choose and apply the mapping. Using Python on an NVIDIA Jetson Nano, the author of this research has successfully processed 360-degree images for local and real-time video as well as image geometry modifications.
Multipose to detect Airport Visitor Behavior Iswarawati, N.K.E.; Satyawan, Arief. S.; Puspita, Heni; Utomo, P.A.; Putri, R.A.
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.723

Abstract

The airport is a strategic place where it involves important activities, namely airplane flights. Airport activities are greatly influenced by the ongoing security within the airport. The thing that affects security in the airport is the possibility of crimes committed by unexpected visitors. The purpose of this research is to observe the airport area, especially airport visitors so that if there are visitors who have the potential to commit crimes, they can be detected properly and further investigation procedures can be carried out.  To be able to observe airport visitors and recognize patterns of visitor behavior that have the potential to commit crimes, an airport visitor gesture recognition system can be used. In this thesis, the gesture recognition of airport visitors is done with the multipose estimation method. This method can detect 17 key points on the human body that are used to detect the behavior of airport visitors who have the potential to commit crimes. To develop this system, deep learning algorithms that are currently developing with the help of TensorFlow and architectural models in multipose estimation, namely MobileNetV2, Feature Pyramid Network, and CenterNet, can be used. The experimental results show that the multipose estimation method can recognize human gestures well under several conditions such as the appropriate distance of the human object from the camera and the lighting conditions around the observed human object. It is also seen that from several scenarios, the crime gesture model can be recognized well.
Co-Authors Agus Setiawan Agustianti, Rifka Ali, Abdul Latif Alti, Rahmi Mudia Andriana Andriana Asdim Banowati, Lies Budiarto, Samsul Candra, Abel Bima Desi Arsita Eka Angasa Evi Maryanti Fauzan, R. Aldam Dwi Finasari, Sinta Nurul Gaffar A, Ade Harahap, Taufiq Hidayat Herdiana, Dina Hidayat Hidayat Huda Ubaya Isma Widiaty Iswarawati, N.K.E. Jaladhara, Aryo Paksi Kusumawijayanti, Anita Reta Martono Hadi Putranto, Agus Muharram, Bagus Adriyan Noviely, Isra Fanliv Perdana, Ferdian Yoga Putri, R.A. Reza Kurniawan Rika Agustin Satyawan, Arief Suryadi Satyawan, Arief. S. selly Selly Sitohang, Daniel Pandapotan Sri Desy Siswanti Sutrisno, Renaldy Agung Utomo, P.A. Utomo, Prio Adjie Vini Rizqi, Vini Wulandari, Ike Yuni Yayat Rukayat