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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MULTINETICS Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) eProceedings of Engineering Journal of Computer Engineering: Progress, Application and Technology
Fussy Mentari Dirgantara
Telkom University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Pedestrian Detection System using YOLOv5 for Advanced Driver Assistance System (ADAS) Surya Michrandi Nasution; Fussy Mentari Dirgantara
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 3 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i3.4884

Abstract

The technology in transportation is continuously developing due to reaching the self-driving vehicle. The need of detecting the situation around vehicles is a must to prevent accidents. It is not only limited to the conventional vehicle in which accident commonly happens, but also to the autonomous vehicle. In this paper, we proposed a detection system for recognizing pedestrians using a camera and minicomputer. The approach of pedestrian detection is applied using object detection method (YOLOv5) which is based on the Convolutional Neural Network. The model that we proposed in this paper is trained using numerous epochs to find the optimum training configuration for detecting pedestrians. The lowest value of object and bounding box loss is found when it is trained using 2000 epochs, but it needs at least 3 hours to build the model. Meanwhile, the optimum model’s configuration is trained using 1000 epochs which has the biggest object (1.49 points) and moderate bounding box (1.5 points) loss reduction compared to the other number of epochs. This proposed system is implemented using Raspberry Pi4 and a monocular camera and it is only able to detect objects for 0.9 frames for each second. As further development, an advanced computing device is needed due to reach real-time pedestrian detection.
Implementation of Cellular-Based Drone Module using Cloud Services Adrian Ferdinand Jotham; Fussy Mentari Dirgantara; Muhammad Faris Ruriawan
Journal of Electrical, Electronic, Information, and Communication Technology Vol 5, No 2 (2023): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.5.2.72640

Abstract

The notion of a smart city incorporates the integration of infrastructure, services, and the community and encompasses the deployment of unmanned aerial vehicles (UAVs) for monitoring crop fields, facilitating logistics delivery, and performing high-altitude cleaning tasks. In a smart city, the interconnectedness of devices is realized through the medium of the Internet of Things (IoT). This research endeavors to explore the usage of Beyond Visual Line of Sight (BVLOS) for enabling remote command and control of UAV/UGV modes, leveraging 4G/LTE connectivity as an enabler. 4G/LTE connectivity is known for its improvement in data transfer speed and network capacity, which potentially enables the connection of more devices, including drones. The high availability and scalability of cloud services have become crucial factors in utilizing cloud services as the most cost-effective and expedient relay for connecting two nodes over the internet globally for now. The proposed methodology would be integrated into a smart drone module, which would be deployed at a small scale as a component of the Intelligent Transportation System (ITS).
Co-Authors Adita Sukma Wardani Adrian Ferdinand Jotham Agus Virgono Arief Syaichu-Rohman Attallah Arelian Naufhal Casi Setianingsih Davy Rachmandiaz Hartoyo Lenni Yulianti Miftah Amirul Amin Mohammad Naufal Nabil Abdillah Muhammad Arham Irsyad Muhammad Emir Ghiffari Muhammad Faris Ruriawan Muhammad Nur Habibi Prabu Arie Pradana R Rogers Dwiputra Setiady Randy Erfa Saputra Reza Rendian Septiawan Surya Michrandi Nasution Syaichu-Rohman, Arief Umar Ali Ahmad Yudha Pratama Yulianti, Lenni