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All Journal Jurnal Computech & Bisnis (e-Journal) Jurnal Teknologi Informasi dan Ilmu Komputer ANALITIKA TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol MULTINETICS Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Ilmu Ekonomi dan Sosial (JIES) eProceedings of Engineering Journal of Computer Engineering: Progress, Application and Technology Jurnal INFOTEL BERBAKTI: Jurnal Pengabdian Kepada Masyarakat
Sri Astuti
Telkom University
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Nursing Public Health Social Sciences Other

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Journal : Jurnal INFOTEL

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All-in-one computation vs computational-offloading approaches: a performance evaluation of object detection strategies on android mobile devices Muhammad Abdullah Rasyad; Favian Dewanta; Sri Astuti
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.700

Abstract

Object detection gives a computer ability to classify objects in an image or video. However, high specified devices are needed to get a good performance. To enable devices with low specifications performs better, one way is offloading the computation process from a device with a low specification to another device with better specifications. This paper investigates the performance of object detection strategies on all-in-one Android mobile phone computation versus Android mobile phone computation with computational offloading on Nvidia Jetson Nano. The experiment carries out the video surveillance from the Android mobile phone with two scenarios, all-in-one object detection computation in a single Android device and decoupled object detection computation between an Android device and an Nvidia Jetson Nano. Android applications send video input for object detection using RTSP/RTMP streaming protocol and received by Nvidia Jetson Nano which acts as an RTSP/RTMP server. Then, the output of object detection is sent back to the Android device for being displayed to the user. The results show that the android device Huawei Y7 Pro with an average FPS performance of 1.82 and an average computing speed of 552 ms significantly improves when working with the Nvidia Jetson Nano, the average FPS becomes ten and the average computing speed becomes 95 ms. It means decoupling object detection computation between an Android device and an Nvidia Jetson Nano using the system provided in this paper successfully improves the detection speed performance.
Co-Authors Arif Faturrachman Arif Indra Irawan Dhea Dearly Herman Fakhri Rahmatullah Favian Dewanta Gregorius Pradana Satriawan Hadi Purnama Ibnu Asror Ida Wahidah Hamzah Iman Hedi Santoso Kharisma Bani Adam M. Dwiki Fadhilah Martha Tri Lestari Muh Naufal Setiawan P Muh Nurkhaliz Muhammad Abdullah Rasyad Muhammad Azka Imaddudin Muhammad Bagas Arya Darmawan Muhammad Fajar Firdiansyah Muhammad Risqi Risfianda Nizar Rizky Awany Nurul Adiningtyas Nurwulan Fitriyanti Nyoman Bogi Aditya Karna Putri Ayu Rezeki Rafli Noveri Alfariji Ratna Mayasari Ridha Muldina Negara Sayid Huseini Elfarizi Sofia Naning Hertiana Sussi Tita Melia Milyane Tody Ariefianto Wibowo