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All Journal Jurnal Instrumentasi
Insani, Asep
Pusat Riset Teknologi Pengujian dan Standar, Badan Riset dan Inovasi Nasional
Agriculture, Biological Sciences & Forestry Chemistry Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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MEASURING VEHICLE SAFE DISTANCE USING DEEP LEARNING METHODS ON SMARTPHONE DEVICES Hidayat, Rachmat; Insani, Asep; Khusni, Uus; Hidayat, Asep Rahmat
Instrumentasi Vol 48, No 2 (2024)
Publisher : National Standardization Agency of Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31153/instrumentasi.v48i2.698

Abstract

Maintaining a safe driving distance is an essential part of road safety. Innovations in technology, such as cameras and sensors, assist in calculating vehicle distances but come with limitations like inaccurate results and high computational demands. This research aims to develop a deep learning algorithm that helps drivers maintain a safe distance and enhance safety. Our study found that the Inception V3+DBND method allows for efficient real-time vehicle distance estimation using a smartphone camera, offering an optimal distance prediction accuracy of 97.20%. The research findings provide a practical and effective solution for measuring safe vehicle distances.
Co-Authors Hidayat, Asep Rahmat Hidayat, Rachmat Khusni, Uus