Convolutional Neural Network-based Optical Camera Communication System for Internet of Vehicles
Amirul Islam

TL;DR
This paper presents a CNN-based optical camera communication system for IoV that enables multi-vehicle detection, fast processing, and reliable communication under adverse weather conditions, integrating near-infrared and SDN technologies.
Contribution
The study introduces a novel CNN-based OCC system with multi-vehicle detection, high-speed processing, and the use of near-infrared light, enhancing IoV communication robustness.
Findings
Improved vehicle detection accuracy in OCC systems.
Enhanced communication range with near-infrared light.
Robust performance under adverse weather conditions.
Abstract
The evolution of internet of vehicles (IoV) and the growing use of mobile devices with the development of the Internet of Things, demand has grown for alternative wireless communication technologies. As a promising alternative, optical-camera communication (OCC) has emerged that uses light-emitting diode (LED) and camera as transmitter and receiver respectively. Since LEDs and cameras are exploring in traffic lights, vehicles, and public lightings, OCC has the potential to handle the transport systems intelligently. Though some technologies have been proposed or developed, these are not mature enough to uphold the huge requirements of IoV. However, most of the OCC applications are limited to single vehicle and there has been limited focus on the use of multiple vehicles detection (spatial) or fast processing (temporal) systems. Also, there has no system to challenge with the bad weather…
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Taxonomy
TopicsOptical Wireless Communication Technologies · Video Surveillance and Tracking Methods · Vehicular Ad Hoc Networks (VANETs)
