@phdthesis{eprintsunpak8868,
           month = {October},
          author = {Nurmin Kumas and Andi Chairunnas and Deden Ardiansyah},
          school = {Universitas Pakuan},
           title = {Model Sistem Pengenalan Rambu Lalu Lintas Menggunakan Raspberry PI Berbasis Internet Things},
            year = {2024},
        abstract = {Traffic Sign Recognition System Model Using Raspberry Pi Based on the
Internet of Things
Andi Chairunnas?, Deden Ardiansyah?, Nurmin Kuma?
?,?,? Department of Computer Science, Faculty of Mathematics and Natural Sciences,
Universitas Pakuan, Bogor, West Java, 16143, Indonesia
Abstrak
This research develops a traffic sign recognition system using Internet of
Things (IoT) technology with Raspberry Pi as the main processing unit. The system
aims to help drivers detect traffic signs and improve road safety by providing audio
descriptions of the detected signs. Using OpenCV for image processing, the system
achieves 85\% accuracy for clear images and 77\% accuracy for blurry images,
demonstrating the potential of IoT-based systems in smart driving applications.
Keywords : IoT; Traffic Sign Recognition; Raspberry Pi; Computer Vision;
OpenCV},
             url = {http://eprints.unpak.ac.id/8868/}
}