Object Detection Application for a Forward Collision Early Warning System Using TensorFlow Lite on Android

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Object Detection Application for a Forward Collision Early Warning System Using TensorFlow Lite on Android

Satya, Barka / Hendry / Manongga, Daniel H. F.

Forward collision mitigation system is a safety feature available on cars. This feature prevents collision caused by the lack of maintaining a safe distance between vehicles, as well as from drivers who lack concentration. However, not all vehicles have this feature. So in this research, an android-base application whose function and objectives are similar to the safety feature will be made. This application will use TensorFlow lite for the Custom Object Detector, SSD MobileNet V2 for the pre-trained model, and OpenCV library for the application framework. The research is done using the CRISP-DM methodology, as well as literature studies from previous research as a comparison. The output of this research is an application that can give a passive alert to the driver if the distance between vehicles is less than 3 m for cars, less than 2 m for motorcycles and less than 5 m for buses and trucks, giving a safe distance to do braking if needed.

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Dokumentinformationen

Titel :

Object Detection Application for a Forward Collision Early Warning System Using TensorFlow Lite on Android

Weitere Titelangaben:

Lect. Notes in Networks, Syst.

Beteiligte:

Kumar, Sandeep (Herausgeber:in) / Sharma, Harish (Herausgeber:in) / Balachandran, K. (Herausgeber:in) / Kim, Joong Hoon (Herausgeber:in) / Bansal, Jagdish Chand (Herausgeber:in) / Satya, Barka (Autor:in) / Hendry (Autor:in) / Manongga, Daniel H. F. (Autor:in)

Kongress:

Congress on Intelligent Systems ; 2022 September 05, 2022 - September 06, 2022

Erschienen in:

Third Congress on Intelligent Systems ; Kapitel : 59 ; 821-834

Lecture Notes in Networks and Systems ; 613

Erscheinungsdatum :

2023-05-19

Format / Umfang :

14 pages

ISBN :

978-981-19-9379-4 , 978-981-19-9378-7

ISSN :