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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Hadhrami Abd Ghani
Universiti Malaysia Kelantan
Computer Science & IT Engineering

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Toddler monitoring system in vehicle using single shot detector mobilenet and single shot detector-inception on Jetson Nano Kok Jia Quan; Zamani Md Sani; Tarmizi Bin Ahmad Izzuddin; Azizul Azizan; Hadhrami Abd Ghani
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i4.pp1534-1542

Abstract

Road vehicles are today’s primary form of transportation; the safety of children passengers must take precedence. Numerous reports of toddler death in road vehicles, include heatstroke and accidents caused by negligent parents. In this research, we report a system developed to monitor and detect a toddler's presence in a vehicle and to classify the toddler's seatbelt status. The objective of the toddler monitoring system is to monitor the child's conditions to ensure the toddler's safety. The device senses the toddler's seatbelt status and warns the driver if the child is left in the car after the vehicle is powered off. The vision-based monitoring system employs deep learning algorithms to recognize infants and seatbelts, in the interior vehicle environment. Due to its superior performance, the Nvidia Jetson Nano was selected as the computational unit. Deep learning algorithms such as faster region-based convolutional neural network (R-CNN), single shot detector (SSD)- MobileNet, and single shot detector (SSD)-Inception was utilized and compared for detection and classification. From the results, the object detection algorithms using Jetson Nano achieved 80 FPS, with up to 82.98% accuracy, making it feasible for online and real-time in-vehicle monitoring with low power requirements
Co-Authors Azizul Azizan Kok Jia Quan Tarmizi Bin Ahmad Izzuddin Zamani Md Sani