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An AI-Based Support System for Left-Behind Children Detection in Vehicles

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 189))

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Abstract

In general, accidents involving school buses and parents leaving their infants in the car due to a lack of attention are increasing. Also, in-vehicle inspections are being neglected. In this paper, we focus on this problem and propose an AI-based support system for detecting left-behind children in vehicles. In the proposed system, we use YOLO which optimizes the hyperparameters when performing object detection. The proposed system can detect left-behind children by considering adults and dolls in a vehicle. Based on the evaluation results, we found that in Case #1, the accuracy was higher when the number of generations was 300. While, in Case #2, misidentification of adults was resolved by increasing the number of generations. Finally, in Case #3, some scenes were identified as dolls when were shown some body parts of the child.

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Authors and Affiliations

  1. Graduate School of Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka, 811-0295, Japan

    Hibiki Tanaka & Naoki Tanaka

  2. Department of Information and Communication Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka, 811-0295, Japan

    Shoei Sakano, Makoto Ikeda & Leonard Barolli

Authors
  1. Hibiki Tanaka
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  2. Naoki Tanaka
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  3. Shoei Sakano
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  4. Makoto Ikeda
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  5. Leonard Barolli
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Corresponding author

Correspondence to Makoto Ikeda .

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Editors and Affiliations

  1. Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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Tanaka, H., Tanaka, N., Sakano, S., Ikeda, M., Barolli, L. (2024). An AI-Based Support System for Left-Behind Children Detection in Vehicles. In: Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing . 3PGCIC 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 189. Springer, Cham. https://doi.org/10.1007/978-3-031-46970-1_4

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  • DOI: https://doi.org/10.1007/978-3-031-46970-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-46969-5

  • Online ISBN: 978-3-031-46970-1

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