Nowadays, piece of unattended luggage there are like tens thousands of lost or left behind in the airports in everyevery year. Due to this issue, this research work aims to develop a camera system that can detect the baggage or luggage and human and notify the authority via media social WhatsApp application when abandoned baggage detected. On top of that, Raspberry Pi 3 model B is used as a hardware where Pi camera is installed in the hardware. This research work is using deep learning method to perform the detection of the baggage and human. The Single Shot Multibox Detector (SSD) is used as the deep learning object detection algorithms for this research work to train the object detection model. The OpenCV and Tensorflow Library is a deep learning library is installed in the Raspberry Pi 3 model B minicomputer to perform the process of detection of the human and baggage. As a result, the Abandoned Baggage Detection and Alert System (ABDAS) able to detected human and baggage using computer vision and the system will notify the authority when the system detected an abandoned baggage through WhatsApp using Twilio Internet of Things (IoT) application software.
CITATION STYLE
Soh, Z. H. C., Kamarulazizi, K., Daud, K., Hamzah, I. H., Saad, Z., & Abdullah, S. A. C. (2020). Abandoned Baggage Detection & Alert System Via AI and IoT. In ACM International Conference Proceeding Series (pp. 205–209). Association for Computing Machinery. https://doi.org/10.1145/3384613.3384614
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