Publication Date: 2023/09/30
Abstract: International Wildlife Trade (IWT) poses a grave threat to global biodiversity conservation efforts, exacerbating the ongoing sixth mass extinction crisis. With IWT ranking fourth among the world's largest criminal industries [1], worth an estimated $7-$23 billion annually [2], urgent measures are required to prevent the illegal exploitation of endangered species. This research paper proposes the implementation of an automated weapon detection system in forest areas, where the population density of endangered animal species are high, aiming to detect concealed weapons used by poachers, even in dense forest environments with limited internet connectivity. The paper provides an overview of IWT, its detrimental effects, strategies for prevention, the importance of biodiversity protection, and outlines an advanced artificial intelligence-based approach combining camera traps, the YOLOv5 object detection algorithm, and Long Range (LoRa) technology with Raspberry Pi 4 to identify poachers carrying concealed weapons. The proposed system has the potential to significantly enhance wildlife protection and safeguard the lives of park rangers by monitoring unexplorable geographical areas, detecting weapons and alerting the presence of poachers to park rangers and pinpointing the location in real time.
Keywords: Illegal Wildlife Trade, Yolov5, Camera Traps, Long Range (LoRa) technology, Raspberry, detecting weapons.
DOI: https://doi.org/10.5281/zenodo.8395158
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23SEP506.pdf
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