Authors :
Sachini Kuruppu
Volume/Issue :
Volume 8 - 2023, Issue 9 - September
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/6zkjtf2f
DOI :
https://doi.org/10.5281/zenodo.8395158
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.
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.
