| dc.description.abstract | Human-monkey conflict in Sri Lanka poses a significant challenge to wildlife conserva tion and human livelihoods. In recent years, the threat posed by monkeys has escalated.
Among the culprits, the Sri Lankan Toque macaque (Macaca sinica) emerged as the most
destructive, contributing to an annual loss of US$19.3 million in coconut production
alone. In response, the government proposed exporting 100,000 macaques to China,
but the plan was abandoned due to objections from conservation groups. Instead,
smart technology has been identified as a promising alternative to address this issue.
Innovations such as real-time monitoring and automated prevention systems offer the
potential to detect and deter monkey incursions while safeguarding crops and preserving
wildlife. This research explores the use of low-cost, eco-friendly solutions leveraging
the Internet of Things (IoT), deep convolutional neural networks, transfer learning, and
ultrasonic sound waves. These technologies enable the creation of virtual fences and
provide early, non-invasive warnings of monkey activity, significantly enhancing crop
protection. Through surveys and literature reviews, the study highlights the limitations
of traditional methods such as manual field protection and chemical repellents, which
are neither effective nor sustainable. The findings indicate that integrating IoT with
image processing and sound-based deterrents offers a scalable and sustainable approach
to mitigating human-monkey conflicts. Such innovations not only protect agricultural
productivity but also contribute to broader wildlife conservation efforts. | en_US |
