Published Online:February 2025
Product Name:The IUP Journal of Telecommunications
Product Type:Article
Product Code:IJCT020225
DOI:10.71329/IUPJTC/2025.17.1.43-53
Author Name:Renju John and Fiza Akbar
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:43-53
Human-wildlife conflict (HWC) is a rising concern in biodiversity hotspots such as Wayanad, Kerala, where agricultural loss, property damage, and human casualties due to wildlife incursions have intensified. With elephant intrusions alone contributing to over 60% of reported conflict events in the region, traditional mitigation strategies—like trenching and electric fencing— have proven both reactive and limited in effectiveness. This paper explores AI-driven solutions as a proactive and scalable response. By combining satellite imagery, GPS tracking, and realtime sensor data, it has developed a predictive model capable of detecting conflict risk zones and alerting stakeholders in near real time. The approach improves prediction accuracy over legacy systems by 23% and enables faster mobilization of response teams. The findings underscore the viability of integrating Edge AI and remote sensing into conservation efforts, offering a sustainable model for managing HWC across India’s forest fringes.
Biodiversity hotspots such as Wayanad face growing human-wildlife conflicts due to habitat encroachment, climate change, monoculture expansion, and agricultural practices (Gopi and Madhusudan, 2017; Krishnan and Bose, 2020). These conflicts often manifest in crop damage, livestock depredation, and even loss of human life, especially in the context of elephant and wild boar intrusions (Fernando et al., 2012; Nath et al., 2018). Traditional deterrent mechanisms such as electric fencing and manual patrolling have shown limited success and high maintenance costs (Forest Department of Kerala, 2023).