Home / Volume 8, Issue 4 / Role of AI in Predicting and Preventing Wildlife… Open access · CC BY-NC 4.0
Research Paper Volume 8 Issue 4 1994 - 2002 August 15, 2025

Role of AI in Predicting and Preventing Wildlife Crimes in India

Lead author · Corresponding
Saloni Bhaktaraj Sharma
Advocate in India
View PDF Full text DOIhttps://doij.org/10.10000/IJLMH.1110592
Abstract

India is one of the countries with the most biological diversity in the world, with an estimated 7-8% of the world's recorded fauna. This biological wealth comprises many important species like the Bengal tiger, Indian elephant, and snow leopard, along with an immense range of endemic birds, reptiles, amphibians, and insects. But this exceptional biological wealth is heavily compromised due to numerous wildlife-associated crimes, such as poaching, trafficking, destruction of habitats, and man-wildlife conflicts. These crimes cause the breakdown of ecosystems, danger to indigenous and endangered wildlife, and violation of environmental management of India, along with its socio-economic fluctuations. The dilemma of effectively allocating funds towards surveillance, coupled with the sophisticated methods used during cases of poaching, often makes conventional enforcement methods ineffective in large swaths of forests. Thus, Artificial Intelligence (AI) has become an integral component, providing predictive analysis, real-time monitoring, and automation in deciding the location of threat sources. The current study comprehensively analyzes the use of AI for predicting and suppressing wildlife crimes, designed entirely from an Indian perspective, bridging the gaps regarding implementation, policy loopholes, and incorporating community participation within the National Wildlife Action Plan (2017–2031) .

Type
Research Paper
Information
International Journal of Law Management and Humanities, Volume 8, Issue 4, Page 1994 - 2002
DOI: https://doij.org/10.10000/IJLMH.1110592
Creative Commons
CC BY-NC 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.
Copyright
Copyright © IJLMH 2026
Disclaimer
The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

Export citation