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) .

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