This research introduces an AI-based alert system to reduce human-wildlife conflicts in the Romanian Carpathian Mountains. Globally, conflicts between people and wildlife are rising due to population growth, shifting land use patterns and climate change. In Romania, mountain communities are impacted by bears and wild boars, which damage livestock, crops and property. These conflicts can undermine conservation efforts and may result in the killing of problematic animals. In collaboration with Fundația Conservation Carpathia, this research supports Rapid Intervention Teams who respond to wildlife activity in mountain villages. Six years of camera trap data are used to train and test AI models to detect and classify European mammals. These models are integrated into an alert system and deployed in three locations. The new pipeline improves on the state-of-the-art for detecting and classifying bears and wild boars. Preliminary results from the field deployment show a positive impact on conservation efforts. This is the first known study to use remote processing of 4G-enabled camera trap images to operate a human-wildlife conflict alert system. It is also the first known study to design and evaluate all stages of an AI-based wildlife alert system, from data collection and model training to field deployment and conservation impact. Bio: Tom is an MRes student on the AI for Environmental Risk Centre for Doctoral Training at the University for Cambridge. He previously spent 10 years working for the UK's Foreign, Commonwealth and Development Office, where he designed and managed sustainable development projects while on postings in DRC, Sierra Leone and Tanzania.
