Wildlife Intelligent Monitoring: Advancing Conservation Through Visual and Acoustic Monitoring Technologies

Dear Colleagues,

The accelerating biodiversity crisis underscores the urgent need for innovative approaches to wildlife monitoring and conservation. “Wildlife Intelligent Monitoring: Advancing Conservation Through Visual and Acoustic Monitoring Technologies” is a multidisciplinary Topic that brings together cutting-edge research and practical innovations in wildlife monitoring. This Topic aims to highlight advances in intelligent monitoring technologies that integrate visual sensing and acoustic analysis to provide comprehensive insights into wildlife populations, behaviors, and habitats.

This Topic welcomes original research articles, reviews, and case studies that explore the deployment, optimization, and application of wildlife intelligent monitoring in diverse ecosystems across the globe. We aim to cover themes including but not limited to

• Novel methodologies for camera trap/passive acoustic device deployment and data collection;
• AI and deep learning for automated species and behavior recognition;
• Multimodal data fusion (e.g., combining camera traps with acoustic, thermal, and drone data);
• Population estimation and occupancy modeling using camera trap/passive acoustic monitoring data;
• Temporal and spatial analysis of animal activity patterns;
• Behavior ecology and social interaction analysis via long-term camera trap/passive acoustic monitoring;
• Detection and management of invasive species and poaching activity;
• Human–wildlife conflict monitoring and mitigation strategies;
• Wildlife health assessment and disease surveillance using imagery/audio;
• Community-based and citizen science approaches using camera trap/audio recorder;
• Data sharing platforms, camera trap/passive acoustic monitoring networks, and open-access databases;
• Standardization, benchmarking, and reproducibility in camera trap/passive acoustic monitoring research;
• Integration of camera trap/passive acoustic monitoring data into conservation policy and decision-making;
• Assessment of animal health, stress, and well-being through multimodal sensing, physiological and behavioral indicators, and data-driven welfare evaluation frameworks.

Given the interdisciplinary nature of this Topic, we encourage contributions from ecologists, wildlife biologists, computer scientists, conservation practitioners, and data scientists. In particular, we welcome papers that showcase cross-disciplinary approaches and demonstrate real-world conservation impacts.

Potential contributors include research groups and institutions actively involved in wildlife monitoring, AI-assisted conservation, and biodiversity informatics. Planned papers may include large-scale biodiversity assessments using camera trap networks, studies presenting methodological advancements in species recognition, or comparative studies focused on monitoring strategies across different biomes.

By consolidating research across several MDPI journals, including Animals, Biology, Birds, Veterinary Sciences, and Wild, this Topic aims to foster collaboration and knowledge exchange among diverse scientific communities working toward global wildlife conservation.

Dr. Jiangjian Xie
Dr. Junguo Zhang
Topic Editors