About FaunaScope
FaunaScope connects computer science and ecology to make wildlife observation more scalable, more intelligent, and more useful for real biological discovery.
FaunaScope is an interdisciplinary research initiative building next-generation infrastructure for AI-driven wildlife monitoring. The project focuses on both practical challenges at human-wildlife interfaces and a broader biological mission: understanding behavior and interactions in natural environments.
Traditional camera trap workflows often miss nuanced behaviors, inter-species interactions, and long-term patterns. FaunaScope is designed to close that gap and enable richer ecosystem insight at scale.
Edge devices (e.g., NVIDIA Jetson Orin) process footage in real time, filtering irrelevant frames and prioritizing biologically meaningful events.
Learned neural video codecs and aggressive compression make low-bandwidth transmission practical, with cloud-side reconstruction for analysis.
Cloud multimodal models annotate species, behaviors, interactions, and environmental context, enabling semantic search across large video archives.
Weather-resistant hardware with LiFePO4 batteries, solar generation, and smart power management supports 24/7, unattended operation.
FaunaScope software is released as open source to support the broader scientific and conservation community.
Edge Repository: github.com/imics-lab/faunascope-edge
This work is supported by the Texas State University Research Enhancement Program (REP).
Research is conducted in the Intelligent Multimodal Computing and Sensing (IMICS) Lab at Texas State University.