2022 AAAI AAAI 2022

SWWS: A Smart Wildlife Warning Sign System

Abstract

Abstract Every year in the US, millions of animals are run over by vehicles making wildlife vehicle collisions a real danger to both animals and human. In addition, road networks be-come abiotic barriers to wildlife migration between regions creating ripple effects on ecosystems. In this paper, a smart wildlife warning sign system (SWWS) is demonstrated, utilizing the technologies of Internet of Things, image recognition, data processing and visualization. This smart sign system is intended to prevent roadkill by warning drivers to slow down once sensors are triggered and simultaneously capture animal images via infrared cam-era. Data collection is conducted through local neural network model identification of wildlife images and saved along with metadata based on animal activity occurrence. Wildlife activity data can be exported wirelessly to cloud database to assist ecologists and government road agencies to investigate and analyze the wildlife activity and migration patterns over time.

🧭 Keyword Pioneer — wildlife detection
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors