SWWS: A Smart Wildlife Warning Sign System


  • Alan Ma Jesuit High School Portland




IoT, Wildlife Conservation, Machine Learning, Computer Vision, Roadkill, CNN


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.




How to Cite

Ma, A. (2022). SWWS: A Smart Wildlife Warning Sign System. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13197-13199. https://doi.org/10.1609/aaai.v36i11.21726