Haikubox

From Wikipedia, the free encyclopedia

Haikubox is an artificial intelligence (AI)-enabled device which automatically and continuously identifies backyard birds using their vocalizations. Haikubox was developed by Loggerhead Instruments which also develops and manufactures bioacoustics equipment for oceanographic research.[1]

Haikubox website and mobile app

Haikubox uses a neural net developed through a collaboration with the creators of BirdNET Sound ID[2] at the Cornell Lab of Ornithology's K. Lisa Yang Center for Conservation Bioacoustics.[3]

Each Haikubox becomes a node in a passive acoustic monitoring (PAM)[4] network which researchers can use to map bird behavior. PAM, especially when paired with machine learning, is emerging as an efficient, non-invasive and low-cost way to study animals and their behavioral responses to environmental change.[5] An article published online by bioGraphic[6] and later in Living Bird Magazine,[7] summarized the history of bioacoustics and outlined the potential of PAM to revolutionize scientific research and conservation efforts, noting that Haikubox is "one of the products of this revolution."

Haikubox has been reviewed in WIRED Magazine,[8] Audubon Magazine,[9] Birdwatching Magazine,[10] and Axios Tampa Bay,[11] and appeared on the WIRED Wish List 2022[12] and a 2023 guide to best bird watching gear.[13]

The device was named "Haikubox" because it observes nature, much like haiku poems which capture a moment in time and often focus on nature imagery.

Development of Haikubox was supported in large part by National Science Foundation's SBIR (Small Business Innovation Research) funding (Cooperative Agreement No. 2135664).[14]

References[edit]

  1. ^ "Loggerhead Instruments". Loggerhead Instruments.
  2. ^ "BirdNET-Analyzer". Github. Retrieved 8 November 2023.
  3. ^ Kimel, Earle (6 September 2022). "Haikubox gives citizen scientists a tool to track birds through the sound of their song". Herald-Tribune. USA TODAY. Retrieved 19 October 2022.
  4. ^ Ross, Samuel R. P.-J. (10 January 2023). "Passive acoustic monitoring provides a fresh perspective on fundamental ecological questions" (PDF). Functional Ecology. 37 (4). British Ecological Society: 959-975. Bibcode:2023FuEco..37..959R. doi:10.1111/1365-2435.14275. S2CID 256177246.
  5. ^ Gibb, Rory (4 October 2018). "Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring" (PDF). Methods in Ecology and Evolution. 10 (2). British Ecological Society: 169-185. doi:10.1111/2041-210X.13101. S2CID 92554621.
  6. ^ Dobbs, David (17 February 2023). "What Conservation Sounds Like". bioGraphic. California Academy of Sciences. Retrieved 8 November 2023.
  7. ^ Dobbs, David (Autumn 2023). "What Conservation Sounds Like". Living Bird. 42 (4): 44–53. Retrieved 8 November 2023.
  8. ^ Gilbertson, Scott (17 September 2022). "Review: Haikubox". WIRED. WIRED. Retrieved 8 November 2023.
  9. ^ Leber, Jessica (10 July 2023). "These Smart Devices Can Identify the Birds Outside Your Window". Audubon Magazine (Summer 2023): 61. Retrieved 8 November 2023.
  10. ^ Johnson, Hans. "Always Listening". BirdWatching (January/February 2023): 42–43.
  11. ^ Montgomery, Ben. "New tool identifies birds in your backyard". Axios Tampa Bay. Axios. Retrieved 8 November 2023.
  12. ^ "Wish List: 42 Incredible Gifts to Give and Get". WIRED. Vol. 30, no. 12. 15 November 2022. p. 29. Retrieved 8 November 2023.
  13. ^ Gilbertson, Scott. "Here's All the Gear You Need to Start Birding". WIRED. WIRED. Retrieved 8 November 2023.
  14. ^ "Award Abstract #2135664, SBIR Phase II: Building a Nature Monitoring Network for Birds". National Science Foundation. Retrieved 2 November 2023.