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FASTCAT-Edge: build your own smart camera trap

Authors: Ángela Justamante; Frederic Fol Leymarie; Stefan Rueger; Kai Waddington; Miklas Riechmann; Ryan Rueger; Ross Gardiner; +4 Authors

FASTCAT-Edge: build your own smart camera trap

Abstract

FASTCAT (Flexible AI SysTem for CAmera Traps)-Edge allows you to assemble an AI camera trap that: (1) Automatically filters out most unwanted pictures and video streams, keeping images of animals. This saves you time as you don’t have to delete empty recordings or photos. (2) The camera trap uses bespoke Artificial Intelligence (AI) to automatically identify whether a scene contains an animal or a human, ie, this allows you to only keep animal scenes. (3) Eventually, this service will connect with biodiversity citizen observatories. So, if you are a citizen scientist who uses a camera trap, you will be able to easily upload the picture to some platforms such as iSpot, Artportalen or Natusfera. More information: https://cos4cloud-eosc.eu/services/fastcat-edge-camera-trap/ FASTCAT-Edge has been developed by DynAikon in the Cos4Cloud framework. Infographic's designer: Lucas Wainer.

Keywords

camera trap, AI, citizen science, do-it-yourself, artificial intelligence, biodiversity

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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    35
    downloads
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visibility
download
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
Average
Average
Average
51
35
Funded by
EC| COS4CLOUD
Project
COS4CLOUD
Co-designed Citizen Observatories Services for the EOS-Cloud
  • Funder: European Commission (EC)
  • Project Code: 863463
  • Funding stream: H2020 | RIA
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