UDEEP: Edge-based Computer Vision for In-Situ Underwater Crayfish and
  Plastic Detection
Dennis Monari Jack Larkin Pedro Machado Jordan J. Bird Isibor Kennedy Ihianle Salisu Wada Yahaya Farhad Fassihi Tash Md Mahmudul Hasan Ahmad Lotfi
Invasive signal crayfish have a detrimental impact on ecosystems. They spread
the fungal-type crayfish plague disease (Aphanomyces astaci) that is lethal to
the native white clawed crayfish, the only native crayfish species in Britain.
Invasive signal crayfish extensively burrow, causing habitat destruction,
erosion of river banks and adverse changes in water quality, while also
competing with native species for resources and leading to declines in native
populations. Moreover, pollution exacerbates the vulnerability of White-clawed
crayfish, with their populations declining by over 90% in certain English
counties, making them highly susceptible to extinction. To safeguard aquatic
ecosystems, it is imperative to address the challenges posed by invasive
species and discarded plastics in the United Kingdom's river ecosystem's. The
UDEEP platform can play a crucial role in environmental monitoring by
performing on-the-fly classification of Signal crayfish and plastic debris
while leveraging the efficacy of AI, IoT devices and the power of edge
computing (i.e., NJN). By providing accurate data on the presence, spread and
abundance of these species, the UDEEP platform can contribute to monitoring
efforts and aid in mitigating the spread of invasive species.