Norwegian AI Directory
Description:
The project aims to build the scientific foundations of statistical sampling for oceanographic applications by formulating novel algorithmic methods in statistics and blending it with ocean model
predictions, to embed and test on autonomous vehicles. By sampling, we refer to the design of
experiments in spatio-temporal domains, enabling autonomous platforms to decide on an optimal
strategy of where and when to gather data, in a cost-effective manner.
Renowned oceanographer Walter Munk called the 20th century, the century
of undersampling, something particularly
relevant in ocean-facing Norway with its complex fjord systems
intermixed with coastal skerries.
To improve the state of sampling modern tools and methods, including
the use of autonomous platforms, oceanographic models and satellite
remote sensing at various spatio-temporal scales are
critical. However, without adequate understanding of the theoretical
underpinnings of how, when and where to sample, these
tools and methods are insufficient in our vast and harsh oceans.
The focus of this proposal is in designing, implementing and
testing algorithms for efficient spatio-temporal sampling of the coastal oceans,
with a broader impact to commingling methods in spatial and computational statistics,
with oceanography, with novel methods in automatic control including
artificial intelligence for adaptive sampling. Deliverables
include testing of the new algorithms in field experiments in
Norwegian waters with existing robotic assets.
Project leader: Jo Eidsvik
Started: 2020
Ends: 2024
Category: Universiteter
Sector: UoH-sektor
Budget: 12594000
Institution: Institutt for matematiske fag
Address: Trondheim