DAO – Distributed Arctic Observatory

Performing ground-based in-situ observations in remote and challenging environments is very difficult. These environments include the Arctic tundra, remote desert, mountain regions, or even large industrial installations. It requires the manual deployment and on-site maintenance and data collection. Between the time of deployment and data collection, several months will usually pass, as these sites are remote and difficult to reach and often lacking infrastructures such as transport systems, network access, and energy supply. This makes it challenging to plan and undertake large, long-term monitoring programs, and to collect the substantial amount of data required for thorough and statistically relevant analysis.

The aim of the Distributed Arctic Observatory (DAO) is to develop more robust, efficient, and autonomous monitoring systems and instruments in order to improve performance, longevity, and ease of data collection under such challenging conditions. The DOA project is an interdisciplinary effort involving multiple research groups from the Department of Computer Science and the Department of Arctic and Marine Biology at UiT The Arctic University of Norway.

DOA will develop and build the next generation of robust and energy-efficient observation units (OUs). These OUs can comprise multiple sensors, autonomously monitor themselves and the environment, and be configurable so that new applications can be added. The OUs will be part of a cyber-physical system collecting, synchronizing, and submitting data to users that are expecting the data for further analysis.

The DOA project works with the Climate-ecological Observatory for Arctic Tundra (COAT) as a use-case, a national initiative for developing an ecosystem-based and adaptive long-term monitoring system for the vulnerable Arctic Tundra.

DAO is a Norwegian ICT project (IKTPLUSS) funded by the Research Council of Norway. In the DAO project, the Arctic Green Computing group is the leader of the work package on energy-efficient edge devices.

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