Today, to do ground-based in-situ observations of the arctic tundra, researchers carry wild life cameras and other observation units into the field, manually configure the devices while on the arctic tundra, and fetch the collected data several months later. This approach does not scale. Instead, observing and reporting of data must be automated using a distributed wireless network of autonomous observation units.
We present the basic hardware and software architectures of the Distributed Arctic Observatory (DAO) observation units. A DAO observation unit is composed of both heavy and light computer cores. The idea is to use the heavy cores for resource demanding tasks and then power them off and shift the workload to light cores when possible in order to increase energy efficiency and extend battery life.
We report on initial thoughts and experiences in applying a CSP network on an observation unit to ease development of advanced functionalities, while still achieving energy efficiency for observation units.
In order to rapidly develop prototype systems and learn from them, we have composed observation units with a combination of Raspberry Pi computers as the heavy cores, and Arduino, Nucleo, and Sleepy Pi microcontrollers as the light cores.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com