Issue No. 04 - October-December (2010 vol. 9)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MPRV.2010.53
Marcus Chang , IT University of Copenhagen
Philippe Bonnet , IT University of Copenhagen
Monitoring terrestrial high-arctic ecosystems is important because of their exposure to global warming. Ideally, these ecosystems would be monitored continuously to capture the evolution of their characteristics year-round. This requires a pervasive monitoring infrastructure that collects data automatically. Consequently, measurements that have traditionally been obtained manually should now be obtained with automatic measurement systems. Deploying such systems in a high-arctic environment raises specific challenges due to limited access, extreme weather, and the absence of communication infrastructure. The MANA project tackles these challenges with a sensor-network-based data acquisition system for year-round lake monitoring in Northeast Greenland. This article describes the system design and lessons learned from the MANA project's first year of deployment. It emphasizes the issues the researchers underestimated initially—the consequences of operating in a remote region, extreme weather's impact on system design and operator activities, and the demands caused by the absence of a communication infrastructure.
sensor networks, wireless, field experiment, arctic monitoring systems, MANA, Capoh, pervasive computing
M. Chang and P. Bonnet, "Monitoring in a High-Arctic Environment: Some Lessons from MANA," in IEEE Pervasive Computing, vol. 9, no. , pp. 16-23, 2010.