Experiences Building and Deploying Wireless Sensor Nodes for the Arctic Tundra

• Published in: 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
• Main Authors: Murphy, Michael J., Tveito, Øystein, Kleiven, Eivind Flittie, Rais, Issam, Soininen, Eeva M, Bjørndalen, John Markus, Anshus, Otto
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE 2021
• Subjects: VDP::Technology: 500::Environmental engineering: 610; VDP::Teknologi: 500::Miljøteknologi: 610; Arctic; Climate change; Tundra
• Online Access: https://hdl.handle.net/10037/22742; https://doi.org/10.1109/CCGrid51090.2021.00047

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The arctic tundra is most sensitive to climate change. The change can be quantified from observations of the fauna, flora and weather conditions. To do observations at sufficient spatial and temporal resolution, ground-based observation nodes with sensors are needed. However, the arctic tundra is resource-limited with regards to energy, data networks, and humans. There are also regulatory and practical obstacles. Consequently, observation nodes must be small and unobtrusive, have a year or longer operational lifetime from small batteries, and be able to report results and receive software updates over scarce back-haul networks. We describe the architecture, design, and implementation of prototype observation nodes deployed to the arctic tundra for the periods August 2019 to July 2020 and August 2020 to July 2021. For the 2019 deployment, ten nodes were each placed inside ten existing camera traps. A camera trap is a box with a wildlife camera taking pictures of rodents when they enter the box from tunnels under snow and ice. For the 2020 deployment, eight nodes were located pairwise inside four camera traps. Each node measures carbon dioxide level and temperature inside the camera trap during the winter season. A node reports its state and observational data each night over a commercial low power IoT telecom back-haul network, if available. We report on the issues encountered doing actual deployments of the prototype nodes. For each issue, we describe the reason for why it happened, relate it to the architecture, design and implementation, and explain what we did about it.