| Summary: | In this thesis we describe how we designed, built, deployed, and improved upon a robust hardware- and software solution, tailor-made to this scientific question. During the course of this project, we created three distinct versions and we have conducted two deployments of the sensor nodes in the Arctic tundra. The node is able to measure CO2 , temperature, and humidity, in addition to monitoring an already existing COAT experiment. As the energy budget is a crucial factor for the success of our project, we have conducted experiments to optimize the power efficiency of the node. The sensor nodes communicate over the LTE CAT M1 network, are waterproof, and are capable of operating in temperatures as low as −25◦C. Through the use of software optimization, low-power components, and efficient duty-cycling, our solution is capable of operating for several years on battery power. This novel sensor node solution will help the ecologists monitor and predict the impact of climate change on life beneath the snow on the Arctic tundra. The approach described will be applicable to a diverse set of scientific questions, spanning many branches of data-driven research.
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