Arduino data loggers
A helping hand in physical geography
Bibliographic Data
Microcontrollers such as Arduino have been increasingly used by researchers to create and customise their own tools. In geography, microcontrollers are frequently used to design data loggers for monitoring purposes. We reviewed the use of Arduino in physical geography to unravel the opportunities and challenges of using off-the-shelf tools in research. We conducted a literature review, putting the retrieved information in perspective with our experimental work in mountainous and riverine landscapes in Chile and Peru. We show that the low cost and versatility of Do It Yourself (DIY) data loggers open research opportunities, extending the range of application of their expensive commercial counterparts. The possibility of connecting Arduino to a wide range of sensors, actuators, and wireless communication devices has helped to monitor rivers, glaciers, lakes, ice-waves, caves, and landslides, improving the temporal and spatial resolution of data collected in critical environments. Low-cost sensors have been extensively compared against expensive alternatives with good results, although they require thorough testing before field deployment due to the common existence of defective equipment. Building research equipment has several challenges. DIY data loggers might not be unconditionally accepted by environmental agencies, partially restricting their use to educational and research purposes. Failures in data loggers can be difficult to track, since they might be related to coding, electronic assemblage, or inadequate housing to withstand outdoor use. Yet, Arduino-based data loggers have helped scientists around the world in different stages of their career, especially in scarcely funded research endeavours. Arduino has boosted creativity and resourcefulness, paving the way for innovative monitoring strategies in physical geography
Arduino · Data logger · Data science · Embedded system · Geography · Microcontroller · Operating system · Remote sensing · Software deployment · Software engineering · Computer Science · Context-Aware Activity Recognition Systems · Environmental Monitoring and Data Management · Water Quality Monitoring Technologies
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