Broad‐scale applications of the Raspberry Pi: A review and guide for biologists - Jolles, Jolle W. (Methods in ecology and evolution, 2021)
The field of biology has seen tremendous technological progress in recent years, fuelled by the exponential growth in processing power and high‐level computing, and the rise of global information sharing. Low‐cost single‐board computers are predicted to be one of the key technological advancements to further revolutionise this field. So far, an overview of current uptake of these devices and a general guide to help researchers integrate them in their work has been missing. In this paper I focus on the most widely used single‐board computer, the Raspberry Pi, and review its broad applications and uses across the biological domain. Since its release in 2012, the Raspberry Pi has been increasingly taken up by biologists, in the laboratory, the field and in the classroom, and across a wide range of disciplines. A hugely diverse range of applications exists that ranges from simple solutions to dedicated custom‐build devices, including nest‐box monitoring, wildlife camera trapping, high‐throughput behavioural recording, large‐scale plant phenotyping, underwater video surveillance, closed‐loop operant learning experiments and autonomous ecosystem monitoring. Despite the breadth of its implementations, the depth of uptake of the Raspberry Pi by the scientific community is still limited. The broad capabilities of the Raspberry Pi, combined with its low cost, ease of use and large user community make it a great research tool for almost any project. To help accelerate the uptake of the Raspberry Pi by the scientific community, I provide detailed guidelines, recommendations and considerations, and 30+ step‐by‐step guides on a dedicated accompanying website (http://raspberrypi‐guide.github.io). I hope this paper will help generate more awareness about the Raspberry Pi among scientists and thereby both fuel the democratisation of science and ultimately help advance our understanding of biology, from the micro‐ to the macro‐scale.