Camera-based surveillance is a non-invasive method for collecting data on many taxa of animals (reviewed by Reif & Tornberg 2006; Trolliet et al. 2014). Camera technologies are most often used for monitoring the trends over time and space in vertebrate populations (e.g. regory et al. 2014), their activity patterns (e.g. Gray & Phan 2011), behaviour and feeding ecology (e.g. Miller, Carlisle & Bechard 2014), or for the identification of nest predators (e.g. DeGregorio, Weatherhead & Sperry 2014).
Despite rapid advances in the miniaturization, image quality, data storage, portability, and utility of video-camera technology, the flexibility and cost-effectiveness of many camera systems has largely lagged behind the needs of many field researchers (Cutler and Swann 1999, Steen 2009, Cox et al. 2012, Waldstein 2012).
The Raspberry Pi (hereafter RPi) is a reliable, low-cost (~ EU 45€) micro-computer developed in 2006 by the University of Cambridge’s Computer Department, and produced by the Raspberry Pi Foundation in 2012 as a tool to encourage students to learn programming language (Severance 2013). This credit card-sized micro-computer boots to a programming environment that allows users to customize their RPi using Python programming language and uses the UNIX/debian-based Raspbian operating system, a free operating system optimized for RPi hardware. One of the foremost uses of the Raspberry Pi is as a low-cost image and (HD) video recording device (Jolles, 2021).
In this project we develop an automated monitoring system for multiple nest-boxes at once, using the RPi technology. The effective design and construction of this camera system brings a new opportunity to get detailed information about several breeding processes in the nest, such as egg laying dates, hatching dates, mortality events, fledging dates and parental caring effort monitoring.