While networked sensors are becoming a ubiquitous part of many human lives, their applications to the study of wild animals have been largely limited to off-the-shelf and stand-alone technologies such as web cameras. However, purpose-designed systems, applying features found in Internet-of-Things devices, enable more efficient gathering, managing, and disseminating of a diverse array of data needed to study the life histories of wild animals. We illustrate these claims based on our development of a system of networked nest boxes that we created to study nesting birds in urban environments. This system uses general-purpose processors within nest boxes to perform edge computing to control data acquisition, processing, and management from multiple sensors. A central data-management system permits easy access to all data, once downloaded, which has facilitated our uses to date of this system for formal university-and school-level education, and informal science education.