As sensor network technologies become more mature, they are increasingly being applied to a wide variety of applications, ranging from agricultural sensing to cattle, oceanic and volcanic monitoring. Significant efforts have been made in deploying and testing sensor networks resulting in unprecedented sensing capabilities. A key challenge has become how to make these emerging wireless sensor networks more sustainable and easier to maintain over increasingly prolonged deployments. In this paper, we report the findings from a one year deployment of an automated wildlife monitoring system for analyzing the social co-location patterns of European badgers (<i>Meles meles</i>) residing in a dense woodland environment. We describe the stages of its evolution cycle, from implementation, deployment and testing, to various iterations of software optimization, followed by hardware enhancements, which in turn triggered the need for further software optimization. We report preliminary descriptive analyses of a subset of the data collected, demonstrating the significant potential our system has to generate new insights into badger behavior. The main lessons learned were: the need to factor in the maintenance costs while designing the system; to look carefully at software and hardware interactions; the importance of a rapid initial prototype deployment (this was key to our success); and the need for continuous interaction with domain scientists which allows for unexpected optimizations.