This paper discusses our experience in designing and deploying a 994-node sensor network to measure the social contact network of a high school over one typical day. The system aims to capture interactions of human subjects for the study of infectious disease spread. We describe unique challenges posed by a large-scale network that is heavily affected by humans. We present techniques to address challenges such as frequent node reboots and global timestamps. The end result of the deployment is a dataset of 792 traces which can be used to calculate the school population's contact network and the rough location where interactions occurred