Wireless sensor networks (WSNs) is a field with broad variety of applications. Its flexibility for remote continuous measurement lends itself to applications ranging from locating snipers to measuring volcanic activity. One application that stands to substantially benefit from WSNs is building management. Buildings currently account for 41% of the total energy consumption of U.S. [bed11]. Reducing this energy is of critical importance if we are to achieve sustainability. In most commercial buildings, many rooms remain unoccupied or are conditioned assuming maximum occupancy. By relaxing temperature setbacks and adjusting ventilation to match actual occupancy, significant energy savings are possible. This Dissertation examines the use of wireless sensor networks for the purpose of building energy management and actuation. It explores the design and development of wireless sensor networks for building energy management, how data from these deployments are utilized, the development and implementation of data driven occupancy models to perform simulation and prediction, how data models are used to actuate building management systems, and how crowd-sourced data can be integrated into building control strategies. We show based on real-world data that 30% energy savings is possible through usage based strategies and that 80% occupant satisfaction rates are possible by occupant driven control strategies.