Using sensors to monitor surface or subsurface traffic requires sensor placement, detection of traffic changes, and sensor power scheduling for improved efficiency. Of these capabilities, sensor power scheduling is one of the most important as the appropriate sensors must be selected for activation to respond to changes in the traffic. We present an adaptive power scheduling algorithm that uses the homogeneous equilibrium of a potential-field-based dynamical system to determine which sensors should be active. Our algorithm assumes a nearest neighbor topology, which makes additional assumptions about the placement of sensors. We formalize these conditions and construct a sensor placement algorithm to support our scheduling algorithm. To demonstrate the efficacy of our scheduling approach, we provide two distinctive traffic detection algorithms that we combine with our placement and scheduling algorithm to test via simulation. We provide the simulation results that show in both cases, the adaptive scheduling algorithm behaves efficiently as compared to an area coverage approach , as well as an all-active path coverage approach.