Sensor Placement Reasoning Using an Evolutionary Algorithm and Digital Elevation Maps (SPREAD)

Wireless ground sensor networks provide superior situational awareness in operational areas, but their deployment is complicated by unpredictable signal traffic patterns, limited battery life, and physical obstacles that interfere with signal propagation. Sub-optimal layouts create transmission bottlenecks and force some nodes to drain their batteries faster than others. Currently, personnel must rely on experience and trial and error to achieve an optimal configuration, which may not be practical in hostile territory or during time-sensitive missions. To address these concerns, we propose to design a system for Sensor Placement Reasoning using an Evolutionary Algorithm and Digital elevation maps (SPREAD). SPREAD is a robust, intelligent approach that can calculate optimal sensor layouts and monitor network performance. Our solution consists of: (1) an evolutionary algorithm that finds the optimal sensor placement for a given 3D terrain based on a configurable tradeoff between coverage, number of sensors, and connectivity; (2) a mobile user interface for the user to configure optimization parameters, add or remove obstacles that might interfere with signal propagation, and understand the algorithm's optimized placement results; and (3) a health monitoring component that listens for diagnostic messages from the deployed network and notifies the user of potential problems.