Energy Efficient and Accurate Monitoring of Large-Scale Diffusive Objects in Internet of Things

摘要

Based on distributed sensing via energy-constrained sensor devices, the key of large-scale and shape-dynamic object monitoring is how to reduce communication costs, which is the highest related factor to energy consumption. For achieving this goal, we propose a novel detection mechanism based on the convex hull algorithm that has a strong aspect for reducing the number of (geographic) sensing points to be transmitted to base stations for figuring out a large-scale object. As the convex hull only could recognize convex shapes, we develop methods to not only detect shape loss being a convex but recovery original boundary. That is, our mechanism could take both low communication cost and high detection reliability of large-scale objects.