Automated and Optimized Sensor Deployment using Building Models and Electromagnetic Simulation

Abstract

With the advent of wireless sensing technology and interest in tracking resources, researchers have developed advanced tracking algorithms by using one or more sensor systems for improved accuracy and reliability of tracking. The objective of this research lies in another aspect−deployment−of tracking that has received only little attention until now. The research explores a method for sensor deployment particularly designed for the building in which the sensors are used. To tailor our solution to a specific building, we integrate a building information model with an electromagnetic energy analysis. By using such a model, the system extracts the properties of building materials, which are used as parameters of sensor deployment optimization. Then, we find a method of optimizing the deployment of a Received Signal Strength Indication (RSSI)-based tracking sensors for reducing wireless energy dissipation during the operation of the tracking system. For the numerical validation of the proposed method, the High-Frequency Structural Simulator (HFSS) runs an electromagnetic simulation to generate comparison data of electromagnetic energy flow from optimized sensor deployment and random sensor deployment. The results indicate that the proposed method could produce results that are correlated to the HFSS results. In addition, the method shows clear evidence of a reduction in signal power loss. Finally, optimized sensor deployment through the proposed framework can use signals of electromagnetic energy more effectively and potentially improve the efficiency of the RSSI-based tracking system.