Activity-informed Dynamic Data Driven Simulation

Abstract

In previous work we developed dynamic data driven simulation (DDDS) that assimilates real time sensor data using Sequential Monte Carlo (SMC) methods. This paper builds on previous work and presents a framework that adds a real time behavior pattern detection layer on top of data assimilation for dynamic data driven simulation. The real time behavior pattern detection layer uses Hidden Markov Model (HMM) to detect the behavior patterns of a system in real time and uses the detected behavior pattern to inform the simulation model for more accurate simulation. We apply the proposed framework to a smart environment application and discuss how to recognize behavior pattern from spatial-temporal sensor data using Coupled HMM (CHMM).