| Title |
Building Occupancy Estimation with Robust Kalman Filter |
| ID_Doc |
40219 |
| Authors |
Li, KY; Zhang, K |
| Title |
Building Occupancy Estimation with Robust Kalman Filter |
| Year |
2017 |
| Published |
|
| DOI |
|
| Abstract |
People flow and occupancy estimation is critical for smart city and intelligent building operation such as emergency evacuation (egress). Most previous works on this topic are based on the Kalman filter (KF) for its efficacy and efficiency. However, the classical KF requires precise people flow models which are usually hard to get due to the complexity of people behavior. There are always model mismatches and the model may change with time and different situations, so the classical Kalman filter may not work well in real applications. In this work, the robust Kalman filter is applied to the people occupancy estimation problem and an iterative algorithm is developed to handle the state-dependent model uncertainties. Professional people behavior simulation software is used to generate people flow data in a specified building structure and the estimation result from the robust Kalman filter is compared with the classical KF with simulated people flow data. |
| Author Keywords |
Smart city; Robust estimation; Kalman filtering |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000426957300246 |
| WoS Category |
Automation & Control Systems; Engineering, Electrical & Electronic |
| Research Area |
Automation & Control Systems; Engineering |
| PDF |
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