TY  - GEN
N2  - Indoor Air Quality monitoring is an essential
ingredient of intelligent buildings. The release of various airborne contaminants into the buildings, compromises the health and safety of occupants. Therefore, early contaminant detection is of paramount importance for the timely activation of proper contingency plans in order to minimize the impact of
contaminants on occupants health. The objective of this work is to enhance the performance of a distributed contaminant detection methodology, in terms of the minimum detectable contaminant release rates, by considering the joint problem of partitioning selection and observer gain design. Towards this direction, a detectability analysis is performed to derive
appropriate conditions for the minimum guaranteed detectable contaminant release rate for specific partitioning configuration and observer gains. The derived detectability conditions are then exploited to formulate and solve an optimization problem for jointly selecting the partitioning configuration and observer
gains that yield the best contaminant detection performance.
ID  - discovery10060822
PB  - IEEE
UR  - https://doi.org/10.1109/CDC.2018.8619262
SN  - 2576-2370
A1  - Kyriacou, A
A1  - Timotheou, S
A1  - Reppa, V
A1  - Boem, F
A1  - Panayiotou, C
A1  - Polycarpou, MM
A1  - Parisini, T
KW  - Buildings

KW  - 
Observers

KW  - 
Detectors

KW  - 
Optimization

KW  - 
Uncertainty

KW  - 
Pollution measurement

KW  - 
Monitoring
TI  - Optimization Based Partitioning Selection for Improved Contaminant Detection Performance
AV  - public
Y1  - 2019/01//
SP  - 5568
EP  - 5573
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
ER  -