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.
