The automatic preservation of the indoor air quality (IAQ) is an important task of the intelligent building design in order to ensure the health and safety of the occupants. The IAQ, however, is often compromised by various airborne contaminants that penetrate the indoor environment as a result of accidents or planned attacks. In this paper, we provide the detailed analysis, implementation, and evaluation of a distributed methodology for detecting and isolating multiple contaminant events in large-scale buildings. Specifically, we consider the building as a collection of interconnected subsystems, and we design a contaminant event monitoring software agent for each subsystem. Each monitoring agent aims to detect the contaminant and isolate the zone where the contaminant source is located, while it is allowed to exchange information with its neighboring agents. For configuring the subsystems, we implement both exact and heuristic partitioning solutions. A main contribution of this paper is the investigation of the impact of the partitioning solution on the performance of the distributed contaminant detection and isolation (CDI) scheme with respect to the detectability and isolability of the contaminant sources. The performance of the proposed distributed CDI methodology is demonstrated using the models of real building case studies created on CONTAM.^{1 1}CONTAM is a multizone simulation program developed by the U.S. National Institute of Standards and Technology.

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An intelligent building is required to provide safety to its occupants against any possible threat that may affect the indoor air quality, such as accidental or malicious airborne contaminant release in the building interior. In this work, we design a distributed methodology for detecting and isolating multiple contaminant events in a large-scale building. Specifically, we consider the building as a collection of interconnected subsystems and we design a contaminant event monitoring agent for each subsystem. Each monitoring agent aims to detect the contamination of the underlying subsystem and isolate the zone where the contaminant source is located, while it is allowed to exchange information with its neighboring agents. The decision logic implemented in the contaminant event monitoring agent is based on the generation of observerbased residuals and adaptive thresholds. We demonstrate our proposed formulation using a 14-zone building case study.

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The dispersion of contaminants from sources (events) inside a building can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. Such events could be the result of an accident, faulty equipment or a planned attack. Under these safety-critical conditions, immediate event detection should be guaranteed and the proper actions should be taken to ensure the safety of the people. In this paper, we consider an event as a fault in the process that disturbs the normal system operation. This places the problem of contaminant event monitoring in the fault diagnosis framework of detection and isolation. A main contribution of this work is the development of the state-space method, based on multi-zone building models, that enables the use of advanced fault diagnosis tools for contaminant event monitoring. Specifically, in this paper, we develop estimator schemes with adaptive thresholds for the detection and isolation of a single contaminant source under conditions of noise and modeling uncertainty. We demonstrate our proposed formulation using a 2-zone illustration example and a more realistic 14-zone building setting.

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The dispersion of contaminants from sources (events) inside a building can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. These events could be the result of an accident, faulty equipment or a planned attack. Under these safety-critical conditions, immediate event detection should be guaranteed and the proper actions should be taken to ensure the safety of the people. In this paper, we consider an event as a fault in the process that disturbs the normal system operation. Furthermore, we demonstrate how the problem of monitoring the indoor air quality in intelligent buildings against the presence of contaminant sources fits the usual framework of fault detection, isolation, identification and accommodation. Specifically, we develop a multi-zone formulation using state space equations that enables the use of fault diagnosis and fault tolerant control techniques for monitoring contaminant events inside the building environment. We demonstrate our proposed formulation for the problem of isolating multiple contaminant sources using an estimation scheme in a nine zone building setting.@en