No abstract

International audienceAn 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 observer-based residuals and adaptive thresholds. We demonstrate our proposed formulation using a 14-zone building case study

Abstract. An intelligent building should take all the necessary steps to provide protection against the dispersion of contaminants from sources (events) inside the building which can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. Multi-zone models and software, such as CONTAM, have been widely used in building environmental studies for predicting airflows and the resulting contaminant transport. This paper describes a developed Matlab Toolbox that allows the creation of data sets from running multiple scenarios using CONTAM by varying the different problem parameters. The Matlab-CONTAM Toolbox is an expandable research tool which facilitates the implementation of various algorithms related to contamination event monitoring. In particular, this paper describes the implementation of state-of-the-art algorithms for detecting and isolating a contaminant source. The use of the Toolbox is demonstrated through a building case-study. The Matlab-CONTAM Toolbox is released under an open-source licence, and is available at https://github.com/KIOS-Research/matlab-contam-toolbox.

No abstract

Abstract. In this work, we address the problem of airborne contaminant sensor placement in high-risk buildings where critical infrastructures are managed and operated, making them possible locations for terrorist attacks (such as governmental buildings and ministries, utilities, airports and hospitals). A new software is presented based on the "Matlab-CONTAM Toolbox" and the CONTAM multi-zone simulation software, to construct multiple scenarios of contamination events and to solve the multi-objective sensor placement problem for minimizing the average and maximum impact risk with respect to the contaminant mass inhaled impact metric. The use of the software is demonstrated in a case-study using the Holmes's House benchmark. The Toolbox is released under an open-source license at https://github.com/KIOS-Research/ matlab-contam-toolbox.