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Software agent reasoning supporting non-intrusive building space usage monitoring

Dibley, Michael James, Li, Haijiang ORCID:, Rezgui, Yacine ORCID: and Miles, John Christopher 2013. Software agent reasoning supporting non-intrusive building space usage monitoring. Computers in Industry 64 (6) , pp. 678-693. 10.1016/j.compind.2013.03.008

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Conventional facility management (FM) software tools, lacking automatic synchronisation with the domain and rich semantic modelling, are limited to the simpler querying of manually maintained models. A software system that monitors and interprets temporally changing (internal) building environments and generates related knowledge can better assist in facility management decision making. This paper introduces a non-intrusive building monitoring framework that includes ZigBee sensor network and supporting software agents to provide better building space usage monitoring through software agents based on the belief-desire-intention (BDI) abstraction, exploiting ontology based reasoning to direct behaviour. The non-intrusive method is particularly useful and more amenable than the use of cameras for example when building monitoring involves human behaviours. The use of the multi agent paradigm renders a system that delivers demonstrable rationality and is robust within the dynamic environment that it operates. Agent behaviour directed at working towards goals is rendered intelligent with semantic web technologies. The capture of semantics through formal expression to model the environment adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The agent goals are currently used to generate knowledge about building space usage as well as environmental conditions by elaborating and combining near real time sensor data and information from conventional building models. The deployed and tested sensor based monitoring framework exhibits intelligence that will find application in the better support of decision making by integration with existing FM tools.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TJ Mechanical engineering and machinery
Uncontrolled Keywords: ZigBee sensor; Multi-agent system (MAS); Belief-desire-intention (BDI) reasoning; Ontology
Publisher: Elsevier
ISSN: 0166-3615
Last Modified: 10 Nov 2022 13:03

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