Authors:
Ovidiu Noran
1
;
Peter Bernus
2
and
Sorin Caluianu
3
Affiliations:
1
IIIS Centre for Enterprise Architecture Research and Management - Griffith University, Brisbane, Australia, Faculty of Installations Engineering, Technical University of Constructions Bucharest, Romania
;
2
IIIS Centre for Enterprise Architecture Research and Management - Griffith University, Brisbane, Australia
;
3
Faculty of Installations Engineering, Technical University of Constructions Bucharest, Romania
Keyword(s):
Building Information Model, Building Management System of Systems, Decision Support Systems, Situational Awareness, Big Data, Data Warehousing, Decision Model, Situated Reasoning, Channel Theory.
Abstract:
Technical advances in Information and Communication Technology have enabled the collection and storage of large amounts of data, rising hopes of improving asset decision-making and related building management support systems. It appears however that the gap between the required decision-making knowledge and the actual useful information provided by current technologies appears to increase, rather than contract. Thus, often the multitude of patterns afforded by current data analytics techniques does not deliver a set of scenarios prone to effective decision making. This paper advocates a decision analytics solution featuring the use of Situated Logic to create ‘narratives’ providing adequate meaning to data analytics results, and the use of Channel Theory so as to support adequate situational awareness. This approach is also analysed in the context of a Building Management System-of-Systems paradigm, highly relevant to the emerging complex Clusters of Intelligent Buildings within Smar
t Cities, featuring collaborative decision-making centres and their associated decision support systems.
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