TY - GEN
T1 - Data Quality in Building Productivity Assessment - the Case of Acute Care Environments
AU - Morewood, Jack
AU - Bacon, Matthew
AU - de Wilde, Pieter
N1 - Publisher Copyright:
© 2021 Universitätsverlag der Technischen Universität Berlin. All Rights Reserved.
PY - 2021
Y1 - 2021
N2 - Acute care environments are typically cost- and energy-intensive facilities. This paper presents a methodology to map operational processes to predict occupancy. Veracity of occupancy data is assured by an enhanced brief, quality measurement and quality improvement. A major development over existing and more general frameworks applied in this domain, this new approach challenges the basis of engineering. Feedback loops and roles set based on expected competencies instates strong governance. Application to a knowledge intensive case study for a hospital in Gothenburg, Sweden, sees data quality improvements facilitate improved occupancy modelling. Revising energy consumption from 94 to 81 kWhm-2a-1, a typical “performance gap” is avoided. Analysis modelled and optimised the space use, informed by knowledge of operational policy, increasing productivity, reducing energy consumption and need for capital-intensive plant.
AB - Acute care environments are typically cost- and energy-intensive facilities. This paper presents a methodology to map operational processes to predict occupancy. Veracity of occupancy data is assured by an enhanced brief, quality measurement and quality improvement. A major development over existing and more general frameworks applied in this domain, this new approach challenges the basis of engineering. Feedback loops and roles set based on expected competencies instates strong governance. Application to a knowledge intensive case study for a hospital in Gothenburg, Sweden, sees data quality improvements facilitate improved occupancy modelling. Revising energy consumption from 94 to 81 kWhm-2a-1, a typical “performance gap” is avoided. Analysis modelled and optimised the space use, informed by knowledge of operational policy, increasing productivity, reducing energy consumption and need for capital-intensive plant.
UR - http://www.scopus.com/inward/record.url?scp=85134206245&partnerID=8YFLogxK
M3 - Conference proceedings published in a book
AN - SCOPUS:85134206245
T3 - EG-ICE 2021 Workshop on Intelligent Computing in Engineering, Proceedings
SP - 135
EP - 145
BT - EG-ICE 2021 Workshop on Intelligent Computing in Engineering, Proceedings
A2 - Abualdenien, Jimmy
A2 - Borrmann, Andre
A2 - Ungureanu, Lucian-Constantin
A2 - Hartmann, Timo
PB - Technische Universitat Berlin
T2 - 28th International Workshop on Intelligent Computing in Engineering of the European Group for Intelligent Computing in Engineering, EG-ICE 2021
Y2 - 30 June 2021 through 2 July 2021
ER -