Name
Abstract | ||
|---|---|---|
Building information modeling is only beginning to incorporate human factors, although buildings are sites where humans and technologies interact with globally significant consequences. Some buildings fail to perform as their designers intended, in part because users do not or cannot properly operate the building, and some occupants behave differently than designers expect. Innovative buildings, e.g., green buildings, are particularly susceptible to usability problems. This paper presents a framework for prospectively measuring the usability of designs before buildings are constructed, while there is still time to improve the design. The framework, which was implemented as an agent-based computer simulation model, tests how well buildings are likely to perform, given realistic occupants. An illustrative model for lighting design shows that this modeling approach has practical efficacy, demonstrating that, to the extent that users exhibit heterogeneous behaviors and preferences, designs that allow greater local control and ease of operation perform better. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TSMCA.2011.2116116 | IEEE Transactions on Systems, Man, and Cybernetics, Part A |
Keywords | Field | DocType |
green building,usability problem,building information modeling,heterogeneous behavior,modeling approach,designing buildings,illustrative model,agent-based approach,real occupants,greater local control,human factor,agent-based computer simulation model,innovative building,usability,computer simulation,design automation,indexing terms,human factors,building design,software agents,construction industry,building information model,simulation,cad | CAD,Software engineering,Simulation,Computer science,Usability,Software agent,Construction industry,Electronic design automation,Artificial intelligence,Building information modeling,Machine learning | Journal |
Volume | Issue | ISSN |
41 | 6 | 1083-4427 |
Citations | PageRank | References |
4 | 1.01 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| CLINTON J. ANDREWS | 1 | 5 | 5.76 |
| Daniel Yi | 2 | 4 | 1.01 |
| Uta Krogmann | 3 | 4 | 1.01 |
| Jennifer A. Senick | 4 | 4 | 1.68 |
| Richard E. Wener | 5 | 4 | 1.01 |