Big Data analytics are increasingly used to discover potentially interesting patterns in large data sets. In this chapter, we discuss the potential of combining Big Data methods with those of agent-based simulations to support architectural and urban designs, for agent-based models allow for the generation of novel datasets to study hypothetical situations and thus designs. Specifically, we present two conceptual studies that investigate the utility of agent- based models in conjunction with Big Data analytics in the context of multi-level pedestrian areas and current office designs, respectively. The analyses of the case studies suggest that it will be worthwhile, both for urban designers and architects, to pursue a combined agent- based simulation Big Data analytics approach.
@incollection{scheutzmayer16ucus,
title={Combining Agent-Based Modeling with Big Data Methods to Support Architectural and Urban Design},
author={Scheutz, Matthias and Mayer, Thomas},
year={2016},
booktitle={Understanding Complex Urban Systems},
publisher={Springer},
pages={15--31}
url={https://hrilab.tufts.edu/publications/scheutzmayer16ucus.pdf}
doi={10.1007/978-3-319-30178-5_2}
}