ABSTRACT
Buildings are an integral part of our physical environment and have aesthetic significance with respect to the organizational integrity of architectural elements. While Gestalt principles are essential in design education, their relationship with architectural features remains understudied. The present study explored how Gestalt principles and complexity levels influence evaluations of building façades through the use of questionnaires and eye tracking. Twenty-four two-dimensional black and white façade drawings, manipulated using selected Gestalt principles (similarity and proximity) to achieve different levels of complexity (low, medium & high), were presented to 79 participants. The results suggested a negative linear relationship between aesthetic ratings and complexity levels across selected Gestalt principles. In addition, as expected, participants had the highest number of fixations, shortest fixation durations, and lowest aesthetic ratings for higher levels of complexity. Results involving Gestalt principles revealed that proximity-based designs received higher aesthetic ratings, demanded less time, elicited lower number of fixations, and resulted in shorter fixation durations. Conversely, similarity-based designs received lower aesthetic ratings, demanded more time, elicited higher number of fixations, and resulted in longer fixation durations. These findings offer insights into architectural aesthetic experiences and inform future research directions.
ABSTRACT
This Dataset provides a method of optimizing robot arm, facade pick and place locations in the construction site during facade assembly activity using generative design. A set of generative algorithms are provided in the form of graphical algorithm editors. The dataset is divided into three sets, each set controlling an essential subtask of facade assembly in the construction site. the dataset is called (iFOBOT) and consist of the following sub datasets: generative tool for facade population on building envelop (iFOBOT-D), Generative algorithm aided robot spatial location optimizer (iFOBOT-B), and Quantity take-off generative (iFOBOT-L). A sample project associated with its script and outcome results are included in this dataset to guide readers how to use this tool. This dataset only focuses on robot arm and facade module placement in construction sites. This dataset can generate optimized location of robot arm workstation in jobsite while also reducing robot collision with its body and surrounding objects, 2) reducing reachability rate, 3) reducing robot time travel during operation which in result minimize risk in facade assembly and increase productivity. This dataset is in parametric format which makes it reusable with all its history data using the reproducing guide provided here. More details of how to reuse this dataset and developed tool in construction site is covered in Robot-based Facade Spatial Assembly Optimization paper [1].