Building Code

Building codes, sets of rules governing building design and construction, are increasingly being analyzed and interpreted using computational methods to improve efficiency and compliance. Current research focuses on applying machine learning, particularly large language models and deep learning architectures like multilayer perceptrons, to automate the translation of natural language building regulations into machine-readable formats and to accelerate tasks such as sunlight assessment. This work aims to improve the speed and accuracy of compliance checking and enhance the overall design and construction process, ultimately leading to safer and more efficient buildings.