DF Predictor aims to revolutionize daylight prediction in architectural design by implementing the conditional generative adversarial network (cGAN) Pix2Pix to predict daylight factors, motivated by the need to improve efficiency and accuracy in daylight analysis. Daylight factor analysis, an integral part of the early design stages and mandated by building codes, is typically lengthy due … Read more
Introduction Accurate prediction of rental prices poses a significant challenge in dynamic real estate markets such as Amsterdam. Our research project explores the use of graph-based machine learning to improve the accuracy of such predictions. This methodology could be of interest to various actors in the real estate sector, including brokers, investors, and urban planners. … Read more
Studying migration is crucial for urban planners and architects to anticipate and accommodate the influx of people into cities, ensuring the development of robust infrastructure that can support this growth. As migration patterns shape demographic changes, understanding these trends allows cities to plan for adequate housing, transportation, healthcare, and educational facilities. This foresight is essential … Read more
Who Why: For the Amenities, we selected the following due to its overall correlation with residential real estate and we anticipate that it will give a good indication of how the properties would be priced. By creating bounding boxes around the amenities, with a radius of 1km, we ensure that as much of the graph … Read more
Abstract 3D-SOLIDS Component Classification tool utilizes machine learning to optimize the placement of essential 3D components such as walls, doors, windows, floors, and railings in residential floor plans. By analyzing spatial features and architectural attributes, it automates and enhances the design process, ensuring accuracy, consistency, and compliance with building standards. This tool aids architects and … Read more
Dataset Our database contains more than 181,000 rows, each with comprehensive information. The primary database includes 17 variables, though not all are necessary for our analysis. The most crucial data points are location (latitude and longitude), type of food establishment, type of inspection, inspection results, and risk level. As the person who uploaded the database … Read more
In a world where urban areas are predominantly developed and the heat island effect is intensifying, the construction industry significantly contributes to environmental challenges. Instead of focusing on tools that promote new construction, our goal is to provide a tool that analyzes existing buildings and suggests improvements. This approach aims to enhance sustainability and mitigate … Read more
Greater Manchester, one of the largest and most vibrant urban centers in the UK, is characterized by its substantial student population and a dynamic economic landscape. With approximately 120,670 university students during the 2021/22 academic year and a significant number of these individuals studying at the University of Manchester and Manchester Metropolitan University, the region … Read more
One step for Homelessness Around the world, almost 1 million plastic bottles are purchased every minute. If all of the plastic bottles sold in 2018 were gathered in a pile, it would be higher than the world’s tallest building, the Burj Khalifa in Dubai. What we are going to do with the Plastic bottles? Deposit … Read more
The Case of Tourism in Barcelona The “Guidebook on Urban Degrowth” explores applying degrowth principles in urban planning to promote social well-being and ecological equity in cities. This thesis develops guidelines to shift from high-consumption economic models to those that emphasize environmental balance and social equity. Focusing on Barcelona, it addresses the challenges of over-tourism, … Read more
Beginnings Our project’s concept is to develop a classification model that identifies street intersections (graph nodes) in Stockholm, Sweden, susceptible to flooding during a 100-year flood event. Based on our initial research, we found that graph machine learning operates at three levels: the graph, its edges, and its nodes. With access to a 100-year flood … Read more
The motorway was the symbol of progress during the modern age. The car was the central element of the American dream, and then expanded across the globe, transforming the way we live. Over the years, it has become clear that individual conventional cars are not only good for cities: urban motorways often create physical and … Read more
Introduction Urban transportation planning relies on data science to explain the conditions driving mobility patterns. This exploration of bicing, Barcelona’s resident bike rental program, analyzes the actors impacting discrepancies in bicing data to select machine-learning strategies able to predict biking station vacancies across Barcelona for the year 2024 with an accuracy of 0.02387. With this … Read more
