How Artificial Intelligence Is Reformulating The Notion Of Authorship In Architecture? Also published here: https://readymag.com/u3829384181/4130564/ Abstract Cosmic Dust Laboratory (CDL) is an experimental startup where humans and Artificial Intelligence Systems work together to come up with new architectural solutions for Extreme Climates and Conditions in Monegros Desert. An eloquent sponsor named Hannah goes to CDL … Read more
The data we engage with everyday is growing rapidly, and our digital footprint is increasing! With the cyber-physical convergence and the fast expansion of the Internet, Volume of information created, copied, captured, and consumed worldwide went form 33 zettabytes in 2018 to an expected 175 zettabytes in 2051! That’s close 500% increase in 5 years. … Read more
Introduction For the BIMSC studio project, the class designed a human colony initially capable of accommodating 50 inhabitants, with the potential to expand to 300 inhabitants. Working together, the class settled on the Jezero Crater as the site for the colony and developed a masterplan consisting of thirteen distinct zones. Each group selected one zone … Read more
The project focuses on promoting the physical, mental, and social well-being of older adults in the city of Barcelona through various initiatives, the goal is to empower older adults to remain active and engaged in their communities, and to promote healthy ageing and independence. Projected population aged 65+ What is Ageing? Health in the older … Read more
The New York City Taxi Trip Duration competition is a challenge to develop a model that predicts the total ride time of taxi trips in New York City. Yellow medallion taxicabs, which number 12,779 in New York City, generate a substantial revenue of $1.8 billion per year by providing transportation services to around 240 million … Read more
The Metaverse 2.0 for an environmentally conscious design If environmental consequences could be quickly computed by AI and reflected in an immersive digital model environment, the AEC industry could change the way it delivers results and reduce its carbon footprint? The research proposal is to investigate the “Infoverse”, an enhanced Metaverse for designers, where they … Read more
The construction industry creates a waste that is expected to reach 2.2 billion tons globally by 2025 (Transparency market research). Because of this the market started trying different new techniques to construct with less waste, that is how with the 4.0 industrial revolution came the Additive manufacturing process, that fabricates physical 3D objects layer by … Read more
Welcome Everyone My Name is Anton Klyshnia, I am a student of MaCad program at the Institute of Advanced Architecture of Catalonia. You are listening to the podcast as a part of Course: BIM and Smart Construction Theory. Today we will discuss how the AI will influence the architectural software and BIM software in particular. … Read more
Goal: to predict trip duration of NYC cabs using machine learning models. Tools: Python + Nympy + Pandas + Datetime + Plotly.express + Matplotlib + Math + Seaborn + Bokeh + Sklearn Stages of project: data cleaning, data analysis, data preparation, data testing, evaluating prediction accuracy. Data cleaning The first dataset visualization with splitting datasets … Read more
Ciudades urbana y humanamente digeribles Quetzaltenango, Guatemala. C.A Anteriormente el tema se aborda desde la perspectiva de ecología y cambio climático, donde se expone la situación actual de la ciudad de Quetzaltenango y donde se identifican los procesos alimentarios a traves de la industria y como estas dinámicas crean ciudades enfermas y obviamente ciudadanos enfermos, … Read more
Machine Learning-based Analysis of NYC Cab Trip Duration “Data-Driven Rides” is an entry for the first MaCT Machine Learning Competition that hosted on Kaggle which involves predicting the duration of taxi rides in New York City. The dataset provided for this competition is based on the 2016 NYC Yellow Cab trip record dataset and the … Read more
The MaCT01 students were tasked with training a model that would be used to predict NYC yellow taxi ride durations using machine learning. The dataset included pickup and drop-off datetimes, location coordinates and passenger count. Visualizing the data helped to understand the correlation between the columns and remove the highly correlated values Understanding the distribution … Read more
The source dataset provided for this project is derived from the 2016 NYC Yellow Cab trip records, which were made publicly available on the Big Query platform of the Google Cloud. The data was originally collected and published by the New York City Taxi and Limousine Commission (TLC). This dataset serves as the foundation for … Read more
#Objective #A Kaggle Competition to MaCT01 students to show their knowledge, designing an end-to-end machine learning project to predict the “Trip Duration” of NYC Taxi trips. #Workflow #First of all a workflow hast do be developed, which represents a classic approach for training machine learning models, analysing the provided training data provided by the submission, … Read more
The aim of the project is to predict trip duration, using 2016 NYC YELLOW CAB TRIP DATA. Structuring the dataset The analysis begins with outlier identification. The passenger_count variable has two outliers: 0 and 9, which compared to the amount of people allowed by the NY Limousine law, is impossible. Also, there were some pickup … Read more
INTRODUCTION Urban planning decisions have a significant impact on the development of cities, and using machine learning can provide decision-makers with valuable insights to make informed decisions. By clustering urban areas based on various factors such as population density, built density, POI density, green cover, and build diversity, we can reveal spatial patterns that can … Read more
