Rental Price Predictor – Amsterdam

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

Predictive Coastal Erosion

Why? Coastal erosion is a dynamic and complex process influenced by both natural factors and human activities. Natural causes such as wave action, tidal patterns, weather events, and rising sea levels due to global warming significantly contribute to the gradual wearing away of coastlines. Additionally, human interventions like coastal construction, sand mining, and deforestation exacerbate … Read more

migrAItion

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

3D-SOLIDS: COMPONENTS CLASSIFICATION

3d Component Classification tool

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

Spatial Analysis of Airbnb Real Estate

Our goal was to predict the relationship between the tourist activity zones and the airbnb rentals. Tourism is vital to Spain’s economic growth, with Barcelona as a key contributor, accounting for over 12% of the country’s GDP. TOURIST ANALYSIS AND DATA Tourist spots and zones can be broadly classified to tourist amenities – transits, bus … 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

FacAid + Chatbot

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

Materializer

Introduction Our project, Materializer, leverages the power of multiple self-trained machine learning models to predict material quantities based on an image uploaded by the user and the building coordinates. This innovative approach utilizes image segmentation to isolate buildings, image classification to read material pixels, and a height prediction model for buildings lacking height information in … Read more

MY PARKS : Predicting Miami City’s Parks Scores based on Amenities and Businesses

Miami Parks Prediction GraphML Project

Rethinking Urban Spaces Parks and green areas are critical in cities as they provide spaces for people to meet, interact, and find a social life. They contribute significantly to the mental and physical well-being of residents, offering a natural respite from the urban hustle. Project Summary: According to google reviews, the most important factor for … Read more

Graph Machine Learning – A Study on Preventive Strategies for Femicides in Mexico City

For the last two decades, Mexico has grappled with an escalating wave of violence that has put the entire nation on edge, but it is particularly alarming and dangerous simply for being a woman.  This alarming trend, characterized by uncontrolled levels of violence and fueled by a deeply ingrained misogynistic culture, underscores the urgent need … Read more

Project Sentinel: Predicative analysis of street lighting and safety

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

Haven Ai

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

Fields at Play

Fields at Play identifies the value of gender inequality in Olympic infrastructure and proposes to leverage the derived $12.6B Olympic gender gap in sports facilities to fund the revitalization and ongoing program of reliable, safe, and comfortable spaces for women at risk of gender-based violence. Understanding the purpose and outcomes of Olympic infrastructure strategies in … Read more

Trav-a-live

Context Inter Disciplinary In this project, we explore the intersection of digital nomadism, autonomous mobility, and AI-enabled sensing technology. Inspired by thinkers like Tsugio Makimoto, Pierluigi Coppola, and Tim Ferriss, we aim to create an autonomous living space that supports a mobile, remote work lifestyle. The COVID-19 pandemic has accelerated the rise of digital nomadism, … Read more