AI-powered Urban Development Architect

AI-powered Urban Development Architect

BACKGROUND

Every year, political turmoil and a variety of environmental disasters displace millions from their homes, causing crises that carry over to the nations accepting these refugees. Countries are usually unprepared for these crises and refugees are forced to spend months, even years, in refugee camps. Therefore, our project attempts to create a matching algorithm to appropriately recommend destinations for refugees in hopes to help governments balance the desires of their citizens and maximize the quality of life for refugees.

BACKGROUND

Every year, political turmoil and a variety of environmental disasters displace millions from their homes, causing crises that carry over to the nations accepting these refugees. Countries are usually unprepared for these crises and refugees are forced to spend months, even years, in refugee camps. Therefore, our project attempts to create a matching algorithm to appropriately recommend destinations for refugees in hopes to help governments balance the desires of their citizens and maximize the quality of life for refugees.

ABOUT

Urban Architect Project is part of an AI4Good project series, between the AI for Good Foundation and the Applied Data Science with Venture Applications Course at SCET, UC Berkeley.

PROBLEM

Political turmoil and environmental disasters displace millions of people from their homes

Neighboring nations are unprepared to assist refugees.

Governments are faced with balancing humanitarianism and the wishes of their citizens

GOAL

Help Countries Assist Refugees

OBJECTIVE

We aimed to build a model of ideal refugee migration patterns in order to alleviate social and economic pressures in destination countries due to poor resettlement planning. Furthermore, we intend to target decision makers in hopes of minimizing the disruption to the lives of migrants and inhabitants of recipient communities.

SOLUTION

Model that predicts the number of refugees and where they will be best suited to emigrate:

  • Empirical data of former refugee crises
  • Economic data of specific regions where individuals are likely to be displaced to best predict refugees’ skillset and work experience
  • Economic data of neighboring countries to identify where the refugees would fit best

RESEARCH TEAM

DATA – X 

JASON KIM

Researcher

RISHABH MESWANI

Researcher

AVIRAL PEREIRA

Researcher

NEEL PATEL-SHAH

Researcher

JOHN SHOTTON

Researcher

CLAUDIA PERLICH

SCIENCE LEAD