# Rediscovering Cities through AI | Momin Uppal | TEDxSICAS DHA Youth Source: https://www.youtube.com/watch?v=omVX1mvKn8I Recap page: https://rapidrecap.app/video/omVX1mvKn8I Generated: 2026-02-02T18:33:44.906+00:00 --- ## Quick Overview Momin Uppal discusses how his team at the Center for Urban Informatics, Technology and Policy (CUI-TTP) at LUMS is leveraging AI and data science to redesign urban systems in Pakistan, specifically highlighting the creation of high-resolution population density maps for Lahore and optimizing emergency service routes by analyzing accident hotspots. **Key Points:** - The speaker, Momin Uppal from CUI-TTP at LUMS, advocates for evidence-based planning and policy design for sustainable urban systems using 21st-century technology like AI and data science. - Lahore's built-up area increased four times between 1988 and 2021, leading to significant urban problems stemming from unmanaged growth. - The team created high-resolution population density maps for Lahore by using an AI model for building detection on satellite imagery to disaggregate census data. - The analysis showed that only 15% of Lahore's area (4.42 million people, 40%) is within a 5-minute walk of a public transport station. - In collaboration with Punjab Emergency Services (Rescue 122), they analyzed accident hotspots using advanced analysis to improve resource allocation and response times. - The team also worked with the Lahore Waste Management Company to optimize trash collection routes, potentially saving 150,000 liters of fuel monthly. - The core research team includes urban planners, data analysts, engineers, and transport planners. ![Screenshot at 00:14: The speaker points to a slide illustrating the 'Our City Systems: Current State of Affairs' which details negative trends in Growth \(Lahore built-up area increasing 4x\) and Mobility \(car trips 3x, bike trips 2x\), leading to environmental and health crises.](https://ss.rapidrecap.app/screens/omVX1mvKn8I/00-00-14.jpg) **Context:** The presentation, delivered at TEDxSICAS DHA, focuses on the work of Momin Uppal and his multidisciplinary team at LUMS' Center for Urban Informatics, Technology and Policy (CUI-TTP). The core theme revolves around utilizing modern data science and Artificial Intelligence (AI) techniques to analyze and subsequently redesign critical urban systems in Pakistani cities, using Lahore as the primary case study for population density mapping and emergency service optimization. ## Detailed Analysis Momin Uppal introduces the challenge of redesigning urban systems by first establishing the context of rapid, unplanned urban growth, citing that Lahore's built-up area increased fourfold between 1988 and 2021, resulting in significant environmental, health, and mobility crises. He emphasizes that any meaningful urban change requires high-resolution data, such as population density maps, which his team developed using an AI model for building detection on satellite imagery. This process allowed them to disaggregate census data into high-resolution formats. A critical finding shared was that only 15% of Lahore's area (covering 4.42 million people, or 40% of the population) has access to public transport within a five-minute walk. He also detailed a use case with Punjab Emergency Services (Rescue 122) to analyze accident hotspots, aiming to improve resource allocation and response. Furthermore, they collaborated with the Lahore Waste Management Company to optimize trash collection routes using AI, projecting fuel savings of 150,000 liters per month. The presentation concludes by showcasing the multidisciplinary nature of their team (urban planners, data scientists, engineers, policymakers) and promoting their ongoing work through the City Atlas project. ### Introduction and Urban Challenges - The speaker introduces the problem of unplanned urban growth, citing Lahore's built-up area increasing 4x (1988-2021) and resulting in social inequity, environmental crises, and health crises. ### Population Density Mapping via AI - The team created high-resolution population density maps for Lahore using an AI model for building detection on satellite imagery to disaggregate census data. ### Public Transport Coverage Analysis - A use case revealed that only 15% of Lahore's area (4.42 million people, 40%) is within a 5-minute walk of a public transport station. ### Road Safety Enhancement - Collaborating with Punjab Emergency Services (Rescue 122), the team performed hotspot analysis on accident data to improve resource allocation and response times. ### Waste Management Optimization - The team used AI to optimize trash collection routes for the Lahore Waste Management Company, projecting monthly fuel savings of 150,000 liters. ### The Core Team - The speaker identifies the core research team as a multidisciplinary collective including Public Policy Makers, Engineers, Transport Planners, Data Analysts, and Geo-Spatial Analysts. ### Conclusion and Call to Action - The journey continues with ongoing projects; the audience is invited to join via links provided on screen, including the City Atlas project. ![Screenshot at 00:03: The title slide for the TEDx talk: "Redesigning Our Cities using AI", featuring the speaker's affiliation with LUMS and CUI-TTP.](https://ss.rapidrecap.app/screens/omVX1mvKn8I/00-00-03.jpg) ![Screenshot at 01:16: Slide showing 'Our City Systems: Current State of Affairs,' detailing problematic statistics for Lahore related to Growth \(4x built-up area increase\) and Mobility \(3x car trips, 2x bike trips\).](https://ss.rapidrecap.app/screens/omVX1mvKn8I/00-01-16.jpg) ![Screenshot at 05:22: Slide titled 'Redesigning Urban Systems Requires Data,' showing a population density map of Continental Europe as an example of crucial high-resolution data.](https://ss.rapidrecap.app/screens/omVX1mvKn8I/00-05-22.jpg) ![Screenshot at 07:41: Slide detailing the methodology for 'Use Case: Coverage Analysis of Lahore's Public Transport,' showing Orange Line and Green Line route coverage relative to existing road networks and bus stops.](https://ss.rapidrecap.app/screens/omVX1mvKn8I/00-07-41.jpg) ![Screenshot at 11:13: Slide displaying 'CITY Strategic Partners,' illustrating the collaborative network involving organizations like Careem, LUMS, and various government/private entities.](https://ss.rapidrecap.app/screens/omVX1mvKn8I/00-11-13.jpg)