Evolving the Planning Paradigm: A Machine Learning Framework for Efficient City Planning
Author: Regor Martin Manalo Abuloc Jr.
Degree: Master of Community Planning, Vancouver Island University, April 2024
Summary:
In "Evolving the Planning Paradigm: A Machine Learning Framework for Efficient City Planning," Regor Martin Manalo Abuloc Jr. explores the integration of artificial intelligence into urban planning. This comprehensive thesis presents a groundbreaking machine learning framework aimed at revolutionizing traditional city planning methodologies.
Abuloc delves into how AI can automate mundane tasks, enhance the efficiency of planning processes, and provide innovative solutions to contemporary urban challenges such as population growth and climate change. Through a detailed literature review, case studies, and the creation of practical AI tools, the thesis offers valuable insights and practical guidance for planners looking to leverage AI in their work.
Key topics covered include:
- The history and evolution of AI in urban planning
- Ethical considerations and governance related to AI adoption
- Case studies showcasing successful AI implementation in various municipalities
- Emerging AI planning tools and their applications
- Recommendations for integrating AI into urban planning practices responsibly and effectively
This thesis is an essential read for urban planners, policymakers, and anyone interested in the intersection of technology and urban development. It not only charts a course for the future of urban planning but also provides a practical guide for incorporating AI technologies into planning practices today.
Product Summary for Gumroad Title: Evolving the Planning Paradigm: A Machine Learning Framework for Efficient City Planning Author: Regor Martin Manalo Abuloc Jr. Degree: Master of Community Planning, Vancouver Island University, April 2024 Summary: In "Evolving the Planning Paradigm," Regor Martin Manalo Abuloc Jr. explores the integration of AI into urban planning, presenting a machine learning framework designed to revolutionize traditional methods. This thesis details how AI can automate tasks, enhance efficiency, and address urban challenges like population growth and climate change. Key topics include: AI's history and evolution in urban planning Ethical considerations and governance Case studies of successful AI implementation Emerging AI planning tools Practical recommendations for AI integration This essential read for planners and policymakers offers a practical guide for incorporating AI technologies into planning practices today.