AI In The Urban Planning Market Size, Share, Opportunities, And Trends By Deployment (Cloud, On-Premise), By Application (Public Transport, Security Monitoring, Waste Management, Infrastructure Planning, Others), And By Geography - Forecasts From 2024 To 2029

  • Published : Mar 2024
  • Report Code : KSI061616767
  • Pages : 147

The AI in the Urban Planning market is anticipated to expand at a high CAGR over the forecast period.

The AI in the Urban Planning market refers to the use of artificial intelligence (AI) technology to address different issues and possibilities in urban development and administration. This market includes a diverse spectrum of AI solutions, tools, and services aimed at improving urban efficiency, sustainability, and livability.

Some aspects of the AI in urban planning market are data analysis and predictive modelling, smart infrastructure planning, and traffic management and mobility solutions. AI systems analyze enormous amounts of data to detect patterns, trends, and correlations, anticipating future urban trends such as population increase, transportation congestion, and housing demand.

Smart infrastructure design makes use of artificial intelligence to optimize infrastructure layouts, improve resource allocation, and increase system efficiency. AI-powered traffic management systems track traffic flow, detect congestion, and optimize signal timing. These technologies also help to build intelligent transportation systems, such as self-driving cars and ride-sharing platforms, which improve infrastructure efficiency and resilience.

Market Drivers:

  • Rapid urbanization is contributing to AI in the Urban Planning market growth

The worldwide rise of urban populations needs effective urban planning solutions to address transportation, housing, infrastructure, and sustainability challenges, with AI technology offering novel approaches to optimizing urban development and management.

Among various products available in the market, Blackshark.ai SYNTH3D is a 3D model of the planet's surface created using 2D satellite and aerial images. It contains topography elevation, buildings, plant coverage, and infrastructure, depicting each nation, city, building, and detail in a region-specific, geo-typical manner, with data streamed from blackshark.ai servers and turned into a realistic scene at runtime.

Rapid urbanization poses both difficulties and possibilities for urban planners, and AI technologies provide novel answers to complicated urban development concerns and produce more sustainable, livable cities in the future.

  • Smart city development is contributing to AI in the urban planning market growth

Smart city development transforms urban services and quality of life by incorporating AI into urban planning, notably in areas such as smart transit, infrastructure, energy management, and governance, hence improving urban services.

Among various products, one of the products is CitySwift Explore, which is a complete solution for breaking down bus network data silos, resulting in enhanced service delivery, detailed reporting, and more openness and visibility across different operators and routes.

Smart city development encourages AI use in urban planning for data-driven decision-making, predictive analytics, resource management, transportation solutions, public involvement, safety improvements, and urban resilience projects. The demand for AI-driven urban planning solutions is predicted to increase.

Market Restraints:

  • Data availability and quality hamper the market growth

AI algorithms in urban planning rely significantly on data for insights and suggestions; yet, fragmented, insufficient, or low-quality urban planning data can impede accurate analyses and projections, and restricted access to trustworthy data sources might reduce their usefulness.

AI in the urban planning market is segmented based on different deployment models

AI in the urban planning market is segmented based on different deployment models. Cloud-based AI systems for urban planning employ internet-based servers to store, process, and analyze enormous amounts of urban data, giving planners scale, flexibility, and easy access to advanced analytics tools.

On-premise AI solutions for urban planning entail putting software and hardware infrastructure within agencies, which offers better control, security, and customization but necessitates a significant upfront investment and upkeep.

Application Case Study:

CitySwift -  Oxfordshire County Council is using CitySwift to track a 10% bus productivity objective, with an emphasis on the impact of congestion-reduction initiatives such as a parking tax, traffic filters, and a zero-emission zone. The platform includes data analytics and visualizations for route durations, bus average speeds, network bottlenecks, service punctuality, and passenger delay minutes, providing a strong return on green investment.

North America is anticipated to hold a significant share of the AI in the urban planning market-

North America, particularly the United States, is a hotbed of technological innovation and AI development, with major IT businesses such as Urbanistai, Autodesk, and TLM, Inc. actively creating AI solutions for industries such as urban planning.

North American governments are expanding their investments in smart city programs and urban development initiatives that use AI and data analytics to improve infrastructure, transportation systems, and public services.

North America is anticipated to hold a significant share of AI in the urban planning industry. However, real market dynamics might differ depending on regional legislation, economic situations, and technology improvements.

Key Developments:

  • February 2024: CitySwift secured €14.5 million in a €7 million investment round headed by Gresham House Ventures, with previous investors including aCT Venture Capital, Irelandia Investments, and the Western Development Commission. The investment would speed up platform development, create intelligent data solutions, and deliver personalized client assistance.
  • November 2023:  Eagle 3D Streaming and blackshark.ai collaborated to build a geographic 3D digital twin that could be accessed through any web browser. The real-time, realistic, and semantic twin enables users to explore any environment in photorealistic 3D, which benefits businesses and industries. Eagle 3D Streaming provided real-timed visualization, seamless access, collaboration, cost-effectiveness, scalability, and increased accessibility.

Company Products:

  • ArcGIS Urban: ArcGIS Urban is a web-based 3D program that enables planners and design professionals to collaborate on housing availability, sustainability goals, and economic trends. It streamlines land use and zoning planning, saves time and money, and encourages a more sustainable future. The program supports on-the-fly situations, provides simple visualizations, and expands its reach through online comments and polls.
  • Rhino’s 3D: Rhino is a landscape design application that combines 3D modeling skills with Grasshopper's parametric tools and plugins. It enables users to develop sophisticated 3D projects with terrains, vegetation, and parametric objects while displaying realistic visuals and tour animations.

Market Segmentation:

  • By Deployment
    • Cloud
    • On-Premise
  • By Application
    • Public Transport
    • Security monitoring
    • Waste management
    • Infrastructure planning
    • Others
  • By Geography
    • North America
      • USA
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • Germany
      • France
      • UK
      • Spain
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • UAE
      • Israel
      • Others
    • Asia Pacific
      • China
      • Japan
      • India
      • South Korea
      • Indonesia
      • Taiwan
      • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key benefits to the stakeholder

2. RESEARCH METHODOLOGY

2.1. Research Design

2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. Analyst View

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. AI IN URBAN PLANNING MARKET BY DEPLOYMENT

5.1. Introduction

5.2. Cloud

5.2.1. Market opportunities and trends

5.2.2. Growth prospects

5.2.3. Geographic lucrativeness 

5.3. On-Premise

5.3.1. Market opportunities and trends

5.3.2. Growth prospects

5.3.3. Geographic lucrativeness 

6. AI IN URBAN PLANNING MARKET BY APPLICATION

6.1. Introduction

6.2. Public Transport

6.2.1. Market opportunities and trends

6.2.2. Growth prospects

6.2.3. Geographic lucrativeness 

6.3. Security monitoring

6.3.1. Market opportunities and trends

6.3.2. Growth prospects

6.3.3. Geographic lucrativeness 

6.4. Waste management

6.4.1. Market opportunities and trends

6.4.2. Growth prospects

6.4.3. Geographic lucrativeness 

6.5. Infrastructure planning

6.5.1. Market opportunities and trends

6.5.2. Growth prospects

6.5.3. Geographic lucrativeness 

6.6. Others

6.6.1. Market opportunities and trends

6.6.2. Growth prospects

6.6.3. Geographic lucrativeness 

7. AI IN URBAN PLANNING MARKET BY GEOGRAPHY

7.1. Introduction

7.2. North America

7.2.1. By Deployment

7.2.2. By Application

7.2.3. By Country

7.2.3.1. United States

7.2.3.1.1. Market Trends and Opportunities

7.2.3.1.2. Growth Prospects

7.2.3.2. Canada

7.2.3.2.1. Market Trends and Opportunities

7.2.3.2.2. Growth Prospects

7.2.3.3. Mexico

7.2.3.3.1. Market Trends and Opportunities

7.2.3.3.2. Growth Prospects

7.3. South America

7.3.1. By Deployment

7.3.2. By Application

7.3.3. By Country

7.3.3.1. Brazil

7.3.3.1.1. Market Trends and Opportunities

7.3.3.1.2. Growth Prospects

7.3.3.2. Argentina

7.3.3.2.1. Market Trends and Opportunities

7.3.3.2.2. Growth Prospects

7.3.3.3. Others

7.3.3.3.1. Market Trends and Opportunities

7.3.3.3.2. Growth Prospects

7.4. Europe

7.4.1. By Deployment

7.4.2. By Application

7.4.3. By Country

7.4.3.1. Germany

7.4.3.1.1. Market Trends and Opportunities

7.4.3.1.2. Growth Prospects

7.4.3.2. France

7.4.3.2.1. Market Trends and Opportunities

7.4.3.2.2. Growth Prospects

7.4.3.3. United Kingdom

7.4.3.3.1. Market Trends and Opportunities

7.4.3.3.2. Growth Prospects

7.4.3.4. Spain

7.4.3.4.1. Market Trends and Opportunities

7.4.3.4.2. Growth Prospects

7.4.3.5. Others

7.4.3.5.1. Market Trends and Opportunities

7.4.3.5.2. Growth Prospects

7.5. Middle East and Africa

7.5.1. By Deployment

7.5.2. By Application

7.5.3. By Country

7.5.3.1. Saudi Arabia

7.5.3.1.1. Market Trends and Opportunities

7.5.3.1.2. Growth Prospects

7.5.3.2. UAE

7.5.3.2.1. Market Trends and Opportunities

7.5.3.2.2. Growth Prospects

7.5.3.3. Israel

7.5.3.3.1. Market Trends and Opportunities

7.5.3.3.2. Growth Prospects  

7.5.3.4. Others

7.5.3.4.1. Market Trends and Opportunities

7.5.3.4.2. Growth Prospects

7.6. Asia Pacific

7.6.1. By Deployment

7.6.2. By Application

7.6.3. By Country

7.6.3.1. China

7.6.3.1.1. Market Trends and Opportunities

7.6.3.1.2. Growth Prospects

7.6.3.2. Japan

7.6.3.2.1. Market Trends and Opportunities

7.6.3.2.2. Growth Prospects

7.6.3.3. India

7.6.3.3.1. Market Trends and Opportunities

7.6.3.3.2. Growth Prospects

7.6.3.4. South Korea

7.6.3.4.1. Market Trends and Opportunities

7.6.3.4.2. Growth Prospects

7.6.3.5. Indonesia

7.6.3.5.1. Market Trends and Opportunities

7.6.3.5.2. Growth Prospects

7.6.3.6. Taiwan

7.6.3.6.1. Market Trends and Opportunities

7.6.3.6.2. Growth Prospects

7.6.3.7. Others

7.6.3.7.1. Market Trends and Opportunities

7.6.3.7.2. Growth Prospects

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

8.1. Major Players and Strategy Analysis

8.2. Market Share Analysis

8.3. Mergers, Acquisition, Agreements, and Collaborations

8.4. Competitive Dashboard

9. COMPANY PROFILES

9.1. Urbanistai

9.2. Autodesk Inc.

9.3. Space Syntax Limited

9.4. ArcGIS

9.5. Robert McNeel & Associates, (TLM, Inc.)

9.6. Treepedia

9.7. Blackshark

9.8. Cityswift


Urbanistai

Autodesk Inc.

Space Syntax Limited

ArcGIS

Robert McNeel & Associates, (TLM, Inc.)

Treepedia

Blackshark

Cityswift