Urban Planning & Smart Cities

Smart Cities

Generate, validate, and compare smart city development scenarios with integrated spatial analytics — replacing fragmented GIS workflows with data-driven planning.

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Also in Urban Planning & Smart Cities Compact City City Development 15-Minute City Masterplanning Land Use Prediction Amenity Planning
Aerial view of a smart city with integrated mobility, energy, and data infrastructure overlaid
Trusted by
TAKENAKA Jacobs EMAAR McKinsey Dubai Municipality egis
The Problem

Fragmented workflows create late-stage planning surprises

Smart city planning requires integrating data from multiple systems — mobility, energy, land use, demographics — that are managed in separate tools. Fragmented workflows create late-stage feasibility surprises and slow stakeholder alignment, delaying investment decisions and planning approvals that cities cannot afford to miss.

Without DBF With DBF
Smart city KPIs modelled across disconnected GIS and planning tools
Single integrated workflow from spatial data to KPI validation
Limited scenario options slow stakeholder alignment
50+ smart city scenarios generated and compared in parallel
Sustainability targets bolted on after spatial planning
Sustainability and liveability KPIs built in from the first iteration
Investment decisions made without validated spatial evidence
Traceable, comparable outputs ready for authority and investor reporting
Process

How It Works

01
Data Ingestion

Upload site boundaries, GIS data, demographic datasets, and planning policy constraints. DBF integrates multi-source data into a single spatial model.

02
Scenario Generation

AI generates 50+ development scenarios — each scored against planning, liveability, sustainability, and infrastructure KPIs simultaneously.

03
Spatial Analysis

Every land use configuration, density gradient, and infrastructure relationship is evaluated. Conflicts and opportunities surface with spatial evidence.

04
KPI Scoring

Scenarios are automatically scored against liveability, sustainability, infrastructure capacity, and planning policy compliance.

05
Stakeholder Comparison

Comparable scenario outputs ready for planning authority, investor, and community stakeholder review from day one — not after weeks of consultant work.

06
Authority Reporting

Planning-authority-ready evidence outputs and spatial data exports delivered from the feasibility stage — not the planning application stage.

Platform

Built for smart city planning complexity

Every DBF capability is designed for the specific demands of smart city planning — where mobility, energy, land use, and demographics interact across city-scale spatial scenarios.

  • AI smart city scenario generation
  • Multi-source GIS and IoT data integration
  • Smart city KPI framework and scoring
  • Liveability and sustainability metric integration
  • Land use change prediction
  • Planning-authority-ready reporting outputs
Who Uses DBF

Use Cases

Smart city planning team reviewing integrated spatial analytics and development scenario comparisons
01
Municipal Government
Planning Authority Director

Validate smart city development scenarios against planning policy, infrastructure capacity, and liveability targets before planning applications are submitted.

02
Smart City Developers
Development Director

Test mixed-use smart city configurations against infrastructure investment, sustainability KPIs, and investor return targets before capital is committed.

03
Government Agencies
Urban Policy Lead

Assess smart city policy scenarios against economic development targets, infrastructure capacity, and demographic demand forecasts simultaneously.

04
AEC Consultancy
Project Director

Deliver faster, more evidence-based smart city feasibility with validated spatial scenarios, KPI scoring, and planning-authority-ready outputs.

50+
Scenarios Validated
Per planning cycle
Multi-source
Data Integration
GIS, IoT, demographic
Pre-design
Full Pipeline
Evidence before planning
Future Vision

From reactive zoning to proactive, evidence-based urban strategy

As urbanisation accelerates and smart city investment grows globally, the demand for data-driven urban scenario validation will become a planning requirement. Cities that plan with spatial evidence will attract investment and deliver better outcomes faster. DBF enables planners to move from reactive zoning management to proactive, evidence-based urban strategy — validating and communicating smart city scenarios with the speed and rigour that modern city development demands.

Future vision of a data-driven smart city with integrated mobility, sustainability, and digital infrastructure
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