Research Direction

AI-driven decision intelligence for community digital twins

This research investigates how real-world community data, digital-twin state, predictive analytics, scenario simulation and AI-driven decision intelligence can be integrated into an explainable and interoperable decision-support platform.

Burnaby, British Columbia serves as the initial real-world case study. The current 3D environment is the visualization layer of the broader research platform.

01

Digital Twin State

Representing community entities, spatial relationships and evolving state independently of source-system schemas.

02

AI Decision Intelligence

Exploring machine learning, language models and agentic systems for evidence-grounded decision support.

03

Explainability & Evidence

Connecting AI outputs to provenance, uncertainty, supporting evidence and human oversight.

System Architecture

From real-world community data to explainable decision support

01

Community Data

02

Data Integration

03

Twin State

04

Prediction & Simulation

05

AI Intelligence

06

Decision Support

Data Foundation

Grounded in authoritative municipal data

The initial implementation uses City of Burnaby Open Data. The first implemented ingestion pipeline retrieves all 4,804 street features through the municipal ArcGIS REST service, validates the authoritative feature count and maps source records into digital-twin road-segment entities.

4,804

Street features ingested

54,789

Building footprints visualized

3D

Interactive city representation

Burnaby Open Data

Primary municipal source

The current 3D environment visualizes municipal spatial data with illustrative animation. Vehicle and transit movement does not represent live City of Burnaby operational data. Predictive and scenario simulation capabilities are part of the ongoing research and development.

Research Status

Active research and development

Implemented

Municipal street-data ingestion, twin-domain mapping, automated tests and interactive 3D visualization.

In Progress

Digital Twin State Layer, persistent geospatial state, additional municipal entities and platform integration.

Planned

Predictive models, scenario simulation, explainable AI and evidence-grounded agentic decision support.

Research Context

Interoperability and transferability between Canadian municipal applications and European smart-community research.