Integrating Spatial Digital Twin with Automation System in Smart Infrastructure Asset Management

Host university

University of Melbourne



Spatial Data Infrastructures, Digital Twin and Decision Support

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Industries are lacking a central platform to gather and analyse disparate OT (Operational Technology) data sources. These data can be location-based, multi-dimensional format with various frequencies and fidelity.   

Therefore, current industrial automation systems need to be improved to aggregate dispersed OT data, for robust management of asset’s health, operation, and root-cause analysis in the Water, Waste-Water, Mining, and Oil & Gas industries.   

Furthermore, there is a lack of spatial dimension in those automation systems, which is essential in developing a smart, resilient, and mature Digital twin integrated with industrial IoT (IIoT), where 2D, 3D, and 4D (time-based) data are used and connected to in-built or third-party analytical tools to better identify and predict production and process bottlenecks.  

As such, a composable system architecture is crucial to address these challenges and improve the efficiency, smartness, and resilience of infrastructure.     


Abbas Rajabifard

RIIS Hub Deputy Director and Lead Chief Investigator
The University of Melbourne
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Jagannath Aryal

Chief Investigator
University of Melbourne
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Bijan Samali

RIIS Hub Lead Investigator
Western Sydney University
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Martin Van Der Merwe

Partner Investigator
Emerson Process Management Australia Pty Ltd
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Les Richards

Partner Investigator
Hawk Measurement Systems
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Govinda Pandey

Partner Investigator
Rockfield Technologies Australia Pty Ltd
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