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A Digital Twin Decision Support System for the Urban Facility Management Process.
Armir Bujari1, Alessandro Calvio1, Luca Foschini1
1Department of Computer Science and Engineering (DISI), University of Bologna, 40136 Bologna, Italy.
Sensors (Basel, Switzerland)
|December 28, 2021
Summary
Smart city applications leverage IoT for real-time digital replicas. A new system, IPPODAMO, optimizes urban facility management by minimizing operational interference and costs.
Area of Science:
- Urban planning and management
- Digital twin technology
- Internet of Things (IoT) applications
Background:
- Increasing IoT deployment enables smart city applications.
- Digital replicas can optimize urban resource management.
- Urban Facility Management (UFM) requires efficient operational planning.
Purpose of the Study:
- Present a proof-of-concept for a Digital Twin solution in UFM.
- Detail the Interactive Planning Platform for City District Adaptive Maintenance Operations (IPPODAMO).
- Demonstrate optimized scheduling for urban maintenance operations.
Main Methods:
- Developed a distributed geographical system (IPPODAMO).
- Ingested and refined heterogeneous data from urban providers.
- Quantified urban activity levels using synthetic indexes.
- Modeled stakeholder interference for informed scheduling.
Main Results:
- IPPODAMO provides a detailed proof-of-concept for UFM Digital Twin.
- The system quantifies urban activity and stakeholder interference.
- Enables informed scheduling to minimize operational interference and costs.
Conclusions:
- Digital Twin solutions like IPPODAMO can significantly enhance UFM.
- Integration of heterogeneous data is key to effective urban modeling.
- Optimized scheduling reduces costs and improves smart city operations.
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