UrbanTwin

UrbanTwin aims to develop and validate a holistic tool to support decision-makers in achieving environmental goals, such as the Energy Strategy 2050 and the vision of climate-adaptive "sponge cities". The tool will be based on a detailed model of critical urban infrastructure, such as energy, water, buildings, and mobility, accurately simulating the evolution of these interlinked infrastructures under various climate scenarios and assessing the effectiveness of climate-change-related actions.

Urban areas are responsible for 75% of greenhouse gas emissions while rising temperatures significantly impact their liveability. They represent a natural integrator of several systems, including energy, water, buildings, and transport. So, they represent the ideal setting for implementing a coordinated, multi-sectoral response to climate changes leveraging digitalization as a systemic approach.

In UrbanTwin, we want to collect information from multiple sources by using new edge artificial intelligence (AI) platforms and integrate them using cloud computing technologies on a detailed model of critical urban infrastructures, such as energy, water (both clean and waste), buildings, and mobility and their inter-dependencies.

As a cutting-edge example of what digitalization and AI can offer, this tool will be able to consider underlying socio-economic and environmental factors, while assessing the effectiveness of climate-change-related actions beforehand. The goal is to develop a technology that is open and can be applied to other urban areas in any region of Switzerland.

UrbanTwin website

Related Publications

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Taji, Hossein; Miranda Calero, José Angel; Peon Quiros, Miguel; Atienza Alonso, David
2024-07-04	ISLPED '24: Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design
M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems
Baghersalimi, Saleh; Amirshahi, Alireza; Forooghifar, Farnaz; Teijeiro, Tomas; AMIR AMINIFAR; Atienza Alonso, David
2024-05-29	ACM Transactions on Intelligent Systems and Technology
SAT-based Exact Modulo Scheduling Mapping for Resource-Constrained CGRAs
Tirelli, Cristian; Sapriza, Juan; Rodríguez Álvarez, Rubén; Ferretti, Lorenzo; Denkinger, Benoît Walter; Ansaloni, Giovanni; Miranda Calero, José Angel; Atienza Alonso, David; Pozzi, Laura
2024-04-08	ACM Journal on Emerging Technologies in Computing Systems
Decentralized Federated Learning for Epileptic Seizures Detection in Low-Power Wearable Systems
Baghersalimi, Saleh; Teijeiro, Tomas; Aminifar, Amir; Atienza Alonso, David
2023	IEEE Transactions on Mobile Computing