Objectives
Achieve “zero-km carbon neutrality” by quantifying the CO2 emissions of the analyzed system and determining how many trees are needed to absorb those emissions.
Monitor the health of urban green spaces through a sensor-powered digital twin capable of estimating the CO2 absorbed by plants.
Plan interventions for securing and/or replacing plants through a predictive system.
Suggest more sustainable and efficient mobility and energy consumption solutions based on data analysis, also contributing upstream to the overall reduction of CO2 emissions.
Initial challenge
Modern cities are at the center of complex environmental challenges, with an urgent need to reduce CO2 emissions and promote sustainable development. Efficient management of urban mobility, waste, and energy consumption is a critical goal for achieving carbon neutrality at the local level. To this must be added an increasingly conscious and intelligent use of urban green spaces, as a key player in CO2 absorption. Every hectare of urban green space in Italy absorbs 4.2 tonnes of CO2 per year; with 9.3% of Italian territory covered by urban green spaces, around 12 million tonnes of CO2 are absorbed annually, and this contribution could increase with policies that enhance ecological infrastructure.
Solution
Through a 4-step process, E.T. CompleX builds a digital twin that integrates real-time data and predictive systems. The digital twin will be accessible via the cloud as a detailed virtual representation (map) and will allow real-time monitoring and simulation of interventions to reduce CO2 emissions, assessing the environmental impact of urban actions and determining the number of trees needed to achieve full carbon neutrality.
Phase 1. Data collection and integration
- Collecting complex-system data on mobility, waste, and energy consumption, and installing advanced sensors to gather health status and other vital parameters of the trees in the urban green area.
- Centralizing and integrating the collected data into a single system.
Phase 2. Analysis and creation of digital twins
- Using machine learning algorithms to analyze the data and identify patterns and trends.
- Developing predictive digital twins for the complex system and the green area, also taking into account CO2 emissions and the contribution of trees.
Phase 3. Modeling and simulation
- Creating a predictive model to estimate the number of trees needed to offset the CO2 emissions generated by the complex system.
Phase 4. Implementation and monitoring
- Implementing the digital twins in the digital twin platform, allowing access to and interaction with the data and simulations.
- Ongoing monitoring of performance and results, updating and optimizing the models based on newly collected data.
Benefits
E.T. CompleX offers a replicable model for cities, hospitals, and port areas, promoting more sustainable, intelligent management of urban spaces. The platform will allow stakeholders to make decisions based on reliable data, optimizing resources and improving urban quality of life. It will also make a significant contribution to the fight against climate change, promoting the health and sustainability of urban green spaces through accurate monitoring and proactive management strategies. Finally, the success of E.T. CompleX could inspire further innovation and technological applications for a sustainable urban future.
IFAB’s role
IFAB took part in the project as a funding body, selecting it as part of its investment lines in research, innovation, and technology transfer. IFAB’s contribution consisted of recognizing the project’s scientific and practical value and providing financial support, making it possible to carry out the research activities conducted by the technical partners. This involvement confirms IFAB’s mission as an accelerator of high-impact initiatives for the local area and productive system.
Partners
For more information, contact: projects@ifabfoundation.org
