Decision support for I-US!
A decisive assist for policy-makers, local planners and industry leaders
Imagine a world where industrial facilities located in or near urban areas collaborate with the surrounding community to create mutual benefits while promoting sustainability.
By joining forces, companies can optimize their resource use, reduce waste generation and boost economic growth while creating a better quality of life for everyone involved.
How to undertake this process with knowledge- and information-based decisions?
In the industrial-urban symbiosis (I-US), the industrial side invests its own risk capital, while on the other side public authorities and utility companies invest – directly or indirectly – the capital of citizens.
Indeed the choice of investing money and energy in such a new resource management model brings about great challenges.
Decision-makers on both sides would like to know in advance how the profit and loss account will unfold through the years, when that specific urban-industrial symbiosis system will take-off and start returning dividends, etc. To make informed, knowledge-based decisions they try to gather as much information as possible about demand trends, material flows, the yields and efficiency of industrial processes, inflow and outflow prices, and so on.
The SYMSITES project eases the way to this scheme of circular economy in two important ways:
- first, decision-makers have a reference industrial model: it is the EcoSite model, that encompasses the thread of material and energy flows and their rates, well defined technologies for each transformation, relevant efficiency curves, and life-cycle analyses.
- Second, in order to pave the way to best-informed decisions about the deployment, ramp-up and optimal management of new I-US settings, the SYMSITES partners ITG (Instituto Tecnológico de Galicia) and the Italian SME KlinK Srl are developing a digital platform, that exploits Artificial Intelligence (AI) for digital modeling and simulation.
If simulation is often seen as the silver bullet to support difficult decisions, the underlying models are the actual engine of simulations.
But, who makes the model?
Long time, most modelers fall into two camps: those who think of models as sophisticated thought-experiments, because you can never model the real world in sufficient detail, and those who think it is possible to build good models of the real world and make predictions on that basis.
The first group leads to abstract models which concentrate on a limited set of processes that allow manipulating elements to explore system responses. Models of the second type have as much as possible of the real world represented inside.
What approach is best when dealing with setting up or upgrading an I-US system?
Both sets of models are founded on knowledge from the real world, but both give artificial closure to systems that aren’t closed: still both may act as a medium to store knowledge and test it for consistency in the complicated net of I-US decisions.
The SYMSITES DSS digital platform exploits and integrates both approaches.
KlinK applies exploratory modeling techniques to the most abstract facets, like the social impacts of I-US investments, allowing to explore what potential impacts different I-US configurations may have on employment, work and living conditions, and community building.
ITG applies IIOT to feed a federated AI system and a combination of deterministic and statistic models to predict real world quantities from I-US systems already in place (or artificial data when the I-US is only planned or hypothetical).
During the workshop Water2030 held in January 2023 in Pise (Italy), it was confirmed that, thanks to this approach, policy-makers, regional planners, industry leaders will have a powerful tool to make robust decisions, that is decisions that keep valid also in fast changing contexts.