Our User Centric Digital Twins approach was designed to address the challenge of fitting human’s behavior into digital twin models, so that cities can base their strategies upon a picture that effectively integrates both the technical and the people perspective.
Our deliverables draw from a scientific methodology as a step-by-step process to characterize the issues at hand, to build a replicable model, to analyze its outputs. Our method was built working closely with social & cognitive scientific experts reflecting dozens of years of research.
For any application we typically work with academic partners in the field of cognitive, data and social science to produce best in class models. See some of our partners
Agent-based modeling (ABM) is a technique to gain a deeper understanding of system behaviors; they simulate how city stakeholders, citizens, corporations, NGOs, public entities interact, and what are the likely outcomes of their interactions.
In agent-based models, agents are software entities. Each agent represents an autonomous entity, with its own behavior and decision capabilities. In Insight Signals’ User Centric Digital Twins, agents often model citizens, characterized by a socioeconomic data, which influence the agent’s behavior. Agent-based models allow to recreate the complex dynamics of the real individual agents.
State of the art AI techniques, are used to calibrate digital twin parameters, so that the predictions of a digital twin are consistent with real-world data.
The Digital Twin Dynamo platform is the repository where any city, partner, customer can have access to its own Digital Twin output. User friendly dashboards provide insights to :
Platform results can be shared to involved stakeholders, departments, partners. The data can also be downloaded from our API to fuel customers own analytical platforms.
Most countries have rightly adopted protective privacy laws to restrict use of private data to limited areas, and with user consents.
Insight Signals approach goes one step further in guaranteeing individual privacy because our methodology only uses aggregated and anonymized data. Our Population Replicas are designed to reproduce well the aggregated behavior of the real population. without any personal link between digital agents and humans