Fraunhofer Institute for Computer Graphics Research IGDDigitally connected cities host a growing number of data-generating devices—from traffic lights and security cameras, to distributed sensors that help measure air and water quality, for example. Every second, hundreds of thousands of measurements and data points are created, providing insights into urban life and happenings. Identifiable patterns emerge. And anomalies can flag up significant events.
Identifying accidents and more
As Florian Kirchbuchner, an expert in smart living and biometrics at Fraunhofer IGD, explains: “If, for example, lights go on all around a particular street at three in the morning, that can indicate that something, such as an accident, has occurred.
Machine learning and privacy must go hand-in-hand
As an active member of Germany’s ATHENE research center, Fraunhofer IGD leverages large datasets in combination with machine learning to identify atypical situations. To this end, its experts not only evaluate data at the citywide level; they also analyze sensor data from individual buildings and citizens. Only this granular approach allows researchers to pinpoint potential correlations.
The more sophisticated the digital infrastructure, however, the more vulnerable it is to hacker attacks and data breaches. Kirchbuchner emphasizes: “Privacy and security must go hand-in-hand—we take this into account right from the outset, in the design and development of our software.”