Die Researcherin Laura Knoth erhielt den Preis für die beste Kurzpräsentation auf der SSF 2018.
“Zeit ist die ultimative nicht-erneuerbare Ressource” war eines der Mottos des Symposiums „A Smart Sustainable Future for All 2018“. Auf dieser von den beiden Centren CSDILA und CDMPS der Universität Melbourne in Kooperation mit The World Bank gehosteten Konferenz trafen Mitglieder der akademischen und Forschungscommunity mit Stakeholdern aus Regierungen, Industrie und Fachgremien zusammen, um aktuelle Herausforderungen im Bereich von Nachhaltigkeit und Katastrophenmanagement zu sondieren.
Laura Knoth vertrat hier das Studio iSPACE und präsentierte das Thema „4D Data Infrastructures facilitating Smart City Enablement“. Ihre Kurzpräsentation gewann den Preis für die „BEST SHORT PRESENTATION“.
Nachfolgend finden Sie den englischen Abstract zur Präsentation:
While the term “smart city” is around since the 2000s, a broader interest can be observed since around mid of 2014 (Google Trends). According to Deakin & Al Waer (2011), a smart city can be defined according to four criteria, namely 1) “the application of a wide range of electronic and digital technologies to communities and cities”, 2) “the use of information technologies”, 3) the “embedding of those” and 4) the territorialization of such to bring ICTs and people together. To create a smart city, the first step is to implement measurements, which is enabled by low-cost and improved sensors. The next steps include communication (M2M, Internet of Things (IoT)), real-time analyses (and control of systems), integration of single systems and finally smart services that can be used (Image). Today, mainly the first step is being tackled and the implemented and isolated sensors create a vast amount of data (big data). This vast amount of data can often not be analyzed in a meaningful manner and creates data silos. To overcome this situation, technologies such as machine learning and artificial intelligence are often seen as the “solution” to not drown in the own created data pools. While this might be curing the symptoms, it still does not address the root causes and solutions are still needed for the creation of meaningful integrations and analyses.
However, most data have two properties in common: space and time, which can be used as characteristics for a full integration/aggregation/interaction implementation. This can be done with Spatial Data Infrastructures (SDIs) which have proven before that they are able to bring together information from different sources and integrate them according to their position in space (3D) and time (4D). Nonetheless, as with “physical infrastructure”, there also is the need for a basic 3D “digital infrastructure”, in this case, a sophisticated 3D map that – when filled with information from the implemented sensor systems – can function as a digital twin platform integrating real time data and supporting better decisions, simulations and pave the way to “really” smart cities.