Berlin, August 2024, Benno Bock
Two decades ago, the amount of mobility data we can work with today was unthinkable. Thanks to increasing digitalisation, we now have a whole new range of data sources for mobility demand in addition to traditional survey data and counting data. Mobile phone data (also known as 'floating phone data') can currently be regarded as the crème de la crème in this segment.
This data provided by mobile network operators is an excellent and, above all, comprehensive source for estimating mobility needs. Recording movements via smartphone apps is also a good way of gaining insights into specific mobility patterns at an individual level.
But does the new data also lead to new fields of application? In this article, we would like to analyse where the use cases for new types of mobility demand data are seen - by those who should know: the data providers. The question here is whether the application context also extends beyond the classic application area of survey and counting data. The whole thing also has a very practical significance for the MultiMoFusion research project, as it is precisely the data sets mentioned above that are to be upgraded in this project. MultiMoFusion started in November and will run for three years. The consortium is being funded as part of the FFG call for proposals "Mobility (2022) - Cities and Digitalisation".
Invenium is a technology company specialising in the development of solutions for processing and analysing large volumes of data. Its products support companies in optimising processes and gaining valuable insights.
Teralytics provides data-driven insights into mobility by using anonymised telecoms data.
Senozon is a leading provider of simulation software for transport planning and analysis. Their solutions optimise mobility and transport systems worldwide.
MotionTag provides innovative mobility data collection and analysis technologies for businesses and governments. Their solutions enable precise collection of movement data and provide insights into mobility behaviour to optimise transport systems and services.
Die Anbieterwebseiten wurden im Rahmen des Projekts systematishc nach Use-Cases analysiert. Zusammenfassend kann man folgende, potentielle Use-Cases für Fusionsdaten auf Basis der beiden originären Datensatzformen FPD und SMASI sehen:
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