Smart cities are cities that take advantage of the opportunities offered by digitisation to network their infrastructure accordingly, allowing them to further improve living space and become more sustainable. Swisscom helps cities to achieve this by providing them with tools for planning and networking infrastructures to make management more efficient. In partnership with the town of Pully, which is situated close to Lausanne in the canton of Vaud, Swisscom is realising a project that is exemplary in character. Based on anonymised and aggregated mobile phone data, Swisscom and the town of Pully are working together on a planning method that will improve infrastructure and traffic planning by making traffic flows clearly visible. Robert Gebel, Head of Business Development of Swisscom Enterprise Customers says: 'Compared with current models such as the microcensus, the new method makes it possible to obtain much more precise data. It is able to depict traffic streams in their entirety.'

Ongoing measurements to ensure the right action

Four main traffic arteries traverse Pully, and the town suffers from a high volume of through traffic. It is therefore investing in modern methods to improve the traffic situation and make it easier to access the town centre. At the same time, the town is aiming to improve the quality of life of its residents. The new method delivers benefits to both those who manage the town and its inhabitants.Gil Reichen, Mayor of Pully, said: 'We want to use it to get a realistic picture of the traffic volumes and the length of time that traffic spends in the town centre. These results will enable us to implement city planning measures that really meet the needs of the residents of Pully.'

In a follow-up phase, Swisscom and Pully are planning to work closely with universities to develop further simulation models, which will in future also allow traffic forecasts to be drawn up, for example for major events. Data protection is ensured by this application at all times, as the data is anonymised and aggregated. None of the data can be traced back to individuals.

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