HOW SELF-SERVICE ANALYTICS

HOW SELF-SERVICE ANALYTICS HELPS CITIES UNDERSTAND URBAN TRAFFIC AND MOBILITY

Over the past decade, the urban mobility landscape has changed enormously. Not only have new modes of (micro)mobility emerged; traffic and mobility management is experiencing a surge in innovation.

Traffic diverted from the closed A45 motorway is causing a major obstruction in the German town of Lüdenscheid. The heatmap shows northbound motorway traffic that has been rerouted through the town centre. Blue represents faster traffic, and pink slower traffic. This analysis is straightforward to perform with xyzt.ai and connected vehicle data and does not require any data science skills. Any user can obtain these insights directly and report on them within minutes.

xyzt.ai is a self-service analytics and reporting tool for cities. It handles an extremely broad range of spatio-temporal mobility data sources, including floating car data (see image), traffic count data and air quality data, to name just a few. Analysts can obtain immediate insights from interactive data exploration using spatial, temporal and attribute filtering, allowing them to generate velocity profiles, origin–destination analyses, change and trend analyses, and much more besides. xyzt.ai scales to big data sources, including floating car data with billions of records.

Just think of the many new ways to measure traffic, for instance. They now range from conventional traffic counters, licence plate recognition, CCTV cameras and image recognition to floating car data obtained from modern always-connected vehicles and privacy-preserving crowdsensing data.

This is creating immense opportunities to understand the real-time and historical mobility situation and its evolution, both within city centres and the surrounding areas. Given the importance of sustainability and safety in public policy today, cities need to be in control and must leverage these new and alternative data sources. However, quickly extracting insights from this big data is no easy feat.

While large cities can invest in a team of data scientists to do the number crunching, this is beyond the financial reach of medium-sized and small cities. And even if the municipal administration has a data science unit, it can take months to integrate a new data source and answer the questions posed by the press or policymakers. With xyzt.ai, this time can now be dramatically reduced from months to minutes. xyzt.ai is an easy-to-use, self-service spatio-temporal mobility analytics platform. It works with any data that has a geospatial component (where) and a temporal component (when). Any other attributes, such as velocity, acceleration, trip length or CO2 emissions, are compiled with these two basic components and then leveraged to help the user understand what is happening. xyzt.ai serves as an intuitive BI tool, but it is specifically designed to handle the many new sources of mobility data. You can work with the existing data in the platform and feed in your own data. xyzt.ai allows you and your team to manage projects independently and generate reports via the interactive dashboards. It equips you with the tools you need to analyse, visualise and report in minutes instead of months, putting you in control of the mobility situation.

Contact xyzt.ai at nick.debeer@xyzt.ai for more information or a live demo, or visit www.xyzt.ai. Visit xyzt.ai at stand G010c in hall 1.2.

XYZT.AI Brouwersstraat 80 3000 Leuven Belgium

Nick De Beer Head of Global Business Development +32 (0) 478065970 nick.debeer@xyzt.ai www.xyzt.ai