Data Analytics and Application Center (DAAC): Smart data
At a new Digital Lab, Siemens ITS is developing, in cooperation with pilot customers, data-driven applications and services based on artificial intelligence: The solutions range from network analyses and smart traffic management functions right up to fleet management solutions and tools for intermodal mobility management.
by Peter Rosenberger
For cities, looking ahead into the future of mobility has never been as worthwhile as it is today. A gigantic wave of change is rolling towards them, brought on by disruptive technologies and new, additional modes of transport. Whether this will bring them lasting benefits or chronical suffering, depends above all on the role the cities themselves are going to play. The more actively a municipality is involved in shaping change, the greater the chance it has of being one of the winners.
Fortunately, the brave new world of digital mobility presents not only great challenges, but also fascinating opportunities because the networking of road traffic generates enormous amounts of data, which can then be used to implement innovative solutions. This is precisely the task of the new Data Analytics and Application Center (DAAC), which Siemens ITS set up in spring this year. “We are not developing finished one-for-all products, but rather first-of-its-kind data-driven functions and applications tailored to specific tasks. Of course, these will then be integrated in our products and services," says DAAC manager Dr. Claus Beringer. “That’s why our work does not follow a predefined R&D roadmap. Instead we are developing solutions for specific use cases in close cooperation with our pilot customers. This gives us the agility and flexibility to continually adapt to any changes in requirements that come up during the rapid prototyping process. Hence we are working rather in the way of a start-up."
This approach creates totally new options when it comes to starting a design-thinking process and then implementing specific applications and functions requested by the customer. Of course, the DAAC team profits from internal resources from across the group, such as Mindsphere, the open Internet-of-Things operating system. Customers do not necessarily have to be cities. They may also be operators of individual vehicle fleets. DAAC's first projects include, for example, the fleet management for a Lisbon-based e-bike sharing system that covers around 1000 electric bikes and 140 stations. As a special feature, the concept must be able to ensure that enough e-bikes are available at any time in any part of the city. This is made possible by a smart forecasting tool that precisely predicts how users behave in different weather conditions at a specific time on a certain day of the week.
We are not developing finished one-for-all products, but rather first-of-its-kind data-driven functions and applications tailored to specific tasks.Dr. Claus Beringer, Head of the Data Analytics and Application Center
There are basically three core areas where the DAAC offers genuine added value to customers. The first one is classic network optimization based on the evaluation of existing traffic data, plus any additional data that may be available from operators of navigation or weather information services, for instance. In this area, the initial focus is often on the creation of the greatest possible transparency (Descriptive Analytics), such as in the case of an ongoing project in the Belgian region of Flanders. Here DAAC will build a highly advanced dashboard to monitor around 1,600 controllers. In a first step, the project will serve to identify the bottom-10 junctions so that, later, targeted measures can be defined to improve traffic flow.
Core area number two, as Dr. Beringer and his team see it, is the development of innovative solutions for managing fleets within the mobility network, for instance data-driven forecasting models (Predictive and Prescriptive Analytics) as for the above-mentioned project. Here the possible fields of application are extremely diverse. They range from tailor-made management systems for shared-vehicle fleets, such as the e-bikes in Lisbon, to planning and scheduling tools for highly agile bus systems that do not require fixed timetables and bus stops. It goes without saying that such prognosis tools will also be used in the first core area, network control, for instance for predicting congestion in urban street networks or for predictive infrastructure and vehicle maintenance.
The DAAC's third core topic will be assistant systems that support travelers by managing their trips across different transport modes. The vision for all three core areas is to develop a system that balances mobility demand and ecological requirements. To do this, it must be able to analyze current and historical data, independently initiate suitable control measures, examine their impact and adapt the approach accordingly – right up to providing the users with suggestions for alternative routes or the use of other modes of transport.
Peter Rosenberger works as a journalist in Birkenau
Picture credits: Siemens AG
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