Receive up to € 20k to create your proof of concept


Access to leading corporate partners and opportunities for long-term collaboration
Receive up to EUR 20,000 in funding to draft a proof of concept – without giving up equity
Real-world use cases and unique datasets from established corporations

Data Challenges

DataHub Ruhr is a business building program that connects start-ups with established corporations in the Ruhr region. The program tasks start-ups with developing innovative, data-driven ideas to tackle use cases provided by our corporate partners. As part of a three-month collaboration, start-ups will draft a proof of concept, with the opportunity to receive up to EUR 20,000 in funding.
Smart Data Corrector
Critical infrastructure requires the highest level of data quality. But outdoor sensors are exposed to rough environments and not always deliver the most accurate information. Dirt, aging of sensors and vandalism are typical reasons for data errors. Manual data correction requires a lot of experience, focus and time. It does not scale well with the increasing number of sensors installed. Can smart algorithms come to the rescue?

Use Case

For over 100 years the EGLV provides water management services in the Ruhrgebiet region. At about 100 locations state-of-the-art sensor systems permanently check for changes of in the environmental conditions. To manage water resources in a sustainable and efficient way, high quality data is required on a permanent basis. Unfortunately, sensors are impacted by rough outdoor conditions and unexpected external factors. As of today, the identification and correction of inaccurate sensor data is a manual process. Highly trained and experienced data experts fix data points on a daily basis.

We want to support the current process with a new “Smart Data Corrector”, which identifies inaccurate data points automatically and provides a recommendation how to fix them based on certain rules, analysis and understanding of the hydrological system combined with experience. This can be gathered through historical corrections made. The data expert reviews recommended values by the “Smart Data Corrector” and accepts them or enters correct values manually, if required.

A project duration of approximately 2 months is expected.

What you will need

  • Experience in the field of IoT and sensor data
  • In-Deep knowledge of outlier detection and pattern recognition
  • Experience with intuitive UI and UX development is a plus
  • Motivation to challenge the status quo

Expected result

  • Reliable identification of 99% of sensor measurement errors
  • For all measurement errors a recommendation of corrected values is given
  • In 90% of cases the data experts accept the recommended value as a valid fix
  • Total effort of the data expert is reduced by 50%


The project can be divided into three milestones:

  1. The first milestone is reached when the data has been loaded properly and visualizations and descriptive statistics have been used to understand the problem of identifying and correcting errors.
  2. In the second phase of the project, analysts should use the insights from the first phase to implement an algorithm that reliably identifies errors.
  3. The third milestone is reached when an algorithm is implemented that not only identifies errors but also reliably corrects them. The output of this algorithm is then checked together with EGLV and if deemed satisfactory the projects is concluded.
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Let's talk

Felix Schröder
Program Manager DataHub Ruhr

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Let's talk

Felix Schröder
Program Manager DataHub Ruhr