Building Bike Sensors

The material for 20 open bike sensors was ready for the challenge. More than 15 people set to work to produce the sensors with soldering irons and technical skills. It turned out that the task was very challenging in terms of time. Thus, 4 Open Bike sensors were completed during the hackathon and two more were successfully assembled by the participants on their own. For the unfinished sensors, the Challenge participants will soon be able to continue working on them in the light workshop. The rides of the Open Bike sensors of "Hack the paradise!" can be found on this portal: portal.obs-jena.de

Quality assurance of sensor data

The Challenge addressed the question of how the accuracy of sensor readings can be estimated and further processed as a quality feature. This is necessary so that conclusions can be drawn and processes controlled from real-time data from hundreds of sensors in the future, e.g. for environmental and weather data, soil moisture, traffic or energy consumption.

To this end, three possibilities were identified and further explored:

1. The evaluation of the sensor's technical specifications and possibilities for automation,
2. the scan of the data series for irregularities and implausible progressions according to certain criteria,
3. the comparison of the data series with values from trusted, monitored sensors or with the trajectories of the "sensor swarm".

Valuable ideas and, in some cases, algorithms were developed by the participants for all three approaches. Very good contributions have thus been made for the further development of the urban data platform.

Soil Moisture Sensors

The challenge offered two challenges: The team around the mentor Oliver Mothes, Sofia Moya, Daniel Loos and Raúl Hernández worked very creatively on a route optimization for the irrigation management of the urban greenery maintenance as well as on a visualization of microclimate data of the urban forest. Specifically, a route optimization was to be designed for the watering points (urban trees) in the urban area, which the participants solved by calculating permutations. As a result, the shortest route is shown in color on a map of the urban area. For the microclimate data of the urban forest, a map was created in which each measuring station can be selected individually and for which the microclimate data are displayed in a diagram.

The results are impressive: In the voting of the jury and the audience, the team emerged as the winner! In the future, it will be important to push these ideas further, because many other factors are to be considered in the model for route optimization.

Pedestrian frequency

In this challenge, the three-member team led by mentor Lars Hinneburg from Spleenlab GmbH developed a solution based on a combined approach for capturing pedestrian flows by reading MAC addresses of mobile receivers and the video-based, AI-supported analysis of video recordings. Via this solution, pedestrian and bicycle frequencies as well as through-traffic of delivery vehicles can be captured at predefined locations in the city center in a cost-effective, trouble-free and privacy-compliant way using real-time data.

The team presented an initial prototype that was already able to record the people present in the room during the presentation of the results. In the voting of the jury, the vivid results were awarded with a second place! This solution is now to be further developed so that it can be used in the urban environment.

Data visualization of event-related data.

The Challenge asked participants to come up with a creative approach to visualizing large amounts of real-time data. Initial ideas for visualizing streetcar data consisted of displaying their trips on an interactive map in real time to provide useful information to passengers and transit operators.

This solution is based on an intelligent algorithm that collects streetcar data and processes it in real time. In the first step, the positions of the streetcars were displayed in the city map, and other relevant data such as arrival times, delays and detours will follow. The clear visualization will enable, for example, passengers to plan their trips better in the future or Jena's public transport system to monitor the flow of traffic more efficiently.

The results were presented via a user-friendly web application by Challenge participant Lazaro Alonso. The development of an innovative live display of streetcar data was impressive. In the voting of the audience, these vivid results were awarded with a second place!