Meet Bettair, one of the top 8 EDI startups! They are working on a solution for long term pollution forecast in urban areas, using data from Ubimet.
Can you tell us how you came to your Startup idea? We would also love to know more about your team, what makes your dynamic so promising and impactful?
The founders of the startup participated in the Citisense European project where they both learned about suitable technologies to measure the pollution in urban areas and got in touch with the European academic and industrial actors related to pollution monitoring in cities.
At the end of the project, they decided to go forward and attempt to exploit this technological knowledge, so the team set up a small pilot and collected some data to figure out a stable calibration procedure. After some work, we found out a possible method for a stable and long-lasting calibration method of low-cost sensors, so we decided to evaluate its performance in another pilot with several nodes and…
What makes your solution unique? What is the impact you are trying to achieve?
- Involvement with several academic partners from early stages of the project.
- Involvement with several agents of the industry and the startup environment.
- Experienced team (leading, developers’ hardware / software).
- Accuracy of the measurement obtained from an early scientific approach where both the sensing nodes and the calibration algorithms are designed together. This fact allowed us to get access to high quality data from the very beginning. (access to proprietary datasets)
What challenge have you selected for the EDI incubation programme and why did you choose it?
We decided to take the challenge related to long term pollution forecast in urban areas. It was a service on our technological roadmap and the EDI program let us get in touch with the industrial partner UBIMET. So, EDI has been helping us to fasten the developing pace of the services in our pipeline.
For a few months you have worked hard in the EDI Experiment stage, developing your Big Data solution even further. Can you please elaborate on your progress and how have you evolved during the acceleration process? How was your experience working with your Data Provider?
We are very satisfied with the ongoing results of the EDI Experiment stage. Initially, we focused our work in three directions: (i) we wanted to test several deployment techniques we already had implemented, (ii) the scalability of the platform and (iii) getting in touch with data providers. Regarding the technical directions, we are currently on track executing the work plan as expected. The work allowed us to identify some flaws and correct them as well as getting in touch with several big data technologies and evaluate their performance without needing to configure them.
We also got in touch with a data provider which allowed us to integrate weather forecasting data in our algorithms, important mentorships, interesting webinars and other participants.
“EDI is such a cool experience! Startups can get money and support, exploit their knowledge and take advantage of free resources to test and evaluate different technologies of the big data stack.”
After joining and benefiting from the tools EDI provided you, what is your next step?
We were already employing the FIWARE stack, but EDI provided us with technologies from the Apache stack that we have decided to integrate soon to our own platform: NIFI and Apache Kafka.
Finally, what would you say to a startup considering applying to EDI?
EDI is such a cool experience! Startups can get money and support, exploit their knowledge and take advantage of free resources to test and evaluate different technologies of the big data stack.
What are you waiting for?
If you think European Data Incubator may be a good fit for you: