Inspiration and what it does

Air quality is a matter of importance nowadays in smart cities. Raw data is not imformative for pedestrians, so we thought that converting pollution data to relevant information like effective user exposure is better than giving a lot of unprocessed citizens-useless information.

How we built it

First we had to understand the whole symbIoTe platform because our enabler needs a lot of microservices in order to run it. Afterwards, we worked over the sample Enabler provided by the organizers. We added functionalities to this enabler and build a REST API.

In order to show the enabler possibilities, we developed a simple client to visualize some data provided by our service.

Challenges we ran into

symbIoTe - Enablers Challenge

Accomplishments that we're proud of

To understand and work with a big and distributed architecture. Also, to take significant decisions to have our product finished on time.

What we learned

SymbIoTe platform, microservices-based architecture, Spring, Docker

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