Belly Forecast

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Inspiration

It is waste of time to collect too empty Bellies, but on the other hand those can't be too full. Balance is somewhere between and there analytics is needed.

What it does

Maintenance dashboard shows status per each area. Based on that, maintenance department can see we it needs to act and where not. Fullness speed is predicted and that can be used to plan routes.

How we built it

Data from Smart Bellies were fetched using API. Data were analyzed and predictions were calculated. Output can be seen via tangible dashboard.

Challenges we ran into

Streetreboot 2

Accomplishments that we're proud of

Utilizing data insigths in order to improve city maintenance.

What we learned

Data can be utilized even if public field and potential is huge.

What's next for Belly Forecast

We want to iterate next features and put those in place: better UX and more accurate predictions

Built With

• css
• html
• ibm-spss-modeler
• javascript
• python
• r