IoT dataset of event detection which contains seasonal factor

Question

I am looking for a dataset which is related to IoT data. Specifically, when there are any events detected, the IoT device will record that event immediately. And it should have the seasonal factor: there would be more events detected in some specific periods of the day than the others.

For example, there is an IoT device which will record any person passing through the gate, then in the daytime, there would be more than in the night time.

What I really want is not the detail of the event, but the statistics on the number of events detected on continuous time windows of the day. This is related to time series-formed dataset.

Thank you in advance :-)

Answer 1

The Open Data group from the City of Zürich publish nearly 10 years of pedestrians (Fussgänger) and bicycles (Velos) automatic measurement (counting) data.

Pedestrian and bicycle traffic has the following expected seasonality: time of day, day of week, week of year, as well as heavy dependence on holidays, weather, etc.

You can find the station metadata, including geospatial station data: Standorte der automatischen Zählgeräte für den Fuss- und Veloverkehr (specifically this CSV with latitude and longitude, but also GeoJSON, KML, etc)

And the measurement data in yearly CSV files: Daten der automatischen Fussgänger- und Velozählung - Viertelstundenwerte (it's not a row per event, but number of events per 15 minutes)

If the German text description isn't clear (also after machine translation), I think the CSV should be clear (each 15 minute point gives you the count of velo_in/velo_out (bikes) and fuss_in/fuss_out (pedestrians).

---

This data was used in a recent Hackathon, for which you can see the project results: https://hack.twist2018.ch/project/17 and http://hack.twist2018.ch/project/5