Experimenting with Things using Google Cloud Platform
summary
Deploying 500 sensor Moes (Arduino Leonardo R3 with custom shields: temp/pressure, audio, humidity, light; 300 had specialty sensors — 100 RF, 100 motion via pressure pads, 100 air quality) across 20 ZigBee mesh networks with XBee Pro radios sends bursts every 20s into a pipeline: App Engine → Cloud Storage → Compute Engine → BigQuery (device Cloud adds timestamps). Visualizations show a clear correlation between crowd movement and air quality; 19 of 20 gateways return, ~20 Moes go missing, batteries and venue coordination prove the main operational limits.
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chapters (12)
- 0:00Google I/O sensor project
- 1:23Sensor hardware details
- 2:41Network architecture
- 3:33Data collection workflow
- 4:32Attendee questions and data
- 5:48Visualizing attendee behavior
- 7:27Correlating data trends
- 8:48Visualizing sound levels
- 9:34BigQuery analysis
- 10:38Data pipeline infrastructure
- 14:31Lessons learned and resources
- 18:43Final analysis: The blimp
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