Particle community, we need beta users!
Machine learning is becoming ever more important for synthesizing and learning from data captured by connected devices (like Nest or Fitbit), but solutions take time to build and are often challenging to implement in practice. At glowfi.sh, we want to change that by making machine learning as easy as posting event data to Particle Cloud. Our API consumes streaming data from devices like the Photon, via Particle webhooks, and is capable of returning predictions back to the device, specified URL, or ThingSpeak for viz.
To get started, just sign up here for free access.
Here are some of our ideas for using glowfi.sh on Particle devices:
- Multi-sensor anomaly detection and notification - Check out our Photon real-time learning example video below (code is at https://github.com/glowfishAPI/glowfish-particle).
- Real-time analytics - post sensor data to glowfi.sh and let us categorize it, compile it, and return statistics of usage.
- Intelligent sensing - we have endpoints that can intelligently group multi-sensor data (with or without supervision) to estimate things like activity patterns or predict outcomes.
- Collaborative data analysis and learning across networks of Particle devices publishing to common public events.
Mike and the glowfi.sh team