Dear users,
We have published a guide where we have explored the possibility of using Elasticsearch to visualize your sensor data for IoT.
https://help.iotify.io/database-generator/analyzing-time-series-sensor-data-with-elasticsearch
My question is what kind of anomaly detection algorithm could we write on top of such sensor data. Do you have any experience dealing with such data in the past? Couple of ideas which we have
- Show the instances when Sensor value remains abnormally high for a longer time.
- Filter out the spurious values in sensor (which do not fit into a pattern)
- Correlate two sensor values to predict a condition (e.g. high humidity and low temperature indicates rain)
Any other input will be highly appreciated.