Algorithms key numbers
Prediction process example
Simple data model design
Model creation using previous data or similar sensors models already existing .
Next data prediction
We use our computed model to predict the next data message.
Compute average difference
We compute the average difference that this sensor is used to send (e. g: + or - 2°C)
At this step we liken received data with the computed one reflecting the data average.
If the previous step show an inconsistent data, an alert is thrown.
Popular algorithms used
A light weight computing resources way to find out if a received data is consistent regarding an cluster of data.
Feedforward Neural Network
These heavies algorithms are slow, need to be trained and a lot of computing resources but could discover quality of data and data schema with a great efficiency.
K-Means clustering are used to compare data segment instead of isolate data to look for global sensors behaviours.