SENSOR TUNING - SENSOR SPECIFIC SELECTION FOR IoT-ELECTRONIC NOSE APPLICATION USING GRADIENT BOOSTING DECISION TREES

A system comprising:

• a sensor array, and
• a processor with at least one algorithm stored therein,
• wherein,
• raw data obtained from the sensor array are input into the processor to form an input set of extracted features, wherein each extracted feature is given an importance value,
• the at least one algorithm ranks the extracted features from the input set, and
• a threshold value comprising an aggregate value of the extracted features is established, wherein individual sensors of the sensor array having extracted features ranked on or above the threshold value are suitable for a target application.

A system comprising:

• a sensor array;
• and
• a processor with at least one algorithm stored therein,
• wherein,
• raw data obtained from the sensor array are input into the processor to form an input set of extracted features,
• the at least one algorithm ranks extracted features from the input set, wherein each extracted feature is given an importance value,
• a threshold value comprising an aggregate value of the extracted features is established, and
• an importance score for each sensor of the sensor array is determined based upon the ranking of the extracted features for each sensor.

A method comprising the steps of:

• extracting features from an input set obtained from a sensor array;
• ranking the extracted features with at least one algorithm, wherein each extracted feature is given an importance value;
• calculating a threshold value for the ranked extracted features;
• calculating an importance score for individual sensors of the sensor array based upon the ranking of the extracted features;
• and
• selecting the individual sensors of the sensor array having an importance score on or above the threshold value for a target application.

A method comprising the steps of:

• preparing a sensor array for a target application and applying information to the sensor array to form an input set;
• extracting features from the input set and ranking the extracted features, wherein each extracted feature is given an importance value;
• calculating a threshold value for the extracted features;
• calculating an importance score for individual sensors of the sensor array based upon the ranking of the extracted features;
• and
• selecting the individual sensors for the target application that have an importance score above the threshold value.