Sensor tuning—sensor specific selection for IoT—electronic nose application using gradient boosting decision trees

US11619618B2 · kind B2 · utility

Assignee

• International Business Machines Corporation · US

Inventors

• Mohammed Abdi · San Jose, US
• Aminat Adebiyi · San Jose, US
• Alberto Mannari · San Jose, US
• Andrea Fasoli · San Jose, US
• Ronald R. Labby · San Jose, US
• Luisa D. Bozano · Los Gatos, US
• Pawan R. Chowdhary · San Jose, US
• Abubeker Abdullahi · Central, US

Key dates

• Filing date: Dec 9, 2019
• Grant date: Apr 4, 2023
• Expiry date: Sep 20, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06F2218/08
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

Provided is a system and method for tuning an array of sensors to enable selection of the most suitable sensors for a target application. After extracting features from sensor raw data, the extracted features are ranked with gradient boosting decision trees to assign an importance value to each extracted feature. A threshold value for the entire set of extracted features is calculated and an importance score is calculated for the individual sensors of the array. Individual sensors with an importance score on or above the threshold value are selected for the target application.