Deep Neural Network Regression‐Assisted Pressure Sensor for Decoupling Thermal Variations at Different Operating Temperatures
Joohyung Bang, Keuntae Baek, Jaeyoung Lim, Yong‐Ha Han, Hongyun So
Abstract
Pressure Sensors The efficient measurement of pressure using a sensor under various environmental conditions, such as temperature and humidity, remains challenging due to electrical distortions. In article number 2300186, Joohyung Bang, Keuntae Baek, Jaeyoung Lim, Yongha Han, and Hongyun So present a system-on-chip decoupling system using a sponge-based pressure sensor. The proposed novel decoupling system could separate thermal effects from the pressure sensor using a deep neural network-based regression model, and thus, enhance the reliability of the pressure sensor under variable temperature environments.
Topics & Concepts
Decoupling (probability)Pressure sensorArtificial neural networkReliability (semiconductor)HumidityThermalComputer scienceEngineeringArtificial intelligenceControl engineeringMechanical engineeringMeteorologyPhysicsPower (physics)Quantum mechanicsSensor Technology and Measurement Systems