A battery-free, wireless, flexible bandlike e-nose based on MEMS gas sensors for precisely volatile organic compounds detection

Abstract

Real-time detection of VOCs in the car cabin is crucial for protecting driver’s health. MOS gas sensors, with the advantages of low cost, simplicity and fast response, are widely used for gas monitoring. However, they typically exhibit broad-spectrum responsiveness to multiple gases. Despite numerous improvement strategies proposed from the perspective of MOS material modification, achieving ideal gas selectivity remains challenging. An e-nose based on gas sensor array is a promising approach for gas identification. However, the hardware circuit system and battery supply module in traditional e-nose result in large size, complex structure, and inconvenience in use. In this work, we synthesized MOS materials with different morphologies to form a microarray containing six MEMS gas sensors, and developed a novel belt-shaped wireless and battery-free flexible e-nose, where a mobile phone serves as its wireless power supply and data communication system. This design provides a flexible e-nose with excellent wearability and safety, allowing users to monitor surrounding gas conditions at any time conveniently. Subsequently, we design pattern recognition models using algorithms such as MLP, RF, XGBoost, and LGBM, in combination with ensemble learning strategies, achieving high accuracy in VOCs classification and low-error concentration prediction. This flexible e-nose holds significant application value for gas detection in car cabins and indoor environments.