Recent progress in smart electronic nose technologies enabled with machine learning methods

Z Ye, Y Liu, Q Li - Sensors, 2021 - mdpi.com
Machine learning methods enable the electronic nose (E-Nose) for precise odor
identification with both qualitative and quantitative analysis. Advanced machine learning …

Overcoming the limits of cross-sensitivity: pattern recognition methods for chemiresistive gas sensor array

H Mei, J Peng, T Wang, T Zhou, H Zhao, T Zhang… - Nano-micro letters, 2024 - Springer
As information acquisition terminals for artificial olfaction, chemiresistive gas sensors are
often troubled by their cross-sensitivity, and reducing their cross-response to ambient gases …

Multi-task deep learning model for quantitative volatile organic compounds analysis by feature fusion of electronic nose sensing

W Ni, T Wang, Y Wu, X Liu, Z Li, R Yang… - Sensors and Actuators B …, 2024 - Elsevier
In exploring pattern recognition for electronic noses via deep neural networks, traditional
networks encounter key challenges, such as low training efficiency, and neglect of spatial …

Review on algorithm design in electronic noses: Challenges, status, and trends

T Liu, L Guo, M Wang, C Su, D Wang, H Dong… - Intelligent …, 2023 - spj.science.org
Electronic noses, or e-noses, refer to systems powered by chemical gas sensors, signal
processing, and machine learning algorithms for realizing artificial olfaction. They play a …

Multi-task convolutional neural network for simultaneous monitoring of lipid and protein oxidative damage in frozen-thawed pork using hyperspectral imaging

J Cheng, J Sun, K Yao, M Xu, C Dai - Meat science, 2023 - Elsevier
Lipid and protein oxidation are the main causes of meat deterioration during freezing.
Traditional methods using hyperspectral imaging (HSI) need to train multiple independent …

Portable electronic nose system with elastic architecture and fault tolerance based on edge computing, ensemble learning, and sensor swarm

T Wang, Y Wu, Y Zhang, W Lv, X Chen, M Zeng… - Sensors and Actuators B …, 2023 - Elsevier
The portable electronic nose (E-nose) systems are suffering from the limited computing
ability of microcontrollers and can only adopt simple pattern recognition algorithms. The …

Geographical traceability of soybean: An electronic nose coupled with an effective deep learning method

H Sun, Z Hua, C Yin, F Li, Y Shi - Food chemistry, 2024 - Elsevier
The quality of soybeans is correlated with their geographical origin. It is a common
phenomenon to replace low-quality soybeans from substandard origins with superior ones …

Selective identification and quantification of VOCs using metal nanoparticles decorated SnO2 hollow-spheres based sensor array and machine learning

S Acharyya, PK Bhowmick, PK Guha - Journal of Alloys and Compounds, 2023 - Elsevier
Accurate and selective detection of target gas/volatile organic compounds (VOCs) is of
utmost importance. The chemiresistive gas sensors have been a desirable candidate due to …

E-nose system based on Fourier series for gases identification and concentration estimation from food spoilage

J Luo, Z Zhu, W Lv, J Wu, J Yang, M Zeng… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
This work presents an electronic nose (EN)-based gas identification and concentration
estimation method for the detection of food spoilage. The response data of sensors were …

Advances in machine‐learning enhanced nanosensors: From cloud artificial intelligence toward future edge computing at chip level

Z Zhang, X Liu, H Zhou, S Xu, C Lee - Small Structures, 2024 - Wiley Online Library
Machine‐learning‐enhanced nanosensors are rapidly emerging as a promising solution in
the field of sensor technology, as traditional sensors encounter limitations of data analysis in …