A Study on the Effect of Drift Factor on Feature Optimization in Electronic Nose Detection DOI Creative Commons

Minhao Cai,

Sai Xu,

Xingxing Zhou

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11366 - 11366

Published: Dec. 5, 2024

As an important instrument for olfactory detection in non-destructive testing (NDT), the electronic nose plays role simulating detection. However, its performance is often affected by drift phenomena, including changes sensor caused environmental factors and fatigue due to long-term use. Although effect of on noses widely recognized, there still a relative lack research how affects feature optimization. This study presents novel idea that not only affect direct readings but may also have profound optimization process hence compensation nose. To explore this concept, we chose temperature humidity, two most common factors, our experimental study. In study, verified impact found positive correlation between concentration scores correct classification rate. Moreover, adopted innovative quadratic method, which aims reduce influence factor thus improve resistance experiments, unweighted method performs best reducing effect. After process, recognition rate reaches 100% training set 96% test set, indicates has improved significantly terms resistance. summary, explores proposes effective treatment provides reference direction development technology.

Language: Английский

Multi-scenario Adaptive Electronic Nose for the Detection of Environmental Odor Pollutants DOI
Chen Qu, Zhuoran Zhang, Jinhua Liu

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 489, P. 137660 - 137660

Published: Feb. 18, 2025

Language: Английский

Citations

0
Nanomaterial Innovations and Machine Learning in Gas Sensing Technologies for Real-Time Health Diagnostics DOI

Md. Harun-Or-Rashid,

Sahar Mirzaei, Noushin Nasiri

et al.

ACS Sensors, Journal Year: 2025, Volume and Issue: unknown

Published: March 10, 2025

Breath sensors represent a frontier in noninvasive diagnostics, leveraging the detection of volatile organic compounds (VOCs) exhaled breath for real-time health monitoring. This review highlights recent advancements breath-sensing technologies, with focus on innovative materials driving their enhanced sensitivity and selectivity. Polymers, carbon-based like graphene carbon nanotubes, metal oxides such as ZnO SnO2 have demonstrated significant potential detecting biomarkers related to diseases including diabetes, liver/kidney dysfunction, asthma, gut health. The structural operational principles these are examined, revealing how unique properties contribute key respiratory gases acetone, ammonia (NH3), hydrogen sulfide, nitric oxide. complexity samples is addressed through integration machine learning (ML) algorithms, convolutional neural networks (CNNs) support vector machines (SVMs), which optimize data interpretation diagnostic accuracy. In addition sensing VOCs, devices capable monitoring parameters airflow, temperature, humidity, essential comprehensive analysis. also explores expanding role artificial intelligence (AI) transforming wearable into sophisticated tools personalized enabling disease Together, advances sensor ML-based analytics present promising platform future individualized, healthcare.

Language: Английский

Citations

0
Smart VOCs Recognition System Based on Single Gas Sensor and Multi-task Deep Learning Model DOI
Haixia Mei, Jingyi Peng, Tao Wang

et al.

Sensors and Actuators B Chemical, Journal Year: 2025, Volume and Issue: unknown, P. 137853 - 137853

Published: April 1, 2025

Language: Английский

Citations

0
Advances in Gas Detection of Pattern Recognition Algorithms for Chemiresistive Gas Sensor DOI Open Access
Guanghui Zhou,

Bingsheng Du,

Jie Zhong

et al.

Materials, Journal Year: 2024, Volume and Issue: 17(21), P. 5190 - 5190

Published: Oct. 24, 2024

Gas detection and monitoring are critical to protect human health safeguard the environment ecosystems. Chemiresistive sensors widely used in gas due their ease of fabrication, high customizability, mechanical flexibility, fast response time. However, with rapid development industrialization technology, main challenges faced by chemiresistive poor selectivity insufficient anti-interference stability complex application environments. In order overcome these shortcomings sensors, pattern recognition method is emerging having a great impact field sensing. this review, we focus systematically on advancements data processing methods for feature extraction, such as determining characteristics original curve, curve fitting parameters, transform domain. Additionally, emphasized developments traditional algorithms neural network algorithm discrimination analyzed advantages through an extensive literature review. Lastly, summarized research provided prospects future development.

Language: Английский

Citations

1
A Study on the Effect of Drift Factor on Feature Optimization in Electronic Nose Detection DOI Creative Commons

Minhao Cai,

Sai Xu,

Xingxing Zhou

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11366 - 11366

Published: Dec. 5, 2024

As an important instrument for olfactory detection in non-destructive testing (NDT), the electronic nose plays role simulating detection. However, its performance is often affected by drift phenomena, including changes sensor caused environmental factors and fatigue due to long-term use. Although effect of on noses widely recognized, there still a relative lack research how affects feature optimization. This study presents novel idea that not only affect direct readings but may also have profound optimization process hence compensation nose. To explore this concept, we chose temperature humidity, two most common factors, our experimental study. In study, verified impact found positive correlation between concentration scores correct classification rate. Moreover, adopted innovative quadratic method, which aims reduce influence factor thus improve resistance experiments, unweighted method performs best reducing effect. After process, recognition rate reaches 100% training set 96% test set, indicates has improved significantly terms resistance. summary, explores proposes effective treatment provides reference direction development technology.

Language: Английский

Citations

0