Development and Application of the Electronic Nearby Odour Sensing Element (e-NOSE)

Abstract

Introduction: The Electronic Nearby Odour Sensing Element (e-NOSE) is an advanced technology designed to detect, identify, and classify odors through a sensor array and artificial intelligence (AI)-driven algorithms. This study presents the development and evaluation of the e-NOSE as a humane alternative to traditional methods, such as sniffer dogs, for detecting hazardous substances like drugs and explosives, while also exploring its applications in food quality control and environmental monitoring.

Methodology: The methodology involved the use of a sensor array, specifically designed to detect volatile organic compounds (VOCs) emitted by various substances. The data collected from the sensors was processed using machine learning algorithms, including Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), to identify and classify odors. The e-NOSE system was tested on drug samples (marijuana and methamphetamine), food samples (freshness and spoilage detection), and environmental pollutants (VOCs).

Results: The results demonstrated that the e-NOSE system successfully identified odors with high accuracy, achieving a sensitivity rate of over 95% in drug detection and distinguishing between fresh and spoiled food samples. The system’s ability to detect and classify odors in real-time makes it a promising alternative to sniffer dogs in hazardous detection tasks, offering benefits in terms of animal welfare, continuous operation, and objective analysis.

Discussion: In the discussion, the e-NOSE’s performance was compared to traditional detection methods, highlighting its advantages in speed, accuracy, and safety. Although the system showed occasional inconsistencies in complex odor mixtures, it outperformed conventional methods in several aspects. The use of AI algorithms was key to improving the system’s classification accuracy, although challenges related to sensor calibration and VOC interference remain.

Conclusion: In conclusion, the e-NOSE is a promising technology with the potential to revolutionize industries such as security, food safety, and environmental monitoring. Future advancements in sensor materials, data analysis techniques, and system miniaturization will enhance the system's capabilities, making it an indispensable tool for odor detection in various fields. The ongoing development of e-NOSE technology offers a more humane, efficient, and reliable approach to hazardous substance detection, with broader applications in society and industry.