Understanding the Concepts of Smart E‐Nose Technology in Combination With Machine Learning for New Era of Food Safety: An Advanced Review

ABSTRACT Electronic‐nose (E‐Nose) technology delivers fast and precise detection of volatile substances by utilizing sophisticated data processing techniques such as principal component analysis (PCA) and artificial neural networks (ANN). This makes E‐Nose technology a useful substitute for conventional sensory evaluation methods. E‐Nose systems are now even more capable because of the incorporation of artificial intelligence, which allows for complex pattern recognition and odor classification. Ongoing developments in sensor technology and data processing algorithms are anticipated to cement the position of E‐Nose systems as crucial instruments in guaranteeing food safety, environmental health, and precise medical diagnostics, notwithstanding obstacles associated with sensor stability and environmental sensitivity. This technology's future depends on ongoing innovation and improvement in analytical techniques as well as sensor designs. E‐Nose technology has shown great potential in some fields, including medical diagnostics, environmental monitoring, and food quality evaluation. This is especially true when combined with machine learning. The development of E‐Nose systems from large power‐hungry equipment to small, lightweight, and effective gadgets is examined in this research study.