DIGITAL REPRESENTATION TECHNIQUES FOR OLFACTORY FEATURES

Abstract

Digital representation of odor has a basic principal of chemosensory organism of sensory molecules. A body organism responds to external odor environments. A body of animal/human perceives the odor in the form of molecule structure. But the questions still arises how that odor molecule is presented in the digital format. Also how it act a specific odor behavior. The mechanism used in animal/human body is to solve the problem as per thought process level. Thought process retrieve the stored molecule of odor in a visual smell. Similar concepts are carrying forward to store in a computer system with the help of electron. The system is applied to perform Machine-learned odor recognition from physico-chemical properties of volatile molecules. The properties of volatile molecules are to match the pattern of chemosensory organisms. Artificial intelligence is used to predict the molecule of smell by applying neural network. This paper focuses on the behavior of odors and its digital representation techniques for olfactory features.