Design and Construction of Electronic Nose for Multi-purpose Applications by Sensor Array Arrangement Using IBGSA

• Published in: Journal of intelligent & robotic systems Vol. 92; no. 2; pp. 205 - 221
• Main Authors: Estakhroyeh, Hossein Rezaei, Rashedi, Esmat, Mehran, Mahdiyeh
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.10.2018; Springer; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Bread; Case studies; Control; Electrical Engineering; Electronic noses; Engineering; Gas fields; Gas sensors; Gravitation; Hardware; Mechanical Engineering; Mechatronics; Natural gas; Nose; Odors; Pattern recognition; Petroleum products; Power consumption; Robotics; Search algorithms; Sensor arrays; Sensors; Smell; Technology application; Multi-purpose applications; Odor classification; Electronic nose (E-nose); Sensor array configuration; Gas sensors array; Binary gravitational search algorithm
• ISSN: 0921-0296; 1573-0409
• DOI: 10.1007/s10846-017-0759-3

Technological progresses in the gas sensor fields provide the possibility of designing and construction of Electronic nose (E-nose) based on the Biological nose. E-nose uses specific hardware and software units; Sensor array is one of the critical units in the E-nose and its types of sensors are determined based on the application. So far, many achievements have been reported for using the E-nose in different fields of application. In this work, an E-nose for handling multi-purpose applications is proposed, and the employed hardware and pattern recognition techniques are depicted. To achieve higher recognition rate and lower power consumption, the improved binary gravitational search algorithm (IBGSA) and the K-nearest neighbor (KNN) classifier are used for automatic selecting the best combination of the sensors. The designed E-nose is tested by classifying the odors in different case studies, including moldy bread recognition in food and beverage field, herbs recognition in the medical field, and petroleum products recognition in the industrial field. Experimental results confirm the efficiency of the proposed method for E-nose realization.