E-Nose design and structures from statistical analysis to application in robotic: a compressive review

Authors

DOI:

https://doi.org/10.4108/airo.v2i1.3056

Keywords:

ENose, pre-processing method, statistical analyse, Machine learning, robotic, odour source localization

Abstract

Since 1982, the olfactory system of creatures has piqued the interest of academics who seek to create a comparable system. Despite its mysterious nature, the first stage has been successfully completed with the development of the E-nose. Its extended applications have opened new doors for researchers, ranging from food quality testing to bomb detection and even, more recently, identifying those infected with the coronavirus. In this talk, we will review the structure and sensor behavior of the E-nose, as well as its applications, such as odour source localization and various applications in agriculture. The challenge of odour identification has prompted researchers to employ robots with sensors to investigate and locate odour sources. The present study aims to synthesize documented research and provide a fresh perspective on odour localization research efforts and tests conducted. The study highlights previous attempts to equip robots with sensors to explore the real indoor or outdoor environment. Initially, a review was conducted to investigate various aspects of the sector and the obstacles involved.

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Published

20-04-2023

How to Cite

[1]
A. J. Moshayedi, “E-Nose design and structures from statistical analysis to application in robotic: a compressive review”, EAI Endorsed Trans AI Robotics, vol. 2, Apr. 2023.

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