Welcome to the InfoSci Platform
Reference Hub1
A Framework for an Artificial-Neural-Network-Based Electronic Nose

A Framework for an Artificial-Neural-Network-Based Electronic Nose

Mudassir Ismail, Ahmed Abdul Majeed, Yousif Abdullatif Albastaki
Copyright: © 2018 |Pages: 24
ISBN13: 9781522538622|ISBN10: 1522538623|EISBN13: 9781522538639
DOI: 10.4018/978-1-5225-3862-2.ch001
Cite Chapter Cite Chapter

MLA

Ismail, Mudassir, et al. "A Framework for an Artificial-Neural-Network-Based Electronic Nose." Electronic Nose Technologies and Advances in Machine Olfaction, edited by Yousif Abdullatif Albastaki and Fatema Albalooshi, IGI Global, 2018, pp. 1-24. https://doi.org/10.4018/978-1-5225-3862-2.ch001

APA

Ismail, M., Majeed, A. A., & Albastaki, Y. A. (2018). A Framework for an Artificial-Neural-Network-Based Electronic Nose. In Y. Albastaki & F. Albalooshi (Eds.), Electronic Nose Technologies and Advances in Machine Olfaction (pp. 1-24). IGI Global. https://doi.org/10.4018/978-1-5225-3862-2.ch001

Chicago

Ismail, Mudassir, Ahmed Abdul Majeed, and Yousif Abdullatif Albastaki. "A Framework for an Artificial-Neural-Network-Based Electronic Nose." In Electronic Nose Technologies and Advances in Machine Olfaction, edited by Yousif Abdullatif Albastaki and Fatema Albalooshi, 1-24. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-3862-2.ch001

Export Reference

Mendeley
Favorite

Abstract

Machine odor detection has developed into an important aspect of our lives with various applications of it. From detecting food spoilage to diagnosis of diseases, it has been developed and tested in various fields and industries for specific purposes. This project, artificial-neural-network-based electronic nose (ANNeNose), is a machine-learning-based e-nose system that has been developed for detection of various types of odors for a general purpose. The system can be trained on any odor using various e-nose sensor types. It uses artificial neural network as its machine learning algorithm along with an OMX-GR semiconductor gas sensor for collecting odor data. The system was trained and tested with five different types of odors collected through a standard data collection method and then purified, which in turn had a result varying from 93% to 100% accuracy.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.