Implementation of moving average technique in data mining for signal pre-processing in electronic nose system

• Main Authors: Mohamad Yusof, Umi Kalsom, Che Soh, Azura, Ishak, Asnor Juraiza, Hassan, Mohd Khair, Khamis, Shamsul
• Format: Conference or Workshop Item
• Language: English
• Published: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia 2015
• Online Access: http://psasir.upm.edu.my/id/eprint/77124/1/saes2015-1.pdf; http://psasir.upm.edu.my/id/eprint/77124/

The intervention of electronic nose was capable to reproduced human senses using sensor arrays and pattern recognition systems. The ability to classify distinctive odor pattern for aromatic plants species especially for herbs provides significant impact in the field such as in food industry, medicine, culinary, health care product and pharmaceutical. Pre-processing stage has important role in data mining and to compensate for any sensor drift which typically occurs during data gathering in signal processing. Therefore, the moving average technique was applied for smoothing signal and data reduction in pre-processing stage for development of electronic nose system in this study.