Estimating Gas Concentration using Artificial Neural Network for Electronic Nose

被引:30
作者
Sabilla, Shoffi Izza [1 ]
Sarno, Riyanarto [1 ]
Siswantoro, Joko [2 ]
机构
[1] Inst Teknol Sepuluh Nopember, Dept Informat, Surabaya 60111, Indonesia
[2] Univ Surabaya, Fac Engn, Dept Informat Engn, Jl Kali Rungkut, Surabaya 60293, Indonesia
来源
4TH INFORMATION SYSTEMS INTERNATIONAL CONFERENCE (ISICO 2017) | 2017年 / 124卷
关键词
Artifical Neural Network; Sensor; Electronic Nose; Mangoes Ripeness;
D O I
10.1016/j.procs.2017.12.145
中图分类号
F [经济];
学科分类号
02 ;
摘要
E-nose is a sensor used to detect the existence of gas in the air. Some types of sensor has the ability to detect certain gas and also has different datasheet. Slope deflection is the method to determine the suitable sensor for the experiment. E-nose with MQ Family produces the ratio of existing air and base line air resistance, and it is usually equipped with a datasheet containing the consecration of detected gas in a certain value of the sensor to convert the output to the concentration of detected gas. The ratio is used to estimate the concentration of a gas. In this paper, Artificial neural network is used to estimate the concentration of a gas in the air based on the ratio. Providing the accurate calculation of the ratio is very important to increase the Electronic nose performance, and the result of this experiment showed that the Artificial neural network method achieves a good performance with smaller RMSE of 0.0433 compared with the existing methods. (C) 2018 The Authors. Published by Elsevier B.V.
引用
收藏
页码:181 / 188
页数:8
相关论文
共 14 条
[1]   Electronic-Nose Applications for Fruit Identification, Ripeness and Quality Grading [J].
Baietto, Manuela ;
Wilson, Alphus D. .
SENSORS, 2015, 15 (01) :899-931
[2]  
BARNSTON AG, 1992, WEATHER FORECAST, V7, P699, DOI 10.1175/1520-0434(1992)007<0699:CATCRA>2.0.CO
[3]  
2
[4]   A pilot study of faecal volatile organic compounds in faeces from cholera patients in Bangladesh to determine their utility in disease diagnosis [J].
Garner, C. E. ;
Smith, S. ;
Bardhan, P. K. ;
Ratcliffe, N. M. ;
Probert, C. S. J. .
TRANSACTIONS OF THE ROYAL SOCIETY OF TROPICAL MEDICINE AND HYGIENE, 2009, 103 (11) :1171-1173
[5]  
Hariyanto R., 2017, DETECTION DIABETES G
[6]  
James G., 2013, INTRO STAT LEARNING, V112, DOI [10.1007/978-1-4614-7137-0, DOI 10.1007/978-1-4614-7137-0]
[7]  
Mohamed EI, 2002, DIABETES NUTR METAB, V15, P215
[8]  
Nouri F. G., 2014, 2014 5 INT C FOOD EN
[9]   A practical approach for fish freshness determinations using a portable electronic nose [J].
O'Connell, M ;
Valdora, G ;
Peltzer, G ;
Negri, RM .
SENSORS AND ACTUATORS B-CHEMICAL, 2001, 80 (02) :149-154
[10]  
Seeed Studio, 2017, GROV GAS SENS MQ3