BIRLA INSTITUTE OF TECHNOLOGY

Electronic Nose and Electronic Tongue Presented by:

MT/CS/3553/10 Akash DuttaSupervisors :1. Prof. S. Chaudhuri-Internal Professor , Computer Science Department ,BIT Mesra Kolkata Campus

2. Prof. Rajib Bandyopadhyay -External Professor , Instrumentation and Electronics Engineering Department , Jadavpur University

Project Objective

• Development of an Electronic Nose instrument with commercially available sensors.

• Experimentation with several food and various products for use in quality evaluation.

Nose and Tongue

• Nose – Vapor • Tongue – Solid and Liquid• Poisonous Material• Electronic Nose • Electronic Tongue

Human Smell System

Human Smell System Cont.

Electronic Nose

• Electronic Nose is a machine designed to detect complex odors using sensor arrays.

• The sensor array consists of broadly tuned (non-specific) sensors that are treated with a variety of odor-sensitive biological or chemical materials.

Block Diagram Electronic NoseOdour Delivery SystemOdour Delivery System

Sensor Array ChamberSensor Array Chamber

Signal ConditioningSignal Conditioning

Data AcquisitionData AcquisitionSignal ProcessingSignal Processing

Pattern Recognition

•Responsible for Color•Responsible for Taste•Responsible for Flavor

BIOCHEMICAL COMPOUNDS IN TEA

Sensor Selection for Black Tea

•The sensing element for such sensors(MOS) is tin dioxide (SnO2), which has low conductivity in clean air.

Measuring Circuit with Figaro sensors

Vc

V H

GND

V RL

R L

Data from MOS Sensor

• Table IV(Next slide) lists ∆RS/RS values of the sensors, where ∆RS is the change in resistance of the MOS sensor, and RS is the base resistance value of the respective MOS sensor.

MOS Sensor

Clean Air

Biochemical compounds

∆RS/RS

The final sensor(tin oxide Figaro make) set comprises five sensors—TGS-832, TGS-823, TGS-2600, TGS-2610, and TGS-2611—in the electronic nose setup.

Electronic Nose Setup for Tea Aroma Sensing

The Prototype Instrument

Sample Holder

Screenshot of electronic nose

Component of Electronic Nose

• Pump• 3 Valve• Sensors• Computer Add-on Card• Pattern Recognition Software

The experimental conditions

• amount of each sample = 50 g;• temperature = 60 .C ± 3 .C;• headspace generation time = 30 s;• collection time = 100 s;• purging time = 100 s;• air-flow rate = 5 mL/s.

DATA ANALYSIS

Neural Network•BP-MLP Model• RBF Network • PNN

Neural Network Architecture

Example Calculation

Papers …………..• Nabarun Bhattacharyya, Rajib Bandyopadhyay, Manabendra Bhuyan, Bipan Tudu, Devdulal

Ghosh, and Arun Jana “Electronic Nose for Black Tea Classification and Correlation of Measurements with “Tea Taster” Marks” IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 57, NO. 7, JULY 2008 PP 1313-1321

• Nabarun Bhattacharya (a), Bipan Tudu (b), Arun Jana (a), Devdulal Ghosha, Rajib Bandhopadhyaya (b), Manabendra Bhuyan(c) “Preemptive identification of optimum fermentation time for

black tea using electronic nose” Sensors and Actuators B 131 (2008) 110–116 a. Centre for Development of Advance Computing (C-DAC), Kolkata 700091, India b. Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India c. Tezpur University, Assam, India

• Bipan Tudu, Animesh Metla, Barun Das, Nabarun Bhattacharyya, Arun Jana, Devdulal Ghosh, and Rajib Bandyopadhyay “Towards Versatile Electronic Nose Pattern Classifier for Black Tea Quality Evaluation: An Incremental Fuzzy Approach. “IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 58, NO. 9, SEPTEMBER 2009 PP 3069 -3078

• Mousumi Palit, Bipan Tudu, Pallab Kumar Dutta, Ankur Dutta, Arun Jana, Jayanta Kumar Roy, Nabarun Bhattacharyya, Member, IEEE, Rajib Bandyopadhyay, and Anutosh Chatterjee “ Classification of Black Tea Taste and Correlation with Tea Taster’s Mark Using Volta metric Electronic Tongue.“IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 59, NO. 8, AUGUST 2010 PP 2230 - 2239

• Anil Kumar Bag, Bipan Tudu, Jayashri Roy, Nabarun Bhattacharyya, and Rajib Bandyopadhyay ” Optimization of Sensor Array in Electronic Nose: A Rough Set-Based Approach– “IEEE SENSORS

JOURNAL, VOL. 11, NO. 11, NOVEMBER 2011 PP 3001 - 3008

BOOKS………• Neural Networks, Fuzzy Logic , and Genetic Algorithms Synthesis and Applications

S. Rajasekaran , G.A. Vijayalakshmi Pai—PHI Learning pvt. Ltd. –10th print Oct,2008

• Neural Networks A Comprehensive Foundation

SIMON HAYKIN ---Pearson, 2nd Edition

• INTEGRATED ELECTRONICS Analog and Digital Circuits and Systems

Jacob Millman , Christos C. Halkias -- Tata Mc Graw Hill – Edition 1991 , 17th reprint 2000

• Electronic Devices and Circuit Theory 10th Edition PEARSON Robert L. Boylestad , Louis Nashelsky—3rd Impression 2011

• Biomedical Instrumentation and Measurements – Second Edition Leslie Cromwell , Fred J. Weibell , Erich A. Preiffer – Pearson Prentice Hall 2008• Bio-Medical Electronics & Instrumentation – Prof. S. K. Venkata Ram Revised Edition – Galgotia Publication pvt. Ltd. , 2nd Edition 2003 , Reprint 2007• Higher Engineering Mathematics – Dr. B.S. Grewal Khanna Publishers , 35th Edition, 1st reprint sept 2000

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