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ABSTRACT

Electronic/artificial noses are being developed as systems for the automated detection and

classification of odors, vapors, and gases. An electronic nose is generally composed of a

chemical sensing system (e.g., sensor array or spectrometer) and a pattern recognition system

(e.g., artificial neural network). The Electronic Nose (E Nose) is an array of 32 polymer film

conductometric sensors; the pattern of response may be deconvoluted to identify contaminants in

the environment. An engineering test model of the E Nose was used to monitor the air of the

Early Human Test experiment at Johnson Space Center. These are developing for the automated

identification of volatile chemicals for environmental and medical applications. In this

paper, we briefly describe an electronic nose, show some results from a prototype electronic

nose, and discuss applications of electronic noses in the environmental, medical, and food

industries.

INTRODUCTION

The two main components of an electronic nose are the sensing system and the automated

pattern recognition system. The sensing system can be an array of several different sensing

elements (e.g., chemical sensors), where each element measures a different property of the

sensed chemical, or it can be a single sensing device (e.g., spectrometer) that produces an array

of measurements for each chemical, or it can be a combination. Each chemical vapor presented

to the sensor array produces a signature or pattern characteristic of the vapor. By presenting

many different chemicals to the sensor array, a database of signatures is built up. This database

of labeled signatures is used to train the pattern recognition system. The goal of this training

process is to configure the recognition system to produce unique classifications of each chemical

so that an automated identification can be implemented. The quantity and

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complexity of the data collected by sensors array can make conventional chemical analysis of

data in an automated fashion is difficult. One approach to chemical vapor identification is to

build an array of sensors, where eachsensor in

the array is designed to respond to a specific

chemical. With this approach, the number of

unique sensors must be at least as great as the

number of chemicals being monitored. It is both

expensive and difficult to build highly selective

chemical sensors.

Artificial neural networks

(ANNs), which have been used to analyze

complex data and to recognize patterns, are

showing promising results in chemical vapor

recognition. When an ANN is combined with a

sensor array, the number of detectable chemicals

is generally greater than the number of sensors.

Also, less selective sensors which are generally

less expensive can be used with this approach.

Once the ANN is trained for chemical vapor

recognition, operation consists of propagating

the sensor data through the network. Since this is

simply a series of vector-matrix multiplications,

unknown chemicals can be rapidly identified in

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the field.

An electronic nose (e-nose) is a device that identifies the specific components of an odor and

analyzes its chemical makeup to identify it. An electronic nose consists of a mechanism for

chemical detection, such as an array of electronic sensors, and a mechanism for pattern

recognition, such as aneural network. Electronic noses have been around for several years but

have typically been large and expensive. Current research is focused on making the devices

smaller, less expensive, and more sensitive. The smallest version, a nose-on-a-chip is a single

computer chip containing both the sensors and the processing components.

An odor is composed of molecules, each of which has a specific size and shape. Each of these

molecules has a correspondingly sized and shaped receptor in the human nose. When a specific

receptor receives a molecule, it sends a signal to the brain and the brain identifies the smell

associated with that particular molecule. Electronic noses based on the biological model work

in a similar manner, albeit substituting sensors for the receptors, and transmitting the signal to

a program for processing, rather than to the brain. Electronic noses are one example of a

growing research area calledbiomimetics, or biomimicry, which involves human-made

applications patterned on natural phenomena.

Electronic noses were originally used for quality control applications in the food, beverage andcosmetics industries. Current applications include detection of odors specific to diseases for

medical diagnosis, and detection of pollutants and gas leaks for environmental protection.

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