Machine olfaction

Key takeaways

Machine olfaction belongs to engineering; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Machine olfaction to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Machine olfaction from memory before moving on to harder problems.

Reference excerpt

Machine olfaction is the automated simulation of the sense of smell. An emerging application in modern engineering, it involves the use of robots or other automated systems to analyze air-borne chemicals. Such an apparatus is often called an electronic nose or e-nose. The development of machine olfaction is complicated by the fact that e-nose devices to date have responded to a limited number of chemicals, whereas odors are produced by unique sets of (potentially numerous) odorant compounds. The technology, though still in the early stages of development, promises many applications, such as: quality control in food processing, detection and diagnosis in medicine, detection of drugs, explosives and other dangerous or illegal substances, disaster response, and environmental monitoring. One type of proposed machine olfaction technology is via gas sensor array instruments capable of detecting, identifying, and measuring volatile compounds. However, a critical element in the development of these instruments is pattern analysis, and the successful design of a pattern analysis system for machine olfaction requires a careful consideration of the various issues involved in processing multivariate data: signal-preprocessing, feature extraction, feature selection, classification, regression, clustering, and validation. Another challenge in current research on machine olfaction is the need to predict or estimate the sensor response to aroma mixtures. Some pattern recognition problems in machine olfaction such as odor classification and odor localization can be solved by using time series kernel methods.

Detection

There are three basic detection techniques using conductive-polymer odor sensors (polypyrrole), tin-oxide gas sensors, and quartz-crystal micro-balance sensors. They generally comprise (1) an array of sensors of some type, (2) the electronics to interrogate those sensors and produce digital signals, and (3) data processing and user interface software. The entire system is a means of converting complex sensor responses into a qualitative profile of the volatile (or complex mixture of chemical volatiles) that make up a smell, in the form of an output. Conventional electronic noses are not analytical instruments in the classical sense and very few claim to be able to quantify an odor. These instruments are first 'trained' with the target odor and then used to 'recognize' smells so that future samples can be identified as 'good' or 'bad'. Research into alternative pattern recognition methods for chemical sensor arrays has proposed solutions to differentiate between artificial and biological olfaction related to dimensionality. This biologically-inspired approach involves creating unique algorithms for information processing. Electronic noses are able to discriminate between odors and volatiles from a wide range of sources and quality. The list below shows just some of the typical applications for electronic nose technology – many are backed by research studies and published technical papers.

Odor localization

Odor localization is a combination of quantitative chemical odor analysis and path-searching algorithms, and environmental conditions play a vital role in localization quality. Different methods are being researched for various purposes and in different real-world conditions.

Motivation Odor localization is the technique and process of locating a volatile chemical source in an environment containing one or several odors. It is vitally important for all living beings for both finding sustenance and avoiding danger. Unlike the other basic human senses, the sense of smell is entirely chemical-based. However, in comparison with the other dimensions of perception, detection of odor faces additional problems due to the complex dynamic equations of odor and unpredictable external disturbances such as wind.

Application Odor localization technology shows promise in many applications, including:

quality control in food processing (e.g. taints, bacterial spoilage) locating the source of dangerous substances (e.g.: explosives and chemical warfare agents) discovering underground resources or hazards detecting prohibited materials (e.g.: drug detection) searching for survivors of natural disasters environmental monitoring for pollutants early diagnosis of diseases (e.g. in chronic obstructive pulmonary disease)

History and problem statement The earliest instrument for specific odor detection was a mechanical nose developed in 1961 by Robert Wighton Moncrieff. The first electronic nose was created by W. F. Wilkens and J. D. Hartman in 1964. Larcome and Halsall discussed the use of robots for odor sensing in the nuclear industry in the early 1980s, and research on odor localization was started in the early 1990s. Odor localization is now a fast-growing field. Various sensors have been developed and a variety of algorithms have been proposed for diverse environments and conditions. Mechanical odor localization can be executed via the following three steps, (1) search for the presence of a volatile chemical (2) search for the position of the source with an array of odor sensors and certain algorithms, and (3) identify the tracked odor source (odor recognition).

Localization methods Odor localization methods are often classified according to odor dispersal modes in a range of environmental conditions. These modes can generally be divided into two categories: diffusion-dominated fluid flow and turbulence-dominated fluid flow. These have different algorithms for odor localization, discussed below.

Diffusion-dominated fluid flow Tracking and localization methods for diffusion-dominated fluid flow – which is mostly used in underground odor localization – must be designed so that olfaction machinery can operate in environments in which fluid motion is dominated by viscosity. This means that diffusion leads to the dispersal of odor flow, and the concentration of odor decreases from the source as a Gaussian distribution. The diffusion of chemical vapor through soil without external pressure gradient is often modeled by Fick's second law:

… excerpt ends here. Continue reading the full article.

Illustrations

Worked examples

Example 1 — a first encounter with Machine olfaction

Start with the simplest possible case. Write down what Machine olfaction claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Machine olfaction before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Machine olfaction ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Machine olfaction

In research: Machine olfaction appears in engineering research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Machine olfaction in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Machine olfaction is common in secondary-school and first-year university syllabi. It links to neighbouring topics Olfaction, Robotic sensing, so understanding it makes those chapters shorter.
In everyday life: Look for Machine olfaction outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

How to study Machine olfaction in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Machine olfaction means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Machine olfaction out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Machine olfaction in simple terms?

Machine olfaction is the automated simulation of the sense of smell. An emerging application in modern engineering, it involves the use of robots or other automated systems to analyze air-borne chemicals.

Why does Machine olfaction matter?

Because it connects several engineering ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Machine olfaction?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Machine olfaction.