All kinds of innovation are possible with inspiration. As image processing is inspired by the sense of sight, the electronic nose (abbreviation EN, enose, e-nose)-also known as an odor sensor, aroma sensor, mechanical nose, flavor sensor, multi-sensor array, artificial nose, odorsensing system, electronic olfactometry - technology is inspired by the sense of smell. The olfactory system easily enables living beings to be aware of their environment, of possible dangers, and to identify and classify food. In technology though, automatic identification and classification of odor is a very challenging issue because the scents in chemical mixtures intercommunicate naturally.
This natural interaction has three types: synergism, compensation and masking. Synergism is defined as the interaction when two or more distinct substances produce a mutual scent which is stronger than those of individual components. Compensation is the case when one component counteracts another constituent. Masking is the combination of one pleasant odor with an unpleasant one. Even though there exist reported achievements of some earlier techniques, such chemical mixtures in general conditions were not able to be analyzed and split up into its components with high accuracy until the development of the EN technology. Together with the development of EN devices, several studies were completed to assess odor intensities, to understand mixtures of odor interactions and the sensor responses to these interactions.
Although the first research on detecting distinctive smells began during the 1920s, the idea to detect aromas with a chemical electronic sensor array was primarily mentioned in the early 1980s. However, the EN concept could not be actualized at that time due to limitations in the sensors technology.
In the late 1990s then, the term “electronic nose” was mentioned According to its initial definition, an EN is composed of a multisensor array responsible for detecting more than one chemical component. Subsequently, both technological improvements in sensors and the realization of the potential that the EN holds led to a considerable extension of its applications. Recently, due to the provision of reliable solutions, rapidity, low cost and compactness, the EN concept has become popular in agriculture, the food and water industry, medicine, security systems and many other areas.
Fig. 1 demonstrates the similarities between the biological olfactory system and the EN technology. The electronic sensor array of the EN corresponds to the olfactory nose receptors, which detects the traces of chemicals in the air. When these molecules are sensed and captured, the input signal is sent to the olfactory bulb, where the odor information is processed. After characterizing the aroma, the smell is recognized in the brain by the olfactory cortex as a last stage in the biological system. Likewise, in the EN case, a preprocessor applies feature extraction to the captured odor signal. Afterwards, data analysis, pattern recognition and machine learning related algorithms are generally used for identifying and classifying the input scent using the extracted digital signatures.
After drawing the parallels between the biological olfactory system and the EN technology, an EN obviously consists of both hardware and software components. While the software part can be thought as the “brain”, the hardware part can be seen as the “olfactory receptors” of the EN system. The software part mainly contains a data processing unit which identifies and classifies each individual scent detected using digital signatures of the sensed chemicals. The hardware part is basically a sensor array.
Since the main objective of the EN is detecting and classifying multiple aromas, the sensing array should encompass different types of individual sensors, where each sensor is responsible for detecting a different chemical. The selection of suitable sensors to a given specific task is a key point in this technology. It can be concluded here that choosing the suitable hardware and efficient software components is very important in designing and implementing a successful EN system for a particular problem.
Hence, the main aim of this survey is to provide a complete overview of the EN technology while pointing out the task-dependent importance of its hardware and software components and their characteristic properties. Note that there are several existing reviews in the literature which focus on a specific sub-topic of the EN concept, e.g., the range of sensors as hardware components used in the EN systems, ENs for the food industry, neural networks as software components for ENs On the other hand, this paper rather provides a comprehensive review of broad EN application fields, a wide range of software related algorithms and commonly utilized sensor types and their properties as practical hardware components.
The remaining part of this survey is structured as follows. The EN device and its main components are introduced in Section 2. Then, a wide range of practical EN applications and related topics are described in Section 3. Afterwards, current challenges for this technology are discussed in Section 4, followed by perspectives and possible future research directions in Section 5. This paper is finally concluded with a brief conclusion in Section 6.
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Electronic Nose and Its Applications: A Survey
Diclehan Karakaya, Oguzhan Ulucan, Mehmet Turkan
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