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Olfaction plays a very important role in daily life. The olfactory system has the ability to recognize, discriminate and identify thousands of odorant compounds with extremely high sensitivity and specificity. The research on olfactory system has very important values in exploring the mechanisms of information processing in the other sensory nervous systems and brain. Recently, with the development of molecular biological and microelectronics technology research, the study of olfactory cell-based sensors has made great progress. The purpose of this paper is to provide details of recent developments in olfactory cell-based sensors.

Following an introduction, this paper first discusses some olfactory cell-based biosensors, which focus on the light-addressable potentiometric sensors and the microelectrode arrays. Second, surface modification, microfabrication and microfluidic technology which can improve the efficiency of cell immobilization will be summarized. The research trends of olfactory cell-based sensor in future will be proposed.

This paper shows that the biosensors’ performance is expected to be greatly improved due to the fast development of nanotechnology, optical technology and microelectronics. More and more emerging intelligent olfactory sensors will have a promising prospect in many application fields, including food quality and safety assessment, environmental monitor and human diseases detection.

This paper provides a detailed and timely review of the rapidly growing research in the olfactory cell-based sensors.

The purpose of this paper is to present a mobile robot with an olfactory capability for hazardous site survey. Possible applications include detection of gas leaks and dangerous substances along predefined paths, inspection of pipes in factories, and mine sweeping.

The mobile sentry is equipped with a transducer array of tin oxide chemical sensors, compliant with the standard interface IEEE 1451, which provides odour‐sensing capability, and uses differential drive and spring‐suspended odometric trackballs to move and localize in the environment. The monitoring strategy comprises two stages. First, a path learning operation is performed where the vehicle is remotely controlled through some potential critical locations of the environment, such as valves, pressure vessels, and pipelines. Then, the robot automatically tracks the prerecorded trajectory, while serving as an electronic watch by providing a real‐time olfactory map of the environment. Laboratory experiments are described to validate the approach and assess the performance of the proposed system.

The approach was shown to be effective in experimental trials where the robot was able to detect multiple odour sources and differentiate between sources very close to one another.

One limitation of the methodology is that it has been specifically designed for odour detection along a well‐defined path in a highly structured environment, such as that expected in the industrial field. The problem of detection of leakages outside the search path is not addressed here.

This mobile robot can be of great value to detect hazardous fluid leakages in chemical warehouses and industrial sites, thus increasing the safety level for human operators.

The paper describes a mobile robotic system, which employs an odour‐sensing capability to perform automated monitoring of hazardous industrial sites. A dynamic model of the mobile nose is also discussed and it is shown that it well describes the behaviour of the system.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

The purpose of this paper is to review recent progress in electronic nose technologies, focusing on hybrid systems combining biological elements with physical transducers.

Electronic nose technologies are moving rapidly towards hybrid bioelectronic systems, where biological odour-recognition elements from the olfactory pathways of vertebrates and insects are being utilised to construct new “bionic noses” that can be used in industrial applications.

With the increased understanding of how chemical senses and the brain function in biology, an emerging field of “neuromorphic olfaction” has arisen.

Important components are olfactory receptor proteins and soluble proteins found at the periphery of olfaction called odorant-binding proteins. The idea is that these proteins can be incorporated into transducers and function as biorecognition elements for volatile compounds of interest.

Major drivers are the security, environmental and medical applications, and the internet of things will be a major factor in implementing low-cost chemical sensing in networked applications for the future.

Widespread take up of new technologies that are cheap will minimise the impact of environmental pollution, increase food safety and may potentially help in non-invasive screening for medical ailments.

This review brings together diverse threads of research leading to a common theme that will inform a non-expert of recent developments in the field.

Sheds light on why there is now such a proliferation of new chemical sensors. Describes various olfactory sensors and their differing uses. Concludes that in some areas, although not as efficient as traditional methods, sensors do have some merit.

This study aims to describe a bibliometric analysis of recent articles addressing the applications of e- noses with particular emphasis on those dealing with fuel-related products. Documents covering the general area of e-nose research and published between 1975 and 2021 were retrieved from the Web of Science database, and peer-reviewed articles were selected and appraised according to specific descriptors and criteria.

Analyses were performed by mapping the knowledge domain using the software tools VOSviewer and RStudio. It was possible to identify the countries, research organizations, authors and disciplines that were most prolific in the area, together with the most cited articles and the most frequent keywords. A total of 3,921 articles published in peer-reviewed journals were initially retrieved but only 47 (1.19%) described fuel-related e-nose applications with original articles published in indexed journals. However, this number was reduced to 38 (0.96%) articles strictly related to the target subject.

Rigorous appraisal of these documents yielded 22 articles that could be classified into two groups, those aimed at predicting the values of key parameters and those dealing with the discrimination of samples. Most of these 22 selected articles (68.2%) were published between 2017 and 2021, but little evidence was apparent of international collaboration between researchers and institutions currently working on this topic. The strategy of switching energy systems away from fossil fuels towards low-carbon renewable technologies that has been adopted by many countries will generate substantial research opportunities in the prediction, discrimination and quantification of volatiles in biofuels using e-nose.

It is important to highlight that the greatest difficulty in using the e-nose is the interpretation of the data generated by the equipment; most studies have so far used the maximum value of the electrical resistance signal of each e-nose sensor as the only data provided by this sensor; however, from 2019 onwards, some works began to consider the entire electrical resistance curve as a data source, extracting more information from it.

This study opens a new and promising way for the effective use of e-nose as a fuel analysis instrument, as low-cost sensors can be developed for use with the new data analysis methodology, enabling the production of portable, cheaper and more reliable equipment.

Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in consequence the industry. The purpose of the paper is to investigate the interactions between olfactory proteins, odorant-binding proteins (OBPs) and host plant volatiles through the developed olfactory biosensors. It might be helpful to develop novel pest control strategies.

Using the successfully expressed and purified OBPs of the oriental fruit fly Bactrocera dorsalis, a biosensor was developed by immobilizing the proteins on interdigitated electrodes through nitrocellulose membrane. Based on electrochemical impedance sensing, benzaldehyde emitted by the host plants, such as Beta vulgaris, was detected, which could be used to investigate and analyze the mechanisms of pests’ sense of chemical signals. The relative decreases of charge transfer resistances of the sensor were proportional to the odorant concentrations from 10⁻⁷ M to 10⁻³ M. Meanwhile, the interactions between OBPs and benzaldehyde were studied through the process of molecular docking.

The paper provides a pest OBPs-based biosensor that could sensitively detect the host odorants benzaldehyde. Meanwhile, the most related amino acids of OBPs that bind to host plant volatiles can be distinguished with molecular docking.

An olfactory biosensor was developed to explore interactions and mechanism between the pest OBPs and benzaldehyde, which showed promising potentials for small organic molecule sensing. Simultaneously, it might be helpful for novel pest control strategies.

Sensor arrays and pattern recognition-based electronic nose (E-nose) is a typical detection and recognition instrument for indoor air quality (IAQ). The E-nose is able to monitor several pollutants in the air by mimicking the human olfactory system. Formaldehyde concentration prediction is one of the major functionalities of the E-nose, and three typical machine learning (ML) algorithms are most frequently used, including back propagation (BP) neural network, radial basis function (RBF) neural network and support vector regression (SVR).

This paper comparatively evaluates and analyzes those three ML algorithms under controllable environment, which is built on a marketable sensor arrays E-nose platform. Variable temperature (T), relative humidity (RH) and pollutant concentrations (C) conditions were measured during experiments to support the investigation.

Regression models have been built using the above-mentioned three typical algorithms, and in-depth analysis demonstrates that the model of the BP neural network results in a better prediction performance than others.

Finally, the empirical results prove that ML algorithms, combined with low-cost sensors, can make high-precision contaminant concentration detection indoor.

This paper aims to provide a detailed review of weak interaction biosensors and several common biosensor methods for magnifying signals, as well as judiciously guide readers through selecting an appropriate detecting system and signal amplification method according to their research and application purpose.

This paper classifies the weak interactions between biomolecules, summarizes the common signal amplification methods used in biosensor design and compares the performance of different kinds of biosensors. It highlights a potential electrochemical signal amplification method: the G protein signaling cascade amplification system.

Developed biosensors which, based on various principles, have their own strengths and weaknesses have met the basic detection requirements for weak interaction between biomolecules: the selectivity, sensitivity and detection limit of biosensors have been consistently improving with the use of new signal amplification methods. However, most of the weak interaction biosensors stop at the research stage; there are only a minority realization of final commercial application.

This paper evaluates the status of research and application of weak interaction biosensors systematically. The G protein signaling cascade amplification system proposal offers a new avenue for the research and development of electrochemical biosensors.

Describes the improvements that smart sensors will bring to electronic measurement and control systems, and the advantages of using integrated sensors. Outlines the problems encountered when designing integrating electronics for use on a smart sensor chip and lists the major functions that smart sensors must perform. Concludes that the solution to many real life sensor problems will only be found when a well designed “care‐free” intelligent sensor can be produced and continues that the way to realize this concept is to combine a sensor device with a number of micro‐electronic components into a single sensor package.