REVIEWS

Smart gas sensor arrays powered by artificial intelligence

Zhesi Chen1, 2, Zhuo Chen1, 2, Zhilong Song1, 2, Wenhao Ye1, 2 and Zhiyong Fan1, 2,

+ Author Affiliations

 Corresponding author: Zhiyong Fan, E-mail: eezfan@ust.hk

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Abstract: Mobile robots behaving as humans should possess multifunctional flexible sensing systems including vision, hearing, touch, smell, and taste. A gas sensor array (GSA), also known as electronic nose, is a possible solution for a robotic olfactory system that can detect and discriminate a wide variety of gas molecules. Artificial intelligence (AI) applied to an electronic nose involves a diverse set of machine learning algorithms which can generate a smell print by analyzing the signal pattern from the GSA. A combination of GSA and AI algorithms can empower intelligent robots with great capabilities in many areas such as environmental monitoring, gas leakage detection, food and beverage production and storage, and especially disease diagnosis through detection of different types and concentrations of target gases with the advantages of portability, low-power-consumption and ease-of-operation. It is exciting to envisage robots equipped with a "nose" acting as family doctor who will guard every family member's health and keep their home safe. In this review, we give a summary of the state-of the-art research progress in the fabrication techniques for GSAs and typical algorithms employed in artificial olfactory systems, exploring their potential applications in disease diagnosis, environmental monitoring, and explosive detection. We also discuss the key limitations of gas sensor units and their possible solutions. Finally, we present the outlook of GSAs over the horizon of smart homes and cities.

Key words: mobile robotsgas sensor arrayelectronic noseartificial intelligenceenvironmental monitoringdisease diagnosis



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Fig. 1.  (Color online) Smart gas sensor array fabricated by different techniques assisted by artificial intelligence algorithms can find many real-life applications, exhibiting great potential as a mammalian olfactory system in the areas of air and water quality monitoring, non-invasive disease detection, and dangerous gases leakage alarming.

Fig. 2.  (Color online) MOX sensor array fabrication method and morphology[10, 11]: (a) FSP set-up, (b) SEM image of porous doped SnO2 film, (d) USP setup, (e) Cross-section of SnO2 nanotube decorated with Pt nanoparticles, gas sensor array of (c) doped SnO2 microsensors and (f) 3-D SnO2 nanotube.

Fig. 3.  (Color online) (a) Sensor array fabrication methods and morphology[12, 13]: (a) an SEM image of organic functionalized gold nanoparticle film deposited between adjacent electrodes, (b) a TEM image of monolayer capped gold nanoparticles, (d) a TEM image of ultrathin silicon channel, (e) EDS indicating the elemental composition of a single Pd-Au CS-FET, gas sensor array of (c) gold nanoparticles, (f) CS-FET.

Fig. 4.  (Color online) Artificial intelligence algorithms adopted in a gas sensor array.

Fig. 5.  (Color online) Application of gas sensor array [11, 17, 98]. (a) Processes involved in breath testing, (b) gases associated with different kinds of diseases including cancer, (c) GPRS based air pollution monitoring system, (d) real-time indoor gas monitoring by smart phone in smart buildings.

Table 1.   Summary of different types of gas sensor[3337].

Sensor typePrincipleAdvantageDisadvantage
Thermal (catalytic)Catalytic combustion or reaction of target gases providing reaction heat which acts as the output signalLow cost, fast response, simpleDetection of flammable gas only, possibly be poisoned by catalyst.
MassMonitoring gases using mass-sensitivity transducerHigh sensitivity, good reliability, fast responseThe piezoelectric substrate being influenced by temperature
ElectrochemicalReacting with target gases at electrodes and producing electrical signals that are proportional to the gas concentrationLow concentration detection, wide range of detectable gases, good selectivityRelatively shorter lifetime, difficulty in revealing failure mode
OpticalMeasuring optical absorption/emission scattering of target gasesHigh sensitivity, good stability, good selectivityHigh cost, influenced by ambient light
SemiconductorGas adsorption and desorption at the surface of materials leading to electrical resistance change of the materialsLow cost, long lifetime, ease of miniaturization, wide range of detectable gasesPoor selectivity, humidity and temperature dependent, drift along time, normally working at high temperature
Surface acoustic waveMeasuring the velocity or amplitude of acoustic wave propagating through or on the surface of materials which is sensitive to target gasesBattery-less, ease of miniaturization, selectivity depending on receptorComplex fabrication process
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    Received: 01 August 2019 Revised: 23 August 2019 Online: Accepted Manuscript: 29 September 2019Uncorrected proof: 30 September 2019Published: 08 November 2019

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      Zhesi Chen, Zhuo Chen, Zhilong Song, Wenhao Ye, Zhiyong Fan. Smart gas sensor arrays powered by artificial intelligence[J]. Journal of Semiconductors, 2019, 40(11): 111601. doi: 10.1088/1674-4926/40/11/111601 Z S Chen, Z Chen, Z L Song, W H Ye, Z Y Fan, Smart gas sensor arrays powered by artificial intelligence[J]. J. Semicond., 2019, 40(11): 111601. doi: 10.1088/1674-4926/40/11/111601.Export: BibTex EndNote
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      Zhesi Chen, Zhuo Chen, Zhilong Song, Wenhao Ye, Zhiyong Fan. Smart gas sensor arrays powered by artificial intelligence[J]. Journal of Semiconductors, 2019, 40(11): 111601. doi: 10.1088/1674-4926/40/11/111601

      Z S Chen, Z Chen, Z L Song, W H Ye, Z Y Fan, Smart gas sensor arrays powered by artificial intelligence[J]. J. Semicond., 2019, 40(11): 111601. doi: 10.1088/1674-4926/40/11/111601.
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      Smart gas sensor arrays powered by artificial intelligence

      doi: 10.1088/1674-4926/40/11/111601
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      • Corresponding author: E-mail: eezfan@ust.hk
      • Received Date: 2019-08-01
      • Revised Date: 2019-08-23
      • Published Date: 2019-11-01

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