The electronic nose is a gadget that detects smells more accurately than the human nose. An electronic nose is made up of a chemical sensing system. It is an intelligent sensing device that employs an array of selectively overlapping gas sensors as well as a pattern rearrangement component.
E-nose devices come in two types- embedded sensors and portable devices. Moreover, for e-nose, metal oxide semiconductor sensors (MOS), quartz crystal microbalance (QCM), and conducting polymer technologies are used.
Market Drivers and Demand
According to OMR Research, the global electronic nose market is projected to grow at a CAGR of 11.8% during the forecast period (2023-2029). The key factor contributing to this growth is the use of e-nose in a wide range of applications. In the food and beverage sectors, e-noses are commonly utilized for process monitoring, shelf-life study, quality control, quality evaluation, and authenticity evaluation. Owing to the variety of odor-based metrics used to gauge quality, freshness, components, maturity, and so on, the technology is predicted to find multiple uses in the sector. Hence, the growth of the food industry will increase the demand of the e-nose market.
Apart from this, E-noses have a wide range of commercial applications, including in industries and sectors such as agriculture, biomedicine, cosmetics, manufacturing, the military, pharmaceuticals, and various scientific research domains. They can also be used as a safety device in public places such as airports. For instance, e-noses can detect explosives or narcotics for airport security or employ novel fire monitor modules to detect fire for disaster prevention.
Manufacturers are also focusing on producing IoT-enabled portable noses that are low-cost and low-power. For instance, in December 2020, Breathomix developed the BreathBase Platform in conjunction with Microsoft and Tecknoworks. BreathBase is an IoT-based system that uses the SpiroNose e-nose, which is connected to an internet-enabled IoT device (Gateway to BreathBase) that sends the measurements in real-time to a processing component for analysis and interpretation.
Additionally, e-noses are being researched for a variety of new applications. For instance, in 2021, researchers from Japan's Kyushu University and the University of Tokyo developed a new way for unlocking smartphones using e-nose. According to the research, the users have to breathe to unlock their phones. However, the technology is not at a mature stage yet, since its accuracy was only 97.8% during the study.
Recent Developments
The key companies in the e-nose market include Airsense Analytics GmbH, Alpha MOS, Aryballe Technologies, Comon Invent BV, Electronic Nose Co., Ltd., E-nose Pty Ltd., FOODSniffer, MyDx Inc., Odotech Inc., Plasmion GmbH, Roboscientific Ltd., and others. These market players adopt various strategies such as product launches, partnerships, collaborations, mergers, and acquisitions to sustain a strong position in the market and help meet market demand. Some of the recent developments in the market include-
• In February 2022, SmartNanotubes Technologies, a German startup technology business that created a low-power multi-channel gas detector device for the mass market, secured $2.5 million in Series A investment. Cottonwood Technology Fund and duotec GmbH were among the early investors.
• In January 2022, a research team at the Korea Research Institute of Bioscience and Biotechnology's Infectious Disease Research Center announced the invention of a portable e-nose that can check meat freshness. The e-nose can detect putrescine and cadaverine, organic compounds with an unpleasant odor caused by meat putrefaction, in extremely small amounts.
• In June 2021, a study by researchers at the University of Pennsylvania and Penn's Perelman School of Medicine depicted that an odor-based test that sniffs out vapors originating from blood samples can identify between ovarian and benign and pancreatic cancer cells with up to 95% accuracy. The findings suggest that the Penn-developed tool, which employs artificial intelligence (AI) and machine learning (ML) to decipher the combination of volatile organic compounds (VOCs) emitted by cells in blood plasma samples, could be used as a non-invasive method of screening for difficult-to-detect cancers such as pancreatic and ovarian cancer.