Ainos Expands Smell AI Platform into Digital Breath Intelligence Through National Taiwan University Research Program

Ainos (NASDAQ:AIMD) launched a one-year research program with National Taiwan University to extend its Smell AI platform from environmental sensing into digital breath intelligence for emergency medicine.

Rhea-AI Summary

Ainos (NASDAQ:AIMD) launched a one-year research program with National Taiwan University to extend its Smell AI platform from environmental sensing into digital breath intelligence for emergency medicine. The study will analyze exhaled VOCs to create AI-based breath-print Smell IDs for dyspneic patients.

The program will investigate whether VOC patterns can support a Deep Dyspnea Differential system to help distinguish AECOPD, ADHF, and control groups. Activities include prospective enrollment, breath sampling, deep learning model training, and external validation against final clinical diagnoses. The technology and workflow remain research-stage.

Argus Jun 17 session

+8.51% close to close Open Argus

Details

News Market Reaction – AIMD

On Jun 17, the day this news came out, AIMD closed 8.51% above the previous close.

Data tracked by StockTitan Argus for the Jun 17 session.

Market Context

On Jun 17, the day this news came out, the stock closed 8.5% above the previous close. A strong posi...

Analysis

On Jun 17, the day this news came out, the stock closed 8.5% above the previous close. A strong positive reaction aligns with Ainos’ ongoing pivot toward Smell AI deployments across healthcare and industrial settings. Past AI-tagged news often saw selling pressure despite positive themes, so a sharp gain on this breath-intelligence expansion could reflect changing sentiment. Investors would still need to monitor execution on the NTU program and any commercialization steps that follow this one-year research effort.

Key Figures

Program duration: 1 year Program start date: July 1, 2026

Program duration

1 year

Research program scheduled runtime from start date

Program start date

July 1, 2026

Start of Smell AI dyspnea research program at NTU

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24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

volatile organic compounds, vocs, dyspnea, acute exacerbation of chronic obstructive pulmonary disease, +4 more

8 terms

volatile organic compounds medical

"explore the use of Smell AI platform to analyze volatile organic compounds ("VOCs") in exhaled breath"

Volatile organic compounds (VOCs) are carbon-based chemicals that easily evaporate into the air at room temperature, like the strong-smelling fumes from paint or gasoline. Investors should care because VOCs can trigger health and environmental regulations, cleanup obligations, fines, and restrictions that raise costs, limit operations or reduce property values; think of them as invisible liabilities that can affect a company’s finances and reputation.

vocs medical

"analyze volatile organic compounds ("VOCs") in exhaled breath"

VOCs, or volatile organic compounds, are chemicals that easily evaporate into the air from products like paints, cleaning supplies, and fuels. They can affect air quality and may pose health risks with prolonged exposure. For investors, high levels of VOC emissions can signal environmental concerns or regulatory changes that might impact a company's operations or reputation.

dyspnea medical

"evaluate patients presenting with dyspnea, commonly known as shortness of breath"

Dyspnea is the medical term for shortness of breath or a feeling that breathing is difficult, like trying to breathe through a narrow straw. For investors, it matters because it can be a key symptom in clinical trial results, safety reports or product labels — affecting drug approvals, hospital admissions, and demand for treatments or devices. Changes in dyspnea rates can influence regulatory outcomes and market expectations.

acute exacerbation of chronic obstructive pulmonary disease medical

"Patients with acute exacerbation of chronic obstructive pulmonary disease ("AECOPD") and acute decompensated heart failure"

A sudden worsening of chronic obstructive pulmonary disease (COPD) symptoms — such as shortness of breath, coughing, and sputum production — that usually requires extra treatment or hospitalization. Think of it like a flare-up that interrupts a steady condition and can drive higher healthcare use, costs, and risk for the patient; for investors, frequency and severity of these events affect demand for drugs, hospital services, and the financial outlook for companies making COPD therapies or related healthcare products.

aecopd medical

"acute exacerbation of chronic obstructive pulmonary disease ("AECOPD") and acute decompensated heart failure"

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a sudden worsening of breathing symptoms—such as increased shortness of breath, coughing, or phlegm—in people with long-term lung disease. Think of it as a sudden storm that disrupts an otherwise manageable condition. For investors, AECOPD is important because preventing or shortening these flare-ups is a common goal in drug and device trials, drives hospital visits and costs, and can shape the commercial value of respiratory therapies.

acute decompensated heart failure medical

"acute exacerbation of chronic obstructive pulmonary disease ("AECOPD") and acute decompensated heart failure ("ADHF")"

A sudden worsening of heart function that causes rapid buildup of fluid and severe breathlessness, often requiring emergency care or hospital admission. Think of the heart as a pump that suddenly loses power and allows fluid to back up into the lungs and body; this is an urgent medical problem that drives demand for hospital services, drugs, medical devices and long-term care, and can quickly affect the commercial and regulatory outlook for companies tied to heart-failure treatment.

adhf medical

"acute decompensated heart failure ("ADHF") can appear similar at first"

Acute decompensated heart failure (ADHF) is a sudden worsening of chronic heart failure where the heart can’t pump blood effectively, causing breathlessness, fluid buildup and urgent hospital care — think of the heart as a pump that suddenly gets overloaded and backs up. It matters to investors because ADHF drives high rates of hospital admissions, ongoing treatment needs and drug or device demand, so changes in treatments, trial results or guidelines can quickly affect healthcare costs and the revenue prospects of related companies.

deep learning model technical

"include prospective enrollment, breath sampling ... deep learning model training, and external validation"

A deep learning model is a type of computer program that learns to recognize patterns and make predictions by digesting large amounts of data, similar to how someone becomes better at a task by practicing many examples. For investors, these models can drive faster automation, smarter forecasting, and new product features that boost growth, but they also introduce risks around errors, opaque decision-making, data needs, and regulatory scrutiny that can affect a company’s performance.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Program expands Ainos' Smell AI platform from environmental intelligence into digital breath intelligence for emergency medicine research

HOUSTON, TX / ACCESS Newswire / June 17, 2026 / Ainos, Inc. (NASDAQ:AIMD)(NASDAQ:AIMDW) ("Ainos" or the "Company"), a pioneer in AI-powered scent digitization and Smell AI technologies, today announced a new research program with National Taiwan University ("NTU") to explore the use of Smell AI in emergency medicine.

The program, titled "Rapid Diagnosis of Dyspneic Patients in the Emergency Department via AI-powered Electronic Nose Technology," will explore the use of Ainos' Smell AI platform to analyze volatile organic compounds ("VOCs") in exhaled breath. The goal is to study whether AI-driven breath-print analysis can help emergency physicians more quickly evaluate patients presenting with dyspnea, commonly known as shortness of breath.

Ainos' Smell AI technology, powered by AI Nose and Smell Language Model, traces its roots to healthcare-focused R&D, where the need for non-invasive sensing, accuracy, and real-world validation helped shape the Company's core technology platform.

This program differs from Ainos' existing National Taiwan University Hospital initiative by expanding Smell AI from healthcare environmental sensing into patient-level digital breath intelligence, studying whether exhaled VOC patterns can become machine-readable breath-print Smell ID for emergency medicine research.

Dyspnea is one of the most common and difficult symptoms seen in emergency departments. Patients with acute exacerbation of chronic obstructive pulmonary disease ("AECOPD") and acute decompensated heart failure ("ADHF") can appear similar at first, although they often require different treatment pathways. The research program aims to develop and evaluate a Deep Dyspnea Differential system designed to analyze VOC-based breath prints and study whether those patterns may help differentiate AECOPD, ADHF, and non-disease control groups.

"Emergency dyspnea triage is a high-value clinical challenge where time and diagnostic clarity are critical," said Eddy Tsai, Chairman, President and Chief Executive Officer of Ainos. "AI Nose was originally developed with medical diagnostic applications in mind, where non-invasive sensing, accuracy, and real-world validation are essential. This research program brings that experience back into a high-value clinical setting and extends our Smell AI platform into digital breath intelligence. We believe this is an important step in advancing our broader vision of building Smell ID data and Smell Language Model capabilities across healthcare, industrial, and physical AI environments."

The program is expected to include prospective enrollment, breath sampling from emergency department patients and control subjects, deep learning model training, and external validation against final clinical diagnoses. If successful, the research may contribute to a breath-print database for dyspnea and support future studies in emergency, outpatient, pre-hospital, and home-monitoring settings.

"This program reflects Ainos' platform strategy," added Mr. Tsai. "Across semiconductor manufacturing, healthcare infrastructure, robotics, and emergency breath analysis, our objective is to convert previously inaccessible scent and VOC signals into structured data for AI systems. Each real-world deployment can expand the data foundation for Smell AI."

The research program is scheduled to run for one year, from July 1, 2026. The technology and workflow remain research-stage.

About AI Nose

AI Nose digitizes scent into Smell ID, an AI-driven form of scent intelligence. The full-stack electronic nose platform integrates high-precision sensor arrays with proprietary AI algorithms designed to support ppb-level scent detection sensitivity, subject to application conditions and deployment configurations. Smell ID converts analog scent signals into structured, actionable data, while the proprietary Smell Language Model (SLM) is designed to learn, classify, and contextualize complex scent patterns over time.

Built upon more than a decade of accumulated scent data and deep medtech expertise, AI Nose is designed to support continuous monitoring, predictive analysis, and real-time alerts across industrial and manufacturing environments. AI Nose is offered under a SmellTech-as-a-Service architecture, intended to support ongoing access to scent intelligence, analytics, and AI-driven insights through subscription-based deployment models.

About Ainos, Inc.

Ainos, Inc. (NASDAQ:AIMD) is a dual-platform AI and biotech company pioneering smelltech and immune therapeutics. Its AI Nose platform and smell language model (SLM) digitize scent into Smell ID, a machine-readable data format, powering intelligent sensing across robotics, smart factories, and healthcare. The company also develops VELDONA^®, a low-dose oral interferon targeting rare, autoimmune, and infectious diseases. Ainos, a fusion of "AI" and "Nose," is redefining machine perception for the sensory age. To learn more, visit https://www.ainos.com. Follow Ainos on X, formerly known as Twitter, (@AinosInc) and LinkedIn to stay up-to-date. Visit media room https://ainos.suite.accessnewswire.com.

Forward-Looking Statements

Certain statements in this press release are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. All statements other than statements of historical fact are forward-looking statements. Forward-looking statements are based on management's current assumptions and expectations of future events and trends, which affect or may affect the Company's business, strategy, operations or financial performance, and actual results and other events may differ materially from those expressed or implied in such statements due to numerous risks and uncertainties. Forward-looking statements are inherently subject to risks and uncertainties, some of which cannot be predicted or quantified. There are a number of important factors that could cause actual results, developments, business decisions or other events to differ materially from those contemplated by the forward-looking statements in this press release. These factors include, among other things, our expectation that we will incur net losses for the foreseeable future; our ability to become profitable; our ability to raise additional capital to continue our product development; our ability to accurately predict our future operating results; our ability to advance our current or future product candidates through clinical trials, obtain marketing approval and ultimately commercialize any product candidates we develop; the ability to obtain and maintain regulatory approval of our product candidates; delays in completing the development and commercialization of our current and future product candidates; developing and commercializing additional products, including diagnostic testing devices; our ability to compete in the marketplace; compliance with applicable laws, regulations and tariffs, and factors described in the Risk Factors section of our public filings with the Securities and Exchange Commission (SEC). Because forward-looking statements are inherently subject to risks and uncertainties, you should not rely on these forward-looking statements as predictions of future events. These forward-looking statements speak only as of the date of this press release and, except to the extent required by applicable law, the Company undertakes no obligation to update or revise these statements, whether as a result of any new information, future events and developments or otherwise.

Contact Information
Investor Relations
ir@ainos.com

SOURCE: Ainos, Inc.

View the original press release on ACCESS Newswire

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What did Ainos (NASDAQ:AIMD) announce about its Smell AI digital breath intelligence program on June 17, 2026?

Ainos announced a one-year research program with National Taiwan University to apply its Smell AI to digital breath intelligence in emergency medicine. According to Ainos, the project focuses on analyzing exhaled VOCs to create AI-driven breath-print Smell IDs for dyspneic patients.

How will Ainos' Smell AI be used for dyspnea diagnosis in the new AIMD research program?

The program will use Ainos' Smell AI to analyze volatile organic compounds in exhaled breath from emergency patients with dyspnea. According to Ainos, deep learning models will study whether VOC-based breath prints can help differentiate AECOPD, ADHF, and non-disease control groups.

What is the Deep Dyspnea Differential system in Ainos (AIMD) emergency breath analysis research?

The Deep Dyspnea Differential system is a planned AI tool to analyze VOC-based breath prints from dyspneic patients. According to Ainos, the research aims to evaluate whether these patterns may support distinguishing AECOPD, ADHF, and control subjects in emergency settings.

When does the Ainos and National Taiwan University Smell AI breath intelligence study begin and how long will it run?

The research program is scheduled to start on July 1, 2026, and run for one year. According to Ainos, the project includes prospective patient enrollment, breath sampling, model training, and external validation against final clinical diagnoses in emergency departments.

Is Ainos' digital breath intelligence technology for dyspnea currently commercial or still at the research stage?

Ainos’ digital breath intelligence and Deep Dyspnea Differential system remain at the research stage. According to Ainos, the program focuses on building a dyspnea breath-print database and validating AI models, potentially supporting future studies in emergency, outpatient, pre-hospital, and home-monitoring settings.

How does the new AIMD Smell AI breath program differ from Ainos' existing National Taiwan University Hospital initiative?

The new program moves from environmental healthcare sensing into patient-level digital breath intelligence in emergency medicine. According to Ainos, it specifically studies exhaled VOC patterns as machine-readable breath-print Smell IDs, while the hospital initiative focuses on broader healthcare environmental applications.