Our unique sensor hardware and software provide a data-driven, closed-loop solution for electronic cigarette users to monitor all their puffs in real with quantitative information. Users can effortlessly manage their vaping habits and be guided to reduce or quit vaping.
Our smart sensors can identify abnormal aerosols and manage health risks for users. Vaping device manufacturers can build safer devices by incorporating our sensors. Device safety and health risks are two crucial aspects in receiving FDA's PMTA approval for vaping products.
We introduce the concept "clouds to CLOUD", meaning from "clouds of vaping aerosols" to the "Data Cloud". Through wireless connectivity, sensor data for every puff is uploaded to the Data Cloud to enable personalized data analytics on individual users' vaping patterns.
Cloud-powered analytics on individual users' sensor data can recognize users' vaping habits, and predict the long-term health consequences of vaping. The diagnostic informatics can guide users into healthier vaping habits and prevent dangerous vaping habits.
We study major parameters of vaping aerosols, including particulate matter, toxic and addictive chemicals, and lung deposition. We investigate the connections between vaping and respiratory, cardiovascular, and behavioral disorders. We also provide data to support research on vaping.
We develop specialized vaping devices to help heavy smokers quit traditional smoking. The safety and effectiveness of our devices come from our innovative sensors, which track aerosol consumption and nicotine dosage to guide users to quit smoking.
Smart Electronic Cigarettes
LumCentric introduced smart electronic cigarettes with built-in aerosol sensors. As an integrated device, the user's vaping history and pattern is seamlessly synced with a connected mobile device, which is crucial for managing health risk of vaping.
Puff Topography Sensor
LumCentric developed puff topography sensors that can quantify the mass of total particulate matter (PM) and the nicotine dose puff by puff. The sensor output is highly accurate for a very wide range of vaping habits and allows tracking the puff topography for individual users.
Vaping Aerosol Sensor for Size-Specific PM
Using multi-spectral optical sensing and machine learning, we accomplished measuring PM in specific size channels, which provides crucial information for estimating lung deposition of e-cigarette aerosols.
Vaping Aerosol Safety Sensor
A smart sensor that can detect the quality of the vaping aerosols. If dangerous aerosols are detected, warnings will be triggered to intervene with the users' vaping behaviors.
[1] Hao Jiang. “Aerosol delivery device with aerosol sensor assembly for detecting physical and chemical properties of the generated aerosol.” U.S. Patent Application No. US20220280732A1, published on Sep 08, 2022. [Patent pending]
[2] Hao Jiang, and Keith Kolaczyk. "Quantification of Size-Binned Particulate Matter in Electronic Cigarette Aerosols Using Multi-Spectral Optical Sensing and Machine Learning" Sensors 24 (2024): 7082. https://doi.org/10.3390/s24217082
[3] Keith Kolaczyk, and Hao Jiang. “Photometric monitoring of electronic cigarette puff topography.” Sensors 23 (2023): 8220. https://doi.org/10.3390/s23198220
[4] Hao Jiang, and Keith Kolaczyk. “Quantification of size-binned particulate matter in electronic cigarette aerosols using multi-spectral optical sensing and machine learning.” Sensors. [submitted journal manuscript]
[5] Hao Jiang. “Smart electronic cigarettes with built-in aerosol sensors.” IEEE Sensors Annual Conference 2022, Dallas, TX, Nov 2022.
[6] Keith Kolaczyk, and Hao Jiang. “Monitoring of vaping aerosols inside vehicle cabins using optical particle counters.” IEEE Southeastern Michigan Spring Conference 2023, Southfield, MI, Mar 2023.
[7] Sophia Judge, Juan Jaramillo, and Hao Jiang. “Numerical study of metal nano-orifices for optical sizing of ultrafine particles in aerosols.” Plasmonics 19 (2023): 145-158. https://doi.org/10.1007/s11468-023-01959-x
[8] Hao Jiang, and Sophia Judge. “An optofluidic nanoplasmonic sensor for aerosols.” IEEE Photonics Conference 2023, Orlando, FL, Nov 2023.
[9] Sophia Judge, and Hao Jiang. “Rational selection of metal subwavelength apertures for sensing aerosol nanoparticles.” IEEE Photonics Conference 2023, Orlando, FL, Nov 2023.
[10] Sophia Judge, and Hao Jiang. “Compact optical sensor for detecting airborne ultrafine particles inside vehicle cabins.” IEEE Southeastern Michigan Spring Conference 2023, Southfield, MI, Mar 2023.
These research works were funded by National Science Foundation, Engineering Research Initiation Award (No. 2138534) https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138534
Main research and development activities of LumCentric are conducted at the Aerosol Research Lab at Lawrence Technological University. The lab was established by Dr. Hao Jiang in 2022, after receiving the NSF grant (Award No. 2138534).
The major research focus is Aerosol Sensing for Health, which stands for studying aerosols for health-related applications including bioaerosol detection, vaping/smoking aerosol sensing, and environmental aerosol monitoring. The research works at the lab center on experimentation of novel optical nanostructures, cutting-edge optical configurations, and advanced aerosol manipulation schemes, integrated with computational modeling and machine learning.
The lab is equipped with advanced aerosol research instruments which are crucial for studying electronic cigarettes. The available instruments and resources are listed below:
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