2228149
Project Grant
Overview
Grant Description
Sbir Phase I: Internet of Things (IoT)-enabled smart filter -The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the development of a novel solution for air filter monitoring that will have a positive impact on public health, the environment, and the US economy.
The technology is based upon the direct measurement of the filter status using photosensors, smart signal processing algorithms for accurate filter soiling condition determination using the sensor data, and the Internet of Things (IoT) for control and communication.
According to the World Health Organization (WHO), "ambient air pollution kills about 3 million people annually" about 90 percent of the world's population is exposed to levels exceeding WHO limits. While air-filtration technology alone cannot solve the overwhelming problem of ambient air pollution, it must be an integral part of a comprehensive solution.
With data-driven decision making to eliminate premature filter replacement and to reduce costs, the proposed technology will propel the usage of high-quality filters more ubiquitously, leading to enhanced public health.
With 150 million heating, ventilation and air conditioning (HVAC) systems in operation, and quarterly filter replacement, an estimated 600 million filters are manufactured and thrown away every year. A reduction of 50% of the filter waste will have a significant positive impact on the environment because of reduced manufacturing and waste.
This Small Business Innovation Research (SBIR) Phase I project will leverage the accuracy of photosensors in detecting the degree of filter blockage by sensing transmitted light through the filter. Underlying the seemingly straightforward solution is a set of complex technical challenges.
Due to the uneven structure including pleats and frame obstructions, the sensor data are inherently noisy. A software-controlled actuator will place the sensor in front of the filter and take data from multiple locations of the filter.
A smart algorithm will be developed to extract a parameter from the analysis of the data set that would be an accurate proxy for the particle size removal efficiency defined in the American Society of Heating, Refrigerating and Air-Conditioning Engineers standard which in turn is expected to be a sufficiently accurate indicator of the true filter age.
Using the IoT capability, the sensor data will be collected in the cloud, where the smart algorithm and control software will be stored. The final objective is to determine the optimum point for filter replacement by comparing the parameter with a threshold parameter derived from a predetermined maximum particle size removal efficiency and airflow resistance based on indoor air quality requirements.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
The technology is based upon the direct measurement of the filter status using photosensors, smart signal processing algorithms for accurate filter soiling condition determination using the sensor data, and the Internet of Things (IoT) for control and communication.
According to the World Health Organization (WHO), "ambient air pollution kills about 3 million people annually" about 90 percent of the world's population is exposed to levels exceeding WHO limits. While air-filtration technology alone cannot solve the overwhelming problem of ambient air pollution, it must be an integral part of a comprehensive solution.
With data-driven decision making to eliminate premature filter replacement and to reduce costs, the proposed technology will propel the usage of high-quality filters more ubiquitously, leading to enhanced public health.
With 150 million heating, ventilation and air conditioning (HVAC) systems in operation, and quarterly filter replacement, an estimated 600 million filters are manufactured and thrown away every year. A reduction of 50% of the filter waste will have a significant positive impact on the environment because of reduced manufacturing and waste.
This Small Business Innovation Research (SBIR) Phase I project will leverage the accuracy of photosensors in detecting the degree of filter blockage by sensing transmitted light through the filter. Underlying the seemingly straightforward solution is a set of complex technical challenges.
Due to the uneven structure including pleats and frame obstructions, the sensor data are inherently noisy. A software-controlled actuator will place the sensor in front of the filter and take data from multiple locations of the filter.
A smart algorithm will be developed to extract a parameter from the analysis of the data set that would be an accurate proxy for the particle size removal efficiency defined in the American Society of Heating, Refrigerating and Air-Conditioning Engineers standard which in turn is expected to be a sufficiently accurate indicator of the true filter age.
Using the IoT capability, the sensor data will be collected in the cloud, where the smart algorithm and control software will be stored. The final objective is to determine the optimum point for filter replacement by comparing the parameter with a threshold parameter derived from a predetermined maximum particle size removal efficiency and airflow resistance based on indoor air quality requirements.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Awardee
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
East Brunswick,
New Jersey
08816-5154
United States
Geographic Scope
Single Zip Code
Related Opportunity
None
Pollux Technologies was awarded
Project Grant 2228149
worth $269,498
from National Science Foundation in June 2023 with work to be completed primarily in East Brunswick New Jersey United States.
The grant
has a duration of 8 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I:Internet of Things (IoT)-Enabled Smart Filter
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the development of a novel solution for air filter monitoring that will have a positive impact on public health, the environment, and the US economy. The technology is based upon the direct measurement of the filter status using photosensors, smart signal processing algorithms for accurate filter soiling condition determination using the sensor data, and the Internet of Things (IoT) for control and communication. According to the World Health Organization (WHO), "Ambient air pollution kills about 3 million people annually... About 90 percent of the world's population is exposed to levels exceeding WHO limits." While air-filtration technology alone cannot solve the overwhelming problem of ambient air pollution, it must be an integral part of a comprehensive solution. With data driven decision making to eliminate premature filter replacement and to reduce costs, the proposed technology will propel the usage of high-quality filters more ubiquitously, leading to enhanced public health. With 150 million heating, ventilation and air conditioning (HVAC) systems in operation, and quarterly filter replacement, an estimated 600 million filters are manufactured and thrown away every year. A reduction of 50% of the filter waste will have a significant positive impact on the environment because of reduced manufacturing and waste._x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase I project will leverage the accuracy of photosensors in detecting the degree of filter blockage by sensing transmitted light through the filter. Underlying the seemingly straightforward solution is a set of complex technical challenges. Due to the uneven structure including pleats and frame obstructions, the sensor data are inherently noisy. A software-controlled actuator will place the sensor in front of the filter and take data from multiple locations of the filter. A smart algorithm will be developed to extract a parameter from the analysis of the data set that would be an accurate proxy for the particle size removal efficiency defined in the American Society of Heating, Refrigerating and Air-Conditioning Engineers standard which in turn is expected to be a sufficiently accurate indicator of the true filter age. Using the IoT capability, the sensor data will be collected in the cloud, where the smart algorithm and control software will be stored. The final objective is to determine the optimum point for filter replacement by comparing the parameter with a threshold parameter derived from a predetermined maximum particle size removal efficiency and airflow resistance based on indoor air quality requirements._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
I
Solicitation Number
NSF 22-551
Status
(Complete)
Last Modified 6/6/23
Period of Performance
6/1/23
Start Date
2/29/24
End Date
Funding Split
$269.5K
Federal Obligation
$0.0
Non-Federal Obligation
$269.5K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2228149
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
SCKBLJAGLK39
Awardee CAGE
8SNV8
Performance District
12
Senators
Robert Menendez
Cory Booker
Cory Booker
Representative
Bonnie Watson Coleman
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $269,498 | 100% |
Modified: 6/6/23