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._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.