SBIR Phase I: Internet of Things (IoT)-Enabled Smart Filter
SBIR 第一阶段:支持物联网 (IoT) 的智能过滤器
基本信息
- 批准号:2228149
- 负责人:
- 金额:$ 26.95万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-06-01 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力将是开发一种新颖的空气过滤器监测解决方案,这将对公共卫生、环境和美国经济产生积极影响。该技术基于使用光电传感器直接测量过滤器状态、使用传感器数据精确确定过滤器污染状况的智能信号处理算法以及用于控制和通信的物联网 (IoT)。据世界卫生组织 (WHO) 称,“环境空气污染每年导致约 300 万人死亡……世界上约 90% 的人口所面临的污染水平超过了世界卫生组织的限制。”虽然空气过滤技术本身无法解决环境空气污染这一严峻问题,但它必须成为综合解决方案的组成部分。通过数据驱动的决策来消除过早更换过滤器并降低成本,所提出的技术将推动高质量过滤器的使用更加普遍,从而改善公众健康。有 1.5 亿个供暖、通风和空调 (HVAC) 系统在运行,并且每季度更换一次过滤器,估计每年会制造和丢弃 6 亿个过滤器。由于减少了制造和浪费,减少 50% 的过滤器废物将对环境产生显着的积极影响。这个小型企业创新研究 (SBIR) 第一阶段项目将利用光电传感器的准确性来检测过滤器堵塞的程度,方法是:感测通过滤光片的透射光。看似简单的解决方案背后隐藏着一系列复杂的技术挑战。由于包括褶皱和框架障碍物在内的不均匀结构,传感器数据本质上是有噪声的。软件控制的执行器将传感器放置在过滤器前面,并从过滤器的多个位置获取数据。将开发一种智能算法,从数据集分析中提取参数,该参数将准确代表美国供暖、制冷和空调工程师协会标准中定义的颗粒尺寸去除效率,而该标准预计将是真实过滤器寿命的足够准确的指标。利用物联网功能,传感器数据将被收集在云端,智能算法和控制软件将被存储在云端。最终目标是通过将该参数与基于室内空气质量要求的预定最大颗粒尺寸去除效率和气流阻力得出的阈值参数进行比较,确定过滤器更换的最佳点。该奖项反映了 NSF 的法定使命,并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来获得支持。
项目成果
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