I-Corps: Measuring thermal efficiency in buildings using a thermal energy imaging platform with AI and thermodynamic analysis

I-Corps项目的更广泛影响/商业潜力是开发与热效率有关的能源评估自动化技术。老化的基础设施和不充分的防风雨措施增加了电力和天然气的消耗水平和排放。控制消费率的最佳手段是通过适当的量化能源评估提高能源效率和实现耐候性。该技术可以更快、更安全、更准确地对住宅和商业建筑进行热评估，为识别最大能耗点和提高结构热效率的措施提供丰富的数据源。这项技术的主要市场是公立和私立教育机构，如高等教育大学和K-12机构。设施和工厂经理可以使用该技术快速确定降低公用事业费用和延长结构寿命的措施。能源消耗的量化也可能使这些管理者能够获得进一步的州或联邦资金，用于结构改进。此外，所提出的技术可能对从事建筑项目的风化专家和结构工程师有用，并帮助公用事业提供商进行能源基础设施检查。这个I-Corps项目基于一种技术的开发，该技术可以使用人工智能，数据分析和热力学将从安装在UAS上的辐射红外传感器捕获的热图像快速转换为能源利用估计。红外传感器捕获的热图像经过大气衰减校正，并由人工智能处理，以识别建筑物立面的各个组件和任何热异常。利用热力学程序计算每个元件的热传导或U值，并根据所考虑的元件尺寸以及用于空间加热/冷却的公用设施类型沿着计算建筑物热损失的财务影响。该技术解决方案旨在实现建筑物热评估过程的自动化，与传统评估技术相比，可将总体处理时间减少90%，现场检查时间减少60%。该技术的初步研究进行了三年多的时间，在整个北达科他州的各种结构的热图像进行了分析，并交叉引用其热剖面。该技术已经通过增加财务影响计算和相应的建模工具沿着以及更结构化的数据工作流程得到了改进。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

The broader impact/commercial potential of this I-Corps project is the development of automation technology for energy assessment related to thermal efficiency. Aging infrastructure and insufficient weatherization measures have increased power and natural gas consumption levels and emissions. The best means of reigning in consumption rates are improved energy efficiency and weatherization enabled through proper quantified energy assessments. The proposed technology enables faster, safer, and more accurate thermal assessments for residential and commercial buildings, providing a data-rich source for identification of points of largest energy consumption and measures to improve thermal efficiency of structures. The primary market this technology is public and private educational institutions like higher-education universities and K-12 institutions. Facility and Plant Managers may be able to use the technology to rapidly identify measures to reduce utility charges and increase the lifespan of structures. The quantification of energy consumption also may enable these mangers to access further state or federal funding for structural improvements. In addition, the proposed technology may be useful for weatherization experts and structural engineers working on construction projects and aiding utility providers for energy infrastructure inspection. This I-Corps project is based on the development of a technology to quickly convert thermal images captured from a UAS mounted radiometric infrared sensor to energy utilization estimations using artificial intelligence, data analytics, and thermodynamics. The thermal images captured by the infrared sensors are corrected for atmospheric attenuation and processed by the artificial intelligence to identify individual components of a building’s façade and any thermal anomalies. Thermodynamic procedures are utilized to calculate the heat conductance or the U-value of each element and calculate the financial impact of heat loss from the building depending on the dimensions of the elements being considered along with the type of utility used for space heating/cooling. This technology solution is slated to automate thermal assessment processes for buildings and reduce the overall processing time by 90% and on-site inspection time by 60% compared to traditional assessment techniques. The initial research for the technology was performed over a three-year period where thermal images of various structures throughout North Dakota were analyzed and cross-referenced for their thermal profiles. The technology has since been improved by adding financial impact calculations and corresponding modeling tools along with a more structured data workflow process.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.