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

I-Corps项目更广泛的影响/商业潜力是开发与热效率相关的能源评估自动化技术。老化的基础设施和不充分的气候措施增加了电力和天然气的消费水平和排放。控制消费率的最佳手段是通过适当的量化能源评估来提高能源效率和实现天气预报。提出的技术能够更快、更安全、更准确地对住宅和商业建筑进行热评估，为识别最大的能源消耗点和提高结构热效率的措施提供丰富的数据来源。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。设施和工厂管理人员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以使这些管理者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气象专家和结构工程师有用，并帮助公用事业供应商进行能源基础设施检查。I-Corps项目的基础是开发一种技术，利用人工智能、数据分析和热力学，将安装在无人机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会根据大气衰减进行校正，并由人工智能进行处理，以识别建筑物立面的各个组成部分和任何热异常。热力学程序用于计算每个元件的导热系数或u值，并根据所考虑的元件的尺寸以及用于空间加热/冷却的公用设施的类型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，可将总体处理时间缩短90%，现场检查时间缩短60%。该技术的初步研究历时三年，分析了北达科他州各种结构的热图像，并对其热剖面进行了交叉参考。此后，该技术得到了改进，增加了财务影响计算和相应的建模工具，以及更结构化的数据工作流程。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

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.