SBIR Phase II: Radar-based Building Automation

SBIR 第二阶段：基于雷达的楼宇自动化

• 批准号: 2335079
• 负责人: Mustafa Homsi
• 金额: $ 99.98万
• 依托单位: RIVIEH, INC.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335079&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Radar; based

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is in significantly reducing wasted energy in multi-dwelling and residential buildings while improving occupant living experiences. The research proposes the development of advanced sensor technologies and machine learning algorithms to enable an inexpensive hardware infrastructure to control indoor space conditions autonomously. This concept will foster broader adoption of advanced automation technologies among buildings, especially multi-dwelling and residential buildings. One main benefit of indoor automation is its deep energy savings. The Department of Energy estimates that if all residential units deploy energy-saving features offered by building automation solutions, 1-3 quadrillion units of energy will be saved yearly. This can reduce the nation's annual energy budget by $18-$36 billion and eliminate the release of 60-120 metric tons of CO2 emissions. Alongside energy efficiency, the associated societal benefits of the proposed project can potentially save lives. The proposed solution integrates a higher level of security protection in residential spaces in addition to its ability to monitor occupants' health in real time. These life-saving features can significantly limit the impacts of intrusion events and medical emergencies.The proposed project will advance the scientific knowledge required to approach full autonomous control in indoor spaces. Today’s building automation solutions utilize a primitive sensor infrastructure, which has high deployment costs and limits the solution benefits. This leads to a diminished value proposition and a small adoption rate. This project proposes the utilization of advanced perception sensors in buildings. The rich data stream these sensors offer allows for a compact hardware infrastructure to autonomously control indoor spaces and improve the living experience within buildings. Advances in sensing technologies were fundamental to the recent exponential growth in the autonomous driving industry and the realization of a generation-old dream. This research project aims to instigate a similar technological evolution in the autonomous control of indoor spaces. An upgraded implementation of the Phase I evaluation study will be developed to mitigate Phase I learnings. The project also aims to develop a production-ready implementation of the developed sensor technology to prepare it for commercialization and market introduction.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.

这项小型企业创新研究（SBIR）II期项目的更广泛的影响/商业潜力是，在改善职业生活经验的同时，大大降低了多居住​​和居民建筑物的能源。高级传感器技术和机器学习算法的研究建议使廉价的硬件基础架构能够自动控制室内空间条件。这个概念将在建筑物（尤其是多居民和居民）之间更广泛地采用先进的自动化技术。室内自动化的主要好处是其深度节省。能源部估计，如果所有居民部署建筑自动化解决方案提供的节能功能，则每年将节省1-3亿单位的能源。这可以将美国的年度能源预算减少18至360亿美元，并消除60-120公吨的二氧化碳排放。除了能源效率之外，拟议项目的相关社会益处可以挽救生命。拟议的解决方案除了能够实时监测职业健康的能力外，还集成了更高水平的住宅安全保护。这些挽救生命的特征可以显着限制入侵事件和医疗紧急情况的影响。拟议的项目将促进在室内空间中完全自主控制所需的科学知识。当今的建筑自动化解决方案利用原始的传感器基础架构，该基础架构具有很高的部署成本并限制了解决方案收益。这导致价值提议降低和较小的采用率。该项目建议建筑物中高级感知传感器的利用。这些传感器提供的丰富数据流可以自主控制室内空间并改善建筑物内的生活体验。传感技术的进步是自动驾驶行业最近的指数增长和实现一代梦想的基础。该研究项目旨在在室内空间的自主控制中促进类似的技术演变。 I阶段评估研究的升级实施将是为了减轻I阶段学习的发展。该项目还旨在开发已发达的传感器技术的生产准备就绪的实施，以准备商业化和市场介绍。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，通过评估被认为是珍贵的支持。