SBIR Phase I: Autonomous Living Assistant

SBIR第一阶段：自主生活助手

• 批准号: 2051981
• 负责人: Mustafa Homsi
• 金额: $ 25.6万
• 依托单位: RIVIEH, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051981&HistoricalAwards=false
• 关键词: SBIR; Phase; Autonomous; Living; Assistant

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a wider adoption of autonomous technologies among residential buildings. This research proposes evaluating the use of advanced sensor technologies and machine learning algorithms to enable inexpensive hardware infrastructures to control the conditions in indoor space autonomously. This technology fits well within the capacity of residential buildings. One main benefit of indoor automation is deep energy savings. The Department of Energy estimates a 5% reduction of the country's total energy bill if existing residential buildings save 25% of their energy consumption. The autonomous controller evaluated in this project has the potential to reach this goal, saving the nation up to $63 billion and the planet 284 million metric tons of carbon dioxide emissions. Alongside energy efficiency, the associated societal benefits of the proposed project can potentially save lives. The technologies may spur a higher level of security protection among many unprotected residential spaces. Additionally, tracking occupants’ habits may enable alerts to caregivers or family members in critical emergency situations. This can be beneficial for the aging population that wants to stay within the comfort of their own home.This Small Business Innovation Research (SBIR) Phase I project will advance the scientific knowledge required to approach full autonomous control in indoor spaces. The use of advanced perception sensors in buildings will be evaluated. Their rich data stream will be utilized to develop advanced algorithms for autonomous control of indoor spaces. Advances in sensing technologies and machine learning algorithms will be used to instigate technological evolution in autonomous building systems. A proof of concept will be developed to mitigate the unique risks associated caused by applying autonomous control in indoor spaces, specifically: achieving advanced perception, self-programmability, and reliability.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）I期项目的更广泛的影响/商业潜力是在住宅建筑中广泛采用自主技术。这项研究提案评估了高级传感器技术和机器学习算法的使用，以使廉价的硬件基础架构能够自主控制室内空间中的条件。该技术非常适合住宅建筑物的能力。室内自动化的主要好处是节省大量能源。如果现有的住宅建筑节省了其能源消耗的25％，那么能源部估计该国总能源账单的总收入为5％。在该项目中评估的自治控制器有可能实现这一目标，为国家节省了高达630亿美元，地球2.84亿吨二氧化碳排放。除了能源效率之外，拟议项目的相关社会益处可以节省生命。这些技术可能刺激许多未受保护的居民空间中更高的安全保护。此外，跟踪居民的习惯可能会在关键紧急情况下向看护人或家庭成员发出警报。这对于想要保持自己舒适的家中的老龄化人口可能是有益的。这项小型企业创新研究（SBIR）I阶段项目将促进在室内空间中完全自主控制所需的科学知识。将评估高级感知传感器在建筑物中的使用。他们丰富的数据流将用于开发高级算法，以自主控制室内空间。传感器技术和机器学习算法的进步将用于促进自主建筑系统中的技术发展。将开发概念证明，以减轻在室内空间中应用自主控制引起的独特风险，特别是：实现高级感知，可自我编程性和可靠性。该奖项反映了NSF的法定任务，并被认为是通过使用基金会的知识分子和更广泛的影响来通过评估来获得支持的珍贵的支​​持。