Machine learning, dense sensing and decision theoretic planning for large-scale assistance systems

大规模辅助系统的机器学习、密集感知和决策理论规划

• 批准号: 402243-2011
• 负责人: Hoey, Jesse
• 金额: $ 2.11万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=508287
• 关键词: Machine; learning; dense; sensing; decision

Assistance for elderly persons is becoming an important and pressing need with serious effects on society because of the changing demographic towards an aging population (the so-called "Silver Tsunami''). The burden of care is shifting from the professional arena (e.g., hospitals) into the home and community. Technology to support people in their need to live independently is currently available in the form of personal alarms and environmental aids. Looking to the future, we can imagine intelligent, pervasive computing technologies using sensors and effectors that help with more difficult cognitive problems in planning, sequencing and attention.

由于人口老龄化（所谓的“银海啸”），对老年人的援助正成为一项重要而紧迫的需求，对社会产生严重影响。护理的负担正在从专业竞技场转移（例如，医院，进入家庭和社区。支持人们独立生活的技术目前以个人警报和环境辅助的形式提供。展望未来，我们可以想象使用传感器和效应器的智能普适计算技术，这些技术有助于解决规划、排序和注意力等更困难的认知问题。