ITR: Human Activity Monitoring Using Simple Sensors

ITR：使用简单传感器监测人类活动

• 批准号: 0312991
• 负责人: Christopher Atkeson
• 金额: $ 31.46万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0312991&HistoricalAwards=false
• 关键词: ITR; Human; Activity; Monitoring; Using

The ITR project "Human Activity Monitoring Using Simple Sensors" explores the use of binary sensors typically found in home security systems to monitor human behavior. We envision systems that mightremind a user that the stove was left on, detect situations that might lead to a fall or injury, or help a caregiver diagnose a treatable mental condition. Science advances include new machine learning techniques to extract more information from simple sensors. The project focuses on Bayesian or probabilistic methods to analyse the sensor data. One implication of this work is that it may help the elderly live in their own homes longer than they might otherwise. The significance of this work is that it focuses on developing the potential of inexpensive sensing and minimizing the invasion of privacy of behavior monitoring systems.

ITR项目“使用简单传感器监测人类活动”探索了使用家庭安全系统中常见的二进制传感器来监测人类行为。我们设想的系统可能会提醒用户炉子开着，检测可能导致跌倒或受伤的情况，或者帮助护理人员诊断可治疗的精神状况。 科学进步包括新的机器学习技术，可以从简单的传感器中提取更多信息。该项目侧重于贝叶斯或概率方法来分析传感器数据。 这项工作的一个意义是，它可能有助于老年人在自己家里生活的时间比其他情况下更长。这项工作的意义在于，它专注于开发廉价传感的潜力，并最大限度地减少行为监测系统对隐私的侵犯。