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CSR: Small: Collaborative Research: Smartphone Enabled Social and Physical Compass System (SENSCOPS)

CSR: Small: Collaborative Research: Smartphone Enabled Social and Physical Compass System (SENSCOPS)
CSR:小型:协作研究:智能手机支持的社交和物理罗盘系统 (SENSCOPS)
批准号:
1217387
负责人:
Yingying Chen
金额:
$22.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2016-02-29

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中文摘要
翻译
配备强大嵌入式传感器的智能手机(例如加速计、GPS、麦克风等)可用于监测人类行为的多个维度,包括身体、精神和社会行为的福祉。特别是,移动设备中的这种增强功能使人们能够更好地管理自己的健康。现有的移动健康应用程序大多依赖于手动数据输入,对于某些人群,例如患有情绪行为障碍(EBD)的老年人和学生,这可能是不够的。该项目旨在建立一个多模式传感系统,为用户提供持续有效的监测?使用移动电话和可穿戴传感器的活动。我们的系统分析和关联不同的传感器流,以推断某些行为以及可能触发此类行为的可能环境因素。此外,我们的系统提供了非侵入性的同伴辅助定位技术,允许照顾者跟踪被监视用户的下落。我们还开发了有效的方案来推断更高层的信息,例如受监视个人的活动水平;受监视用户之间的社会关系。此外,在我们的系统中,从移动电话启用的社交网络中提取的社区不仅支持移动医疗系统,而且还可以用于保护系统的某些组件(例如,应对克隆攻击)。我们的系统允许对用户的心理、认知和身体健康状况进行监测,并可能由于提高教师和照顾者的生产力而降低特殊需要教育的成本。
英文摘要
Smartphones equipped with powerful embedded sensors (e.g. accelerometers, GPS, microphones, etc.) can be used to monitor multiple dimensions of human behaviors including physical, mental, and social behaviors of wellbeing. In particular, such enhanced capabilities in mobile devices enable people to better manage their health. Existing mobile health applications mostly rely on manual data entry which may not be sufficient for certain population e.g. seniors and students with emotional behavioral disorders (EBD). This project aims to build a multimodal sensing system which provides continuous and efficient monitoring of users? activities using mobile phones and wearable sensors. Our system analyzes and correlates different sensor streams to infer certain behaviors as well as possible environmental factors that may trigger such behaviors. Furthermore, our system provides non-intrusive peer assisted localization technique that allows caregivers to track the whereabouts of monitored users. We also develop efficient schemes to infer higher layer information e.g. activity levels of monitored individuals; social relationships among monitored users. Additionally, the communities extracted from a mobile phone enabled social network in our system not only enable mobile healthcare systems but can also be exploited for securing certain components of the system (e.g., coping with clone attacks). Our system allows users to be monitored for their mental, cognitive, and physical well-being and can potentially reduce the cost for special need education as a result of increasing the productivity of teachers and caregivers.
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Collaborative Research: III: Small: Efficient and Robust Multi-model Data Analytics for Edge Computing
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    2311596
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  • 财政年份:
    2023
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SHF: Small: A General Framework for Accelerating AI on Resource-Constrained Edge Devices
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Collaborative Research: CCRI: New: Nation-wide Community-based Mobile Edge Sensing and Computing Testbeds
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Collaborative Research: SaTC: CORE: Small: Securing IoT and Edge Devices under Audio Adversarial Attacks
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  • 负责人:
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