CRI: CI-EN: Collaborative Research: mResearch: A platform for Reproducible and Extensible Mobile Sensor Big Data Research

CRI：CI-EN：协作研究：mResearch：可复制和可扩展的移动传感器大数据研究平台

• 批准号: 1823070
• 负责人: Emre Ertin
• 金额: $ 22.48万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823070&HistoricalAwards=false
• 关键词: CRI; CI; EN; Collaborative; Research

The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has developed open-source software for smart phones and cloud. Scientists use MD2K software to develop and test algorithms to monitor health, wellness, and work productivity via wearable sensors. The mResearch project is aimed at assisting Computer and Information Science and Engineering (CISE) researchers. The mResearch project will significantly enhance MD2K software and integrate Internet-of-Things (IoT) devices. The enhanced MD2K software will accelerate research in sensors design, mobile computing, privacy, analytics (especially machine learning and deep learning), and visualization. mResearch will enable CISE researchers to easily deploy their contributed software in scientific studies for health, smart homes, and workplace. The resulting discoveries and tools will help individuals improve their health, wellness, and work productivity.MD2K has developed open-source mobile sensor big data software platforms mCerebrum for smartphones and Cerebral Cortex for the cloud. This scalable and generalizable infrastructure is used for collecting, analyzing, and sharing high-frequency, mobile sensor data and associated labels in the context of scientific field studies. In particular, it supports the development and validation of models and algorithms for inferring markers of health, wellness, and productivity, and their associated risk factors. It has already been used at eleven sites across the country to collect over 300 terabytes of mobile sensor data in the field setting from over 2,000 participants. It has resulted in new computational models for the detection of conversation, smoking, eating, craving, stress, and cocaine use. The mResearch project is making five significant infrastructure enhancements to the MD2K infrastructure to assist CISE researchers in mobile sensor development, mobile computing, privacy, analytics, visualization, and participant engagement. First, it will enable data analytic workflow management across multiple layers of the system to enable reproducible and extensible experimentation. Second, it will allow encapsulation of data sources to provide convenient and responsible access to them in data analytic workflows. Third, it will facilitate cloud-assisted complex, real-time analytics for personalizing mobile interventions and improving engagement. Fourth, simulators will be developed with the ability to feed stored data into the platform at various points to enable research on system components and properties such as data compression, transfer and storage, as well as the scalability of data analytics. Finally, Internet-of-Things (IoT) devices and services will be integrated. With these five enhancements, the MD2K software will provide a complete, open, and modularized architecture. It will include all aspects of sensor data collection, data processing algorithms, cloud-based machine learning, and IoT integration. The enhanced MD2K software will facilitate reproducible and extensible CISE research with high-frequency mobile sensor data.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.

移动传感器数据对知识的卓越中心（MD2K）开发了用于智能手机和云的开源软件。科学家使用MD2K软件来开发和测试算法，以通过可穿戴传感器来监测健康，健康和工作生产力。 Mresearch项目旨在协助计算机和信息科学与工程（CISE）研究人员。 Mresearch项目将大大增强MD2K软件并集成了The Internet（IoT）设备。增强的MD2K软件将在传感器设计，移动计算，分析（尤其是机器学习和深度学习）和可视化方面加速研究。 Mresearch将使CISE研究人员能够轻松地将其贡献的软件部署在健康，智能家居和工作场所的科学研究中。由此产生的发现和工具将帮助个人提高其健康，健康和工作生产力。MD2K已为智能手机和云的大脑皮层开发了开源移动传感器大数据软件平台Mcerebrum。在科学领域研究的背景下，这种可扩展且可概括的基础架构用于收集，分析和共享高频，移动传感器数据以及相关标签。特别是，它支持模型和算法的开发和验证，以推断健康，健康和生产力及其相关风险因素。它已经在全国11个地点使用，以收集来自2,000多名参与者的现场设置中的300多个移动传感器数据。它导致了新的计算模型，用于检测对话，吸烟，饮食，渴望，压力和可卡因。 Mresearch项目正在对MD2K基础架构进行五项重要的基础架构增强，以帮助CISE研究人员进行移动传感器开发，移动计算，隐私，分析，可视化和参与者的参与。首先，它将启用跨系统多层的数据分析工作流程管理，以实现可再现和可扩展的实验。其次，它将允许数据源的封装，以在数据分析工作流程中提供方便且负责任的访问权限。第三，它将促进云辅助复杂的实时分析，以个性化移动干预和改善参与度。第四，将开发模拟器，能够在各个点将存储的数据馈送到平台中，以便研究系统组件和属性，例如数据压缩，传输和存储以及数据分析的可扩展性。最后，将集成了图像（IoT）设备和服务。通过这五个增强功能，MD2K软件将提供完整，开放和模块化的体系结构。它将包括传感器数据收集，数据处理算法，基于云的机器学习和物联网集成的所有方面。增强的MD2K软件将通过高频移动传感器数据促进可再现和可扩展的CISE研究。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估标准来评估值得支持的。

项目成果

mORAL: An mHealth Model for Inferring Oral Hygiene Behaviors in-the-wild Using Wrist-worn Inertial Sensors

• DOI: 10.1145/3314388
• 发表时间: 2019-03-01
• 期刊: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
• 作者: Akther, Sayma;Saleheen, Nazir;Kumar, Santosh
• 通讯作者: Kumar, Santosh

Blind Deconvolution Methods for Estimation of Multilayer Tissue Profiles with Ultrawideband Radar

用超宽带雷达估计多层组织轮廓的盲反卷积方法

• DOI: 10.1109/radar.2019.8835631
• 发表时间: 2019
• 期刊: 2019 IEEE Radar Conference
• 作者: Civek, Burak Cevat;Sugavanam, Nithin;Baskar, Siddharth;Ertin, Emre
• 通讯作者: Ertin, Emre