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

移动传感器数据到知识卓越中心(MD2K)开发了用于智能手机和云的开源软件。科学家使用MD2K软件开发和测试算法，通过可穿戴传感器监控健康、健康和工作效率。MResearch项目旨在帮助计算机和信息科学与工程(CEISE)的研究人员。MResearch项目将显著增强MD2K软件并集成物联网(IoT)设备。增强的MD2K软件将加速传感器设计、移动计算、隐私、分析(特别是机器学习和深度学习)和可视化方面的研究。MResearch将使CISE研究人员能够轻松地在健康、智能家居和工作场所的科学研究中部署他们贡献的软件。由此产生的发现和工具将帮助个人提高健康、健康和工作效率。MD2K开发了用于智能手机的开源移动传感器大数据软件平台mCerebrum和用于云的大脑皮质。这种可扩展和可推广的基础设施用于在科学实地研究的背景下收集、分析和共享高频移动传感器数据和相关标签。特别是，它支持开发和验证用于推断健康、健康和生产力的标志及其相关风险因素的模型和算法。它已经在全国11个地点使用，从2000多名参与者那里收集现场超过300TB的移动传感器数据。这导致了新的计算模型，用于检测交谈、吸烟、进食、渴望、压力和可卡因使用。MResearch项目正在对MD2K基础设施进行五项重要的基础设施增强，以帮助CISE研究人员在移动传感器开发、移动计算、隐私、分析、可视化和参与者参与方面提供帮助。首先，它将实现跨系统多层的数据分析工作流管理，以实现可重复和可扩展的实验。其次，它将允许封装数据源，以便在数据分析工作流中提供对它们的方便和负责任的访问。第三，它将促进云辅助的复杂实时分析，以个性化移动干预并提高参与度。第四，将开发能够在不同时间点将存储的数据输入平台的模拟器，以便能够研究系统组件和属性，如数据压缩、传输和存储，以及数据分析的可扩展性。最后，将集成物联网(IoT)设备和服务。通过这五项增强，MD2K软件将提供一个完整的、开放的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方方面面。增强的MD2K软件将促进使用高频移动传感器数据进行可重复和可扩展的CISE研究。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.