MRI: Development of a Cloud Based Instrument for Heterogeneous Biomedical Body Sensor Systems

该项目开发了一种基于云的仪器，旨在汇总来自一系列人体传感器的数据。该仪器可广泛用于基于可穿戴传感器的医疗应用。支持者调查研究挑战集中在生物医学身体传感器数据采集，传输和分析。云计算和传感器技术的最新进展使得开发一种软件仪器成为可能，该仪器能够集成异构生物医学身体传感器系统的各个方面，从传感器侧的传感器数据预处理、传输和关键事件检测，到数据可靠性评估和增强、数据分析、数据聚合器（通常是智能手机或PC）的传感器控制，最后是数据存储、检索、在云服务器上进行更广泛的分析。与UT-Dallas联合建设，仪器开发包括：Android开发;2. 移动云计算；3. 云基础设施搭建；4. 云API和传感器端APUI；5. 6.可靠性增强；事件检测。其主要组成部分包括：1。支持数据存储/索引分析的云集群；2. 基于开源平台TinyOS的传感器端数据预处理、关键事件检测和传输策略api；3. 手机App开发；和4。用于传感器数据访问和分析算法评估的API。

This project, developing a cloud-based instrument, aims to aggregate data driven from an array of body sensors. The instrument can be used in a wide range of wearable sensor-based medical applications. The proponents investigate research challenges focused on Biomedical Body Sensor Data Acquisition, Transmission, and Analysis. Recent advances in cloud computing and sensor technologies have made feasible to develop a software instrument that is able to integrate all aspects of heterogeneous biomedical body sensor systems, from sensor data preprocessing, transmission, and critical event detection at sensor side, to data reliability evaluation and enhancement, data analysis, sensor control at data aggregator (usually a smart phone or PC), and finally data storage, retrieval, and further extensive analysis at the cloud server. Build jointly with UT-Dallas, the instrument development includes: 1. Android developing; 2. Mobile cloud computing; 3. Cloud infrastructure and set up; 4. Cloud API and Sensor side APUI; 5. Reliability Enhancement, and 6. Event detection. Its major components include: 1. A cloud cluster to support data storage/indexing analysis; 2. APIs for sensor side data preprocessing, critical event detection, and transmission strategies based on open source platform TinyOS; 3. Mobile App development ; and 4. API for sensor data access and analysis algorithms evaluation.