NeTS-NOSS: Sensor Systems to Support Context-Aware Applications

需要一种混合个人和环境传感器系统的中间件。目标是在用户的个人/可穿戴设备上运行的应用程序，利用安装在人们通常移动的环境中的传感器网络的增强传感能力。这种协同传感能够极大地增强个人系统，同时允许用户保留对隐私敏感信息的控制。此外，合作可以提高计算能力，并通过要求环境系统做更多的工作来详细说明传感器数据，从而降低应用程序的功耗要求。这项工作以实际应用为指导，将以个人健康传感和测量作为初步应用领域，对这些概念进行验证。例如，激励应用是一个个人活动测量系统，它不仅可以通过测量身体上的力量来测量一个人的活动和运动水平，还可以与健身中心的设备连接，并从运动设备上的设置和传感器（例如心率监测器）获得进一步的数据。软件构件将是中间件，以使构建这些类型的新应用程序更加有效，并且应用程序本身对于传感和计算资源的可用性更加健壮。科学成果将是关联传感系统的技术，以及在用户来来去去的高度动态环境中协调计算的方法。该中间件将在华盛顿大学的产品设计课程中使用，学生将构建和评估混合可穿戴和环境传感器系统。

There is a need for middleware that blends personal and ambient sensor systems. The objective is for applications, running on a user's personal/wearable devices, to take advantage of the enhanced sensing capabilities of sensor networks installed in the environments that people typically move through. This cooperative sensing has the ability to greatly enhance personal systems while allowing users to retain control of privacy-sensitive information. Moreover, cooperation can enhance the computational capabilities and lessen the power requirements of applications by asking the ambient systems to do more of the work of elaborating the sensor data. This work is guided by practical applications and the concepts will be validated using personal health sensing and measurement as the initial application area. For example, the motivating application is a personal activity measurement system that not only measures a person's activities and level of exertion from measuring forces on their body but can also interface to equipment in a fitness center and gain further data from setting and sensors (e.g., heart rate monitors) on exercise equipment. The software artifacts will be middleware to make building these kinds of new applications more efficient and the applications themselves more robust to the availability of sensing and computational resources. The scientific results will be techniques to correlate sensing systems as well as methods for coordinating computations in a highly dynamic environment where users come and go. The middleware will be exercised in product-design courses at the University of Washington where students will build and evaluate hybrid wearable and ambient sensors systems.