IRES Track I: International Research Experience for Students on Non-Volatile Processor Based Self-Powered Embedded Systems

该项目的目标是为美国学生提供与中国未来物联网（IoT）中的无电池嵌入式系统相关的宝贵研究经验，中国拥有世界上最大的电子产业和市场之一。该项目每年将在全国范围内选择五（5）名研究生和两（2）名本科生，并支持他们在八（8）周内访问清华大学。物联网的愿景是将小型计算机嵌入到我们日常生活中的物体中，以改善我们的经济和社会福祉。据估计，到2020年，物联网（IoT）将由近500亿个对象组成。然而，最大的挑战之一是如何为数十亿嵌入式设备供电，因为电池需要频繁充电，并带来健康和环境问题。在这个项目中，学生们将与清华大学的知名研究小组合作，开发未来的物联网传感器，这些传感器可以对从周围环境来源收集的能量做出反应，例如太阳能，射频能量，动能和热能。由于环境能源本质上是间歇性的，学生将对纳米级器件，电路，系统和软件进行研究，以实现可以使用间歇性能源供应的计算机系统。这些系统将大大提高我们收集数据的能力，同时降低维护成本。潜在的应用包括智能医疗、智能建筑和基础设施监测、智能环境监测等，该IRES项目不仅将为美国学生提供在中国最好的工程研究型大学之一工作的机会，还将使他们充分沉浸在国外环境中，并在与全球团队合作中提高他们的才能。该项目包括精心规划的征聘、准备、辅导和旅行后活动。建议的研究目标在纳米级的器件，电路，系统和软件问题，在无电池的嵌入式系统，需要迫切解决。第一个项目旨在为纳米级存储设备开发快速，节能和统一的写入操作，这对于容忍收集能量的不稳定性至关重要。该项目解决了NVP与外部易失性外围设备交互时的基本不一致问题，这是NVP广泛应用的最紧迫的障碍之一。第二个项目解决了无电池设备收集数据并与外部设备通信时的基本不一致问题。该项目旨在为运行在非易失性物联网平台上的个人紫外线（UV）暴露模式识别系统开发高效准确的二值化神经网络，该系统可以推广到许多其他应用。 第三个项目旨在开发高效准确的人工智能，用于在无电池物联网平台上运行的个人紫外线（UV）暴露模式识别系统，该系统可以推广到许多其他应用。可以预见的是，通过与清华大学和北京未来芯片创新中心的密切互动，这些项目所取得的突破将对未来的物联网市场产生直接影响。该项目将使美国学生能够与清华大学的导师合作，对实现无电池嵌入式系统进行高质量的研究。这些经历使美国学生在职业生涯的关键早期阶段接触到国际研究界。希望通过参加这个项目，美国学生能够在嵌入式计算机系统的研究、中国文化以及在国际环境中的表演和合作方面获得丰富的经验。经验也将通过个人社交媒体分享给更广泛的社区，如Facebook，Twitter和Youtube，基于Web2.0的论坛，精心整合的活动，如本科生，少数民族和代表性不足的群体的研究，以及为当地K-12所学校。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.

The objective of this project is to provide U.S. students with valuable research experience related to battery-less embedded systems in future Internet of Things (IoT) in China, which has one of the world's largest electronic industry and market. The project will select five (5) graduate students and two (2) undergraduate students nation-wide each year and support them to visit Tsinghua University (THU) over a period of eight (8) weeks. The vision of IoT is to embed small computers into objects around our daily life to improve our economy and societal well-being. It is estimated that the Internet of Things (IoT) will consist of almost 50 billion objects by 2020. However, one of the biggest challenges is how to power these billions of embedded devices since batteries need frequent recharging and impose health and environmental concerns. In this project, the students will work with renowned research groups at THU to develop future IoT sensors that can reply on energy harvested from ambient environment sources, such as solar energy, radio frequency energy, kinetic energy, and thermal energy. Since ambient energy is intrinsically intermittent, the students will conduct research on nano-scale device, circuits, system, and software to realize computer systems that can work with intermittent energy supply. Such systems will dramatically improve our capability of collecting data while reducing the maintenance costs. Potential applications include smart healthcare, smart building and infrastructure monitoring, smart environmental monitoring, etc. This IRES project will not only offer U.S. students an opportunity to work in one of the best engineering research universities in China, but also fully immerse them in a foreign environment and improve their talents in working with a global team. The project contains well-planned recruitment, preparation, mentoring and post-trip activities. The proposed research targets at nano-scale device, circuits, system, and software issues in battery-less embedded systems that need to be addressed urgently. The first project aims to develop fast, energy efficient, and uniform write operations for nano-scale memory device, which is critical to tolerate intermittency of harvested energy. The project addresses a fundamental inconsistency issue when the NVP is interacting with external volatile peripheral devices, which is one of the most imminent roadblocks towards wide application of NVPs. The second project addresses a fundamental inconsistency issue when the battery-less device is collecting data and communicating with external devices. The project aims to develop efficient and accurate binarized neural network for individual ultraviolet (UV) exposure pattern recognition system running on nonvolatile IoT platform, which could be generalized to many other applications. The third project aims to develop efficient and accurate artificial intelligence for individual ultraviolet (UV) exposure pattern recognition system running on battery-less IoT platform, which could be generalized to many other applications. It can be anticipated that with the close interaction with THU and the Beijing Innovation Center for Future Chips, the breakthroughs made from these projects can have a direct impact on future IoT market.The project will enable U.S. students to conduct high-quality research on realizing battery-less embedded systems, in collaboration with their faculty mentors in THU. Such experiences expose U.S. students to the international research community at a critical early stage in their careers. It is expected that through participating in this program, U.S. students will gain extensive experience on theresearch of embedded computer systems, on the culture of China, and on performing and collaborating in an international environment in general. The experience will also be shared to the broader community through the personal social media such as Facebook, Twitter, and Youtube, Web2.0 based forum, carefully integrated activities such as research for undergraduate students, minorities and underrepresented groups, as well as outreach events for local K-12 schools.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.