Planning Grant: Engineering Research Center for Edge Intelligence

工程研究中心规划奖助金(ERC)竞赛是作为ERC计划的试点征集活动进行的。规划拨款并不是整个ERC竞赛的一部分，而是为了在团队之间建立能力，以规划汇聚的、中心规模的工程研究。这笔拨款将为拟议的边缘情报中心提供规划资源。拟建的中心将开发由物联网(IoT)系统驱动的数据科学新技术。物联网系统与现实世界交互：工业、医疗保健、农业等。物联网系统通过收集和处理来自现实世界的数据，有望为这些和其他应用领域带来实质性好处。然而，需要新的方法来利用物联网系统的潜力。物联网设备必须在电力和通信方面都有限制。这些因素意味着，这些智能系统的关键方面必须体现在大型数据中心之外，在互联网的边缘，靠近数据的创建和使用地点。这项计划拨款有三个目标。规划拨款工作将确定一个完整的中心团队，包括成员机构研究人员、多样性和包容性协调员、劳动力发展协调员和创业协调员。提议团队将在研究人员、行业合作伙伴、企业家和教育工作者中确定广泛的利益相关者。整个中心团队和利益相关者将为边缘智能中心制定战略计划。边缘智能是三个领域的融合：数据科学、低功耗计算和分布式系统。数据科学和物联网系统通常由非常不同的团队来研究、开发和部署。边缘情报中心的使命将是建立一个由业界和学术界的利益相关者组成的社区，以开发和利用这项新兴技术的能力。该中心的智能方法将基于几个基础：机器学习、统计学、低功率计算、分布式算法。物联网系统广泛应用于制造业、医疗、物流、农业等诸多领域。将机器学习应用于物联网系统可以提供新的定制水平和改进的系统操作。边缘智能中心将在基础、工程和应用方面采取融合的整体研究方法。基本目标包括为带宽和功率有限的分布式计算系统设计的机器学习算法。增量学习算法，可针对其特定环境定制和更新系统。工程目标包括在分布式平台上执行机器学习的分布式系统，包括边缘节点、雾中心和云。低功耗机器学习系统。基于边缘和中心的增量培训的低功耗方法。该奖项反映了NSF的法定使命，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 Planning Grants for Engineering Research Centers (ERC) competition was run as a pilot solicitation within the ERC program. Planning grants are not required as part of the full ERC competition, but intended to build capacity among teams to plan for convergent, center-scale engineering research.This grant will provide planning resources for a proposed Center for Edge Intelligence. The proposed center will develop new techniques for data science driven by Internet-of-Things (IoT) systems. IoT systems interact with the real world: industry, health care, agriculture, etc. IoT systems promise substantial benefits for these and other application areas by gathering and processing data from the real world. However, new approaches are required to harness the potential of IoT systems. IoT devices must operate with limits on both electrical power and communication. These factors mean that key aspects of these intelligent systems must be embodied outside of large data centers, at the edge of the Internet, close to the points at which data are created and used. This planning grant has three goals. The planning grant effort will identify a full center team including member institution researchers, diversity and inclusion coordinators, workforce development coordinators, and entrepreneurship coordinators. The proposing team will identify a broad set of stakeholders among researchers, industrial partners, entrepreneurs, and educators. The full center team and stakeholders will create a strategic plan for the Center for Edge Intelligence.Edge Intelligence is the convergence of three fields: data science, low-power computing, and distributed systems. Data science and IoT systems are typically studied, developed, and deployed by very different groups. The Center for Edge Intelligence's mission will be to build a community of stakeholders across industry and academia to develop and harness the capabilities of this emerging technology. The intellectual approach of the Center will be based on several foundations: machine learning, statistics, low-power computing, distributed algorithms. Internet-of-Things systems are widely used in manufacturing, health care, logistics, agriculture, and many other areas. Machine learning applied to IoT systems can provide new levels of customization and improved system operation. The Center for Edge Intelligence will pursue a convergent, holistic research approach in foundations, engineering, and applications. Foundational goals include machine learning algorithms designed for distributed computing systems with limited bandwidth and power. Incremental learning algorithms to customize and update systems for their particular environment. Engineering goals include distributed systems that perform machine learning on distributed platforms, including edge nodes, fog hubs, and the cloud. Low-power machine learning systems. Low-power approaches to edge- and hub-based incremental training. Applications include manufacturing, health care and wellness, agriculture, transportation and logistics.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.