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.
