ABSTRACT

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).

The sensors and actuators that comprise the Internet of Things (IoT) must be physically deployed in-situ to enable new applications. These locations are often difficult or expensive to access, such as throughout a large farm for precision agriculture or within an operating factory. Ensuring the IoT devices are useful and productive long after they are deployed reduces their overall cost and increases their utility. However, many computing devices today are designed with short, fixed lifetimes, and hardware advances continuously render old devices obsolete. This project proposes the necessary developments to ensure deployed IoT devices remain usable, efficient, and secure decades after their initial commissioning. The result will be new self-powered energy-harvesting IoT devices that can adapt to changing environments, new application requirements, and updated security requirements without being removed and replaced. Enabling this are several foundational advancements, including (i) fine-grained hardware and compiler enforced software modularity that enables energy-efficient software updates, (ii) memory-efficient reinforcement learning algorithms for long-term energy prediction and management, and (iii) transparent application offloading to support future software running on already deployed IoT device hardware. Ultimately, this will equip IoT devices with lifespans similar to the infrastructure they are attached to.

Pursuing data-driven approaches to reduce energy use and greenhouse gas production is essential for combating climate change. This project will develop long-lasting and scalable sensors to provide actionable data over multi-decade lifetimes. Ensuring long operational lifetimes will help avoid exacerbating a growing e-waste problem from billions of otherwise disposable IoT devices. The techniques from this project will be incorporated into graduate and undergraduate courses, training new engineers who understand the intersection of IoT, cross-disciplinary applications, and ethics. Underrepresented minority graduate students and first-year undergraduates will collaborate on this project to develop new fundamental scientific techniques and learn the connections between technology, the built environment, and the associated stakeholders. The outputs of this work, both teaching and research, will be open sourced and disseminated broadly.

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.

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