CPS: Synergy: Collaborative Research: Towards Dependable Self-Powered Things for the IoT

将物联网（IoT）扩展到数十亿甚至可能数万亿的“事物”需要网络物理系统（CPS）的科学，技术和工程方面的变革性进步，而没有比电力问题更紧迫或更具挑战性的了。如果1万亿个物联网网络中的每个设备都有一个电池，可以使用整整五年，那么每天需要更换超过5亿个电池。显然，由于人力资源物流和环境问题，电池供电的物联网在这种规模下是不可行的。需要一种无电池的方法，该方法依赖于使用从物理世界收集的能量来满足功能要求。该项目汇集了材料，设备，电路和系统方面的专家，以寻求在现实环境中部署自供电无线设备以及物联网系统和应用的整体方法。此外，教育和推广活动将有助于为这一相对较新的领域培养劳动力，并具有引领这一领域创新所必需的整体材料到系统的视角。该项目解决的一个关键挑战是，最佳设备操作和能量采集器效率都严重依赖于物理世界动态，因此，静态配置或仅响应瞬时条件的自供电设备不太可能提供许多IoT系统和应用所需的可靠性。为了解决这一基本和关键的挑战，将进行数据收集，以研究影响设备操作和采集器效率的物理世界动态，例如环境条件，电磁干扰和人类行为。这项科学研究将导致动态模型的开发，这些模型将反过来用于开发算法，不仅基于过去和当前的条件，而且还基于对未来条件的预测来动态配置设备和收割机。然后，这些算法将用于动态配置超低功耗设备操作和超高效率能量收集的技术创新，以设计和操作物联网的可靠自供电设备。

Scaling the Internet of Things (IoT) to billions and possibly trillions of "things" requires transformative advances in the science, technology, and engineering of cyber-physical systems (CPS), with none more pressing or challenging than the power problem. Consider that if every device in a 1 trillion IoT network had a battery that lasted for a full five years, over 500 million batteries would need to be changed every day. Clearly, a battery-powered IoT is not feasible at this scale due to both human resource logistics and environmental concerns. There is a need for a batteryless approach that dependably meets functionality requirements using energy harvested from the physical world. This project brings together experts in materials, devices, circuits, and systems to pursue a holistic approach to self-powered wireless devices deployed in real-world environments and IoT systems and applications. In addition, educational and outreach activities will help develop the workforce for this relatively new field with the holistic, materials-to-systems perspective that will be necessary to lead innovation in this space.A critical challenge that this project addresses is that both optimal device operation and energy harvester efficiency are heavily dependent on physical world dynamics, and thus, self-powered devices that are statically configured or that just respond to instantaneous conditions are unlikely to provide the dependability required for many IoT systems and applications. To address this fundamental and critically enabling challenge, data collections will be performed to study the physical world dynamics that impact device operation and harvester efficiency, such as ambient conditions, electromagnetic interference, and human behavior. This scientific study will lead to the development of dynamic models that will, in turn, be used to develop algorithms to dynamically configure devices and harvesters based not only on past and current conditions but also on predictions of future conditions. These algorithms will then be used to dynamically configure technological innovations in ultra-low power device operation and ultra-high efficiency energy harvesting to engineer and operate dependable self-powered things for the IoT.