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

要将物联网(IoT)扩展到数十亿甚至数万亿的物联网，需要在网络物理系统(CP)的科学、技术和工程方面取得革命性的进步，而最紧迫和最具挑战性的就是电源问题。考虑到，如果1万亿物联网网络中的每台设备都有一块电池可持续整整五年，那么每天需要更换的电池将超过5亿块。显然，由于人力资源物流和环境方面的考虑，电池供电的物联网在这种规模下是不可行的。需要一种使用从物理世界获取的能量可靠地满足功能要求的无电池方法。该项目汇集了材料、设备、电路和系统方面的专家，以寻求在现实环境以及物联网系统和应用中部署的自供电无线设备的整体方法。此外，教育和推广活动将帮助培养这一相对较新的领域的劳动力，从整体、材料到系统的角度来引领该领域的创新。该项目解决的一个关键挑战是，最佳设备操作和能量收集器效率都严重依赖于物理世界的动态，因此，静态配置或仅对瞬时条件做出响应的自供电设备不太可能提供许多物联网系统和应用所需的可靠性。为了解决这一根本和关键的挑战，将进行数据收集，以研究影响设备操作和收割机效率的物理世界动态，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，这些模型将被用于开发算法，不仅根据过去和当前的条件，而且根据对未来条件的预测，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能量收集方面的技术创新，为物联网设计和操作物联网可靠的自供电设备。

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.