Bio-inspired Fiber-Optics System based on Crayfish Escape Response for Ultrafast Adaptive Sensing

由于在动态环境中需要大量的资源来保持传感精度，传感器系统面临着显著的传输带宽、能量和数据存储限制。当传感器高度移动或传感器位置恶劣时，这种情况会加剧，因为很难手动重新配置传感器以适应环境中的任何动态。当前的传感器设计要么是非自适应的，要么需要大量的存储资源，因此，只有一小部分数据能够以足够的质量水平传输，从而对应用程序有用。如果传感器系统能够智能地适应快速变化的环境，那么以前收集的数据信息可以用于即时指导传感器配置和数据选择，而无需离线存储和处理数据。该项目是一种新的神经启发方法，可以实现实时自适应传感，从而提高传感器系统的整体带宽使用、功率效率和传感器精度。准确的实时自适应传感可以显著减少自然灾害和人为灾害造成的财产损失。它还可以通过识别故意恐怖行为来提高国家安全，并为安全应用提供智能实时大带宽自适应传感系统。这项工作的教育影响来自于它的多学科基础，拓宽了学生的视野，鼓励他们跳出框框思考。本项目借鉴了小龙虾尾巴翻转逃逸响应和生理电路中的尖峰时序依赖的可塑性，旨在利用光子学实现它。本项目的重点是设计和开发一种能够实时学习和适应快速变化的光子神经小龙虾电路，并将光子小龙虾电路集成到传感器系统中进行实时自适应控制。这是一项跨学科的集成设备和系统设计研究，涉及从神经形态处理的角度进行基础研究。该项目旨在利用光子器件中的物理过程，解决动态复杂现代传感器系统的基本实时自适应控制问题。这种新颖的方法是一种神经启发的方法，通过消除计算瓶颈，提供实时自适应传感所需的高保真度和大带宽处理能力来解决问题。

Sensor systems are facing significant transmission bandwidth, energy, and data storage constraints caused by the vast amount of resources needed to maintain sensing accuracy in a dynamic environment. This situation is exacerbated when the sensor is highly mobile or when the sensor site is hostile, as it is very difficult to manually reconfigure a sensor to accommodate any dynamics in the environment. Current sensor designs are either non-adaptive or require large storage resources and, as a result, only a small fraction of the data be conveyed at a sufficient quality level to be useful for applications. If it is possible for the sensor system to intelligently adapt to the rapidly changing environment, then information from previously collected data can be used to instantaneously guide sensor configuration and the selection of data without the need to store and process the data offline. This project is a new neural-inspired approach to enable real-time adaptive sensing, such that the overall bandwidth usage, power efficiency, and sensor accuracy of the sensor system will be improved. Accurate real-time adaptive sensing can significantly reduce property damage due to natural and manmade disasters. It can also improve national security by identifying intentional terrorist actions, as well as providing an intelligent real-time large bandwidth adaptive sensing system for security applications. The educational impact of this work comes from its multi-disciplinary foundation, broadening students' views and encouraging them to think outside the box.This project borrows the Crayfish Tail-flip Escape Response and the Spike Timing Dependent Plasticity from physiological circuitry, and aims to implement it with photonics. The focus of this project is to design and develop a photonic neural crayfish circuit, capable of real-time learning and adapting to rapid changes, and to incorporate the photonic crayfish circuit for real-time adaptive control in a sensor system. This initiative is an interdisciplinary integrated device and systems design study involving basic research from the standpoint of neuromorphic processing. The project aims to exploit physical processes in photonic devices, and to solve the problem of fundamental real-time adaptive control in a dynamic and complex modern sensor system. This fundamentally novel approach is a neural-inspired way to solve the problem by eliminating the computing bottleneck and providing high fidelities and large bandwidth processing ability that is needed for real-time adaptive sensing.