A Lightweight Event-Driven Network of Biomimetic Image Sensors

该提案重点介绍了仿生图像传感器在图像传感器网络中的应用。自定义图像传感器将提供简化的视觉表示，并使传感器网络能够解释室内环境中的行为和活动。研究的重点是：1)将传感器观测解析成机器可以理解的一组可识别的动作；2)通过从场景中提取数据而不获取图像并使攻击者难以重建图像来保护隐私；3)提供超低功耗组件和使用低带宽无线链路上的符号信息操作的轻型图像传感器网络。将开发新一代概率检测算法，这些算法对按优先级排序的数据进行操作，以在有限信息的情况下产生快速检测。这些算法将能够在传感器节点上使用的低端微控制器上执行。利用模块化和仿生学方法，PI将设计低功率图像传感器，在传感器级别执行有效的数据提取。他们的设计方法将减少图像传感器所需的计算和通信，并提供一种与传统机器视觉正交的方法。这项拟议的研究需要推进移动摄像头监测室内辅助生活环境的技术。广泛的影响：图像传感器网络是建筑安全、广域安全、国家安全、监测桥梁和公路等土建结构健康、观察自然环境和栖息地、检测严重自然事件的基石。拟议的图像传感器网络将用于辅助生活环境，以监测日常活动中的老年患者。该项目的应用性质是一种有吸引力的方式，可以培训学生，特别是妇女和代表性不足的群体，并激励他们在研究和学术界追求职业生涯。

This proposal focuses on the use of biomimetic image sensors for an image sensor network. Custom image sensors will provide a reduced visual representation and enable the sensor network to interpret behavior and activity in an indoor setting. The research emphasis is to 1) parse out sensor observations into a set of distinguishable actions that can be understood by machines, 2) preserve privacy by extracting data from a scene without acquiring images and by making image reconstruction difficult for perpetrators, 3) provide ultra-low power components and a lightweight sensor network of images that operates using symbolic information over low bandwidth wireless links.Intellectual Merit: The research enables image parsing and interpretation on sensor networks. A new generation of probabilistic detection algorithms that operate on prioritized data to produce fast detections with limited information will be developed. The algorithms will be able to execute on the low-end microcontrollers used on sensor nodes. Using modular and biomimetic approaches, the PIs will design low-power image sensors that will perform efficient data extraction at the sensor level. Their design approach will reduce the computation and communications required by image sensors and provide an orthogonal methodology to conventional machine vision. The proposed research is required to advance the technology of mobile cameras for monitoring indoor assisted-living environments.Broader Impacts: The image sensor network is the building block of building security, wide-area security, national security, monitoring health of civil structures as bridges and highways, observing natural environments and habitats, detecting severe natural events. The proposed image sensor network will be used in an assisted-living environment to monitor aging patients during everyday activity. The applied nature of the project is an attractive way to train students, particularly women and under-represented groups, and to motivate them to pursue careers in research and academia.