Programmable Sensing Composites

大多数人造物体仍处于模拟时代：很少有人造物体包含传感器，更少的是在传感器旁边有嵌入式计算。这种情况很像世纪之交的模拟摄像机。在物体制造过程和制造结构中嵌入数字计算和传感可以实现现场计量，在实际使用过程中进行现场分析，以及来自每个单个物理对象的有价值的统计数据。这种对物体内部和使用的物理历史进行实时处理的数字摘要，可能会使我们在设计、制造和使用物理物体的方式上发生根本性的转变。物理对象内部条件的合成数字摘要可以实现与无处不在的数码相机实现的计算机视觉数据驱动方法的革命相同规模或更大的革命。因为它们将使嵌入传感与本地原位信号处理相结合，传感器增强制造工艺和传感器增强制造对象可以实现一场革命，对社会（更适合用途的更好的产品）和环境（用更少的废物制造的产品）具有潜在的深远利益。嵌入式传感和计算还可以使未来的材料属性在计算的控制下适应物体的使用模式。嵌入式感知和计算设备以及该项目的相关研究成果和方法可以让我们第一次在物理对象的生命周期内自主监控这些现象，基于整个产品量的实时监控数据，执行全新形式的结构完整性分析，并实现新的结构能力和商业产品能力，比如感觉压力驱动的适应性召回和数据驱动的产品定制。在这个项目中，我们的目标是研究将计算和传感嵌入到增材制造对象中的新基本方法，并使用传感器数据进行原位分析，以改进其材料配方、设计和制造。在实际使用过程中，来自连续物内计量的数据可以为制造高价值物品提供全新的、潜在的颠覆性方法。如今，与其他工程领域不同的是，来自实际使用的大量数据正在彻底改变计算机视觉和语音识别等任务，而制造的对象在很大程度上仍然没有仪器化，数据贫乏，并且错过了数据驱动的使用信息设计、材料配方和制造的机会。

Most man-made objects are still in the analog era: Few man-made physical objects contain sensors and fewer still have any embedded computation alongside sensors. This situation is much like analog cameras at the turn of the century. Embedding digital computation alongside sensing in object fabrication processes and in fabricated structures could enable in situ metrology, in situ analysis during real-world use, and valuable statistics from every individual physical object. Such in-situ-processed digital summaries of the physical histories of internals and usage of objects could enable a fundamental shift in how we design, fabricate, and use physical objects.Synthesized digital summaries of the internal conditions within physical objects could enable a revolution at the same scale or greater than the revolution in data-driven methods for computer vision enabled by ubiquitous digital cameras. Because they will enable embedding sensing combined with local in situ signal processing, sensor-augmented fabrication processes and sensor-augmented fabricated objects could enable a revolution with potential far-reaching benefits to society (better products that are more fit for purpose) and the environment (products manufactured with less waste). Embedded sensing and computation could also enable a future where materials properties adapt, under control of computation, to the modes of usage of objects. Embeddable sense-and-compute devices and the associated research results and methods from this project could allow us, for the first time, to monitor those phenomena autonomously over a physical object's lifetime, to perform fundamentally new forms of structural integrity analysis based on real-time data monitored throughout the volume of products, and to enable new structural capabilities and commercial product capabilities, such as sensed-stress-driven adaptive recalls and data-driven product customization.Our goal in this project is to investigate new fundamental methods for embedding computation and sensing into additively-manufactured objects and to use sensor data, analyzed in situ, to improve their materials formulation, design, and manufacturing. Data from continuous in-object metrology during real-world use could enable fundamentally-new and potentially-disruptive methods for manufacturing high-value items. Today, unlike in other areas of engineering, where large amounts of data from real-world use are revolutionizing tasks such as computer vision and speech recognition, manufactured objects are still largely un-instrumented, data-poor, and missing out on opportunities for data-driven usage-informed design, materials formulation, and manufacturing.