Modeling Computational, Sensing, and Actuation Surfaces

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Recent years have seen the emergence of many efforts to embed computing resources in everyday environments. These efforts have ranged from the use of wireless sensor networks, to wired ubiquitous computing environments in homes and commercial installations. A promising culmination of these directions is that of general purpose flexible surfaces, with large numbers of computational, sensing, and actuation elements embedded in them. Thin and flexible sheets of general purpose active materials could find use in a variety of commercial and household applications. These materials with embedded computation, sensing, and actuation capabilities, may be deployed cheaply over large surfaces, for both the interiors and exteriors of buildings, automobiles, marine vessels (e.g., as a hull lining), and aerospace applications. Such active or computational surfaces will take advantage of their large contiguous spatial extents, and the ability to actuate these surfaces. Such an active material with embedded actuators might be used in building structures that self-repair, or adapt to weather conditions.

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... Progress in device technologies, coupled with reduction in costs, is enabling new classes of applications, such as sensor networks, and large-area surfaces with embedded computation, sensing and actuation capabilities [13]. Such flexible substrates may contain 100's or 1000's of low power microcontrollers embedded per m 2 , with power distribution and communication fibers, and actuation capabilities in the form of shape-memoryalloys embedded in the substrate [14] . These emerging technologies pose new CAD challenges in much the same way that the burgeoning portable computing device market caused increased attention to power management techniques and algo- rithms. ...
... Each sample is processed (filtered), and this processing is largely independent of the processing of other sam- ples. In a system with multiple spatially distributed processing devices, the beamforming application may be partitioned such that each filter operation for a given sensor is mapped to one processing device (henceforth referred to as a slave node), and the filtered samples may be communicated to one device (henceforth, master node) to perform a final collation step.Fig- ure 1 illustrates the logical and a possible physical organization for an integrated computational, sensing and actuation surface [14] used to perform beamforming. ...
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