Current Issue : October - December Volume : 2013 Issue Number : 4 Articles : 4 Articles
To improve the dynamic characteristic of two-axis force sensors, a dynamic compensation method is proposed. The two-axis force\r\nsensor system is assumed to be a first-order system. The operation frequency of the system is expanded by a digital filter with\r\nbackward difference network. To filter high-frequency noises, a low-pass filter is added after the dynamic compensation network. To\r\navoid overcompensation, parameters of the proposed dynamic compensation method are defined by trial and error. Step response\r\nmethods are utilized in dynamic calibration experiments. Compared to experiment data without compensation, the response time\r\nof the dynamic compensated data is reduced by 30%~40%. Experiments results demonstrate the effectiveness of our method....
Combining multiple proximal sensors within a wireless sensor network (WSN)\r\nenhances our capacity to monitor vegetation, compared to using a single sensor or\r\nnon-networked setup. Data from sensors with different spatial and temporal characteristics\r\ncan provide complementary information. For example, point-based sensors such as\r\nmultispectral sensors which monitor at high temporal frequency but, at a single point, can\r\nbe complemented by array-based sensors such as digital cameras which have greater spatial\r\nresolution but may only gather data at infrequent intervals. In this article we describe the\r\nsuccessful deployment of a prototype system for using multiple proximal sensors\r\n(multispectral sensors and digital cameras) for monitoring pastures. We show that there are\r\nmany technical issues involved in such a deployment, and we share insights relevant for\r\nother researchers who may consider using WSNs for an operational deployment for pasture\r\nmonitoring under often difficult environmental conditions. Although the sensors and infrastructure are important, we found that other issues arise and that an end-to-end\r\nworkflow is an essential part of effectively capturing, processing and managing the data\r\nfrom a WSN. Our deployment highlights the importance of testing and ongoing monitoring\r\nof the entire workflow to ensure the quality of data captured. We demonstrate that the\r\ncombination of different sensors enhances our ability to identify sensor problems necessary\r\nto collect accurate data for pasture monitoring....
In this paper, we describe how information obtained from multiple views using\r\na network of cameras can be effectively combined to yield a reliable and fast human\r\nactivity recognition system. First, we present a score-based fusion technique for combining\r\ninformation from multiple cameras that can handle the arbitrary orientation of the subject\r\nwith respect to the cameras and that does not rely on a symmetric deployment of the\r\ncameras. Second, we describe how longer, variable duration, inter-leaved action sequences\r\ncan be recognized in real-time based on multi-camera data that is continuously streaming in.\r\nOur framework does not depend on any particular feature extraction technique, and as a\r\nresult, the proposed system can easily be integrated on top of existing implementations\r\nfor view-specific classifiers and feature descriptors. For implementation and testing of the\r\nproposed system, we have used computationally simple locality-specific motion information\r\nextracted from the spatio-temporal shape of a human silhouette as our feature descriptor.\r\nThis lends itself to an efficient distributed implementation, while maintaining a high frame\r\ncapture rate. We demonstrate the robustness of our algorithms by implementing them on\r\na portable multi-camera, video sensor network testbed and evaluating system performance\r\nunder different camera network configurations....
Timely dissemination of required state information poses a significant challenge\r\nin the design of distributed sensor/actuator network-based control systems. In this paper,\r\ndistance sensitivity properties inherent in many sensor-actuator network-based control\r\nsystems are exploited to establish conditions under which information within a bounded\r\nlocality of each controller closely approximates optimal control based on knowledge of\r\nsystem-wide state information. By doing so, it is shown that optimal control in extremely\r\nlarge-scale distributed control systems can be achieved in O(1) time using information only\r\nwithin a fixed neighborhood around each controller, the size of which depends on the decay\r\ncharacteristics of the actuator influence matrix....
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