ion to application users supported by efficient and robust optimization techniques. In this paper, we propose, MiSense, a service-oriented component-based middleware layer in order to support distributed sensor applications with various performance requirements. MiSense reduces complexity by imposing a structure on top of the component model in the form of composability restrictions and by offe...

We present a Sensor-Network Asynchronous Processor (SNAP), which we have designed to be both a processor core for a sensor-network node and a component of a chip multiprocessor, the Network on a Chip (NoC), which will execute a novel sensor-network simulator. We discuss the advantages of using the same processor for nodes in physical and simulated sensor networks. We describe the attributes tha...

We describe a sensor fusion algorithm based on a set of simple assumptions about the relationship among the sensors. Under these assumptions we estimate the common signal in each sensor, and the optimal fusion is then approximated by a weighted sum of the common component in each sensor output at each pixel. We then examine a variety of techniques to map the sensor signals onto perceptual dimen...

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a modelbased approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component an...

We describe a sensor fusion algorithm based on a set of simple assumptions about the relationship among the sensors. Under these assumptions we estimate the common signal in each sensor, and the optimal fusion is then approximated by a weighted sum of the common component in each sensor output at each pixel. We then examine a variety of techniques to map the sensor signals onto perceptual dimen...