Acquiring medium models for sensing performance estimation

The quality of sensing in practical sensor net- work deployments suffers due to the presence of obstacles in the sensing medium. The obstacles may not be known before deployment and may change over time. This makes it hard to provide any estimate on the reliability of sensor data. Hence, it is of interest to develop methods which enable a sensor network to determine the presence and extent of sensing occlusions. We present one such method based on the use of a range sensor to map the obstacles in the medium. A network architecture to support efficient medium mapping facilities is presented, along with several design choices in the acquisition and update of the medium map data. We also present algorithms to rapidly acquire this data and share it among multiple nodes. All algorithms presented are implemented on prototype hardware con- sisting of an actuated laser and an embedded processing platform.

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