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The circular sensing model has been widely used to estimate performance of sensing applications in existing analyses and simulations. While this model provides valuable high-level guidelines, the quantitative results obtained may not reflect the true performance of these applications, due to the sensing irregularity introduced by existence of obstacles in real deployment areas and insufficient hardware calibration. In this paper, the authors design and implement two Sensing Area Modeling (SAM) techniques useful in the real world. They complement each other in the design space. Physical Sensing Area Modeling (P-SAM) provides accurate physical sensing area for individual nodes using controlled or monitored events, while Virtual Sensing Area Modeling (V-SAM) provides continuous sensing similarity between nodes using natural events in an environment.
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