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Existing adaptive sampling methods for mobile sensors are poorly suited to scenarios in which the sensor continuously samples as it moves. We discuss why this is the case and suggest some techniques that may help. Next we propose an entirely different approach that uses a colored planar triangulation model and how it can be analysed by using Bayesian inference and MCMC simulation, which we believe better utilizes the path sampling capabilities of some sensors.

Existing adaptive sampling methods for mobile sensors are poorly suited to scenarios in which the sensor continuously samples as it moves. We discuss why this is the case and suggest some techniques that may help. Next we propose an entirely different approach that uses a colored planar triangulation model and how it can be analysed by using Bayesian inference and MCMC simulation, which we believe better utilizes the path sampling capabilities of some sensors.

Andrew McC. Parker discusses the challenges associated with building a canal across the Isthmus.