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We carry out a structural and algorithmic study of a mobile sensor coverageoptimization problem targeting 2D surfaces embedded in a 3D workspace. Theinvestigated settings model multiple important applications including cameranetwork deployment for surveillance, geological monitoring/survey of 3Dterrains, and UVC-based surface disinfection for the prevention of the spreadof disease agents (e.g., SARS-CoV-2). Under a unified general "sensor coverage"problem, three concrete formulations are examined, focusing on optimizingvisibility, single-best coverage quality, and cumulative quality, respectively.After demonstrating the computational intractability of all these formulations,we describe approximation schemes and mathematical programming models fornear-optimally solving them. The effectiveness of our methods is thoroughlyevaluated under realistic and practical scenarios.

Sensor Placement for Globally Optimal Coverage of 3D-Embedded Surfaces