In directional sensor networks research, target event detection is currently an active research area, with applications in underwater\ntarget monitoring, forest fire warnings, border areas, and other important activities. Previous studies have often discussed target\ncoverage in two-dimensional sensor networks, but these studies cannot be extensively applied to three-dimensional networks.\nAdditionally, most of the previous target coverage detection models are based on a circular or omnidirectional sensing model.\nMore importantly, if the directional sensor network does not design a better coverage algorithm in the coverage-monitoring\nprocess, its nodesâ?? energy consumption will increase and the network lifetime will be significantly shortened. With the objective\nof addressing three-dimensional target coverage in applications, this study proposes a dynamic adjustment optimisation\nalgorithm for three-dimensional directional sensor networks based on a spherical sector coverage model, which improves the\nlifetime and coverage ratio of the network. First, we redefine the directional nodesâ?? sensing model and use the three-dimensional\nVoronoi method to divide the regions where the nodes are located. Then, we introduce a correlation force between the target\nand the sensor node to optimise the algorithmâ??s coverage mechanism, so that the sensor node can accurately move to the\nspecified position for target coverage. Finally, by verifying the feasibility and accuracy of the proposed algorithm, the simulation\nexperiments demonstrate that the proposed algorithm can effectively improve the network coverage and node utilisation.
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