Target-Barrier Coverage Improvement in an Insecticidal Lamps Internet of UAVs
Pengju Si, Zhumu Fu, Lei Shu, Yuli Yang, Kai Huang, Ye Liu
Abstract
Insecticidal lamps Internet of things (ILs-IoTs) has attracted considerable attention for its applications in pest control to achieve green agriculture. However, ILs-IoTs cannot provide a perfect solution to the migratory pest outbreak if the ILs are fixed on the ground. In this paper, we embed ILs in unmanned aerial vehicles (UAVs) as the mobile nodes, which can be rapidly landed on the ground to kill agricultural pests, and the Internet of UAVs (IoUAV) is introduced to extend the application of ILs-IoTs. To take full advantage of the IL-IoUAVs, we formulate the problem of target-barrier coverage and investigate how to minimise the number of IL-UAVs in constructing the target-barrier coverage. The <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>-target-barrier coverage is introduced utilizing the realistic probabilistic sensing model of IL-UAVs, based on which we study how to guarantee the <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>-target-barrier coverage while minimizing the number of IL-UAVs needed. The problem is solved by an optimal algorithm to merge multiple target-barriers. Evaluation results show the efficiency of our designed algorithms for constructing <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>-target-barrier coverage.