4.7 Article

Target-Barrier Coverage Improvement in an Insecticidal Lamps Internet of UAVs

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 71, Issue 4, Pages 4373-4382

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2022.3148175

Keywords

Internet of Things (IoT); insecticidal lamp (IL); probabilistic sensing model; target-barrier coverage; unmanned aerial vehicle (UAV)

Funding

  1. National Natural Science Foundation of China [62072248]
  2. Natural Science Foundation of Henan Province [202300410149]
  3. Key Scientific Research Projects of Universities in Henan Province [20A120008]
  4. Jiangsu Agricultural Science and Technology Innovation Fund [CX(21)3060]

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This paper introduces the use of insecticidal lamps embedded in unmanned aerial vehicles for pest control in agriculture, and the application of Internet of UAVs to extend its usage. The problem of target-barrier coverage is formulated to minimize the number of IL-UAVs needed. A solution is proposed based on the introduction of epsilon-target-barrier coverage.
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 epsilon-target-barrier coverage is introduced utilizing the realistic probabilistic sensing model of IL-UAVs, based on which we study how to guarantee the epsilon-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 epsilon-target-barrier coverage.

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