A Scheme for Pest-Dense Area Localization With Solar Insecticidal Lamps Internet of Things Under Asymmetric Links

Abstract

The combination of solar insecticidal lamps (SILs) and wireless sensor networks has spawned a green and efficient solution for agricultural pest control, called solar insecticidal lamps Internet of Things (SIL-IoTs). In realistic large-scale SIL-IoTs deployment scenarios, the integrated pest information collected across the network enables effective localization of pest-dense areas. However, the problem of asymmetric links caused by various factors, such as irregular wireless communication range and discharge interference of nodes, is the main obstacle to the deployment of SIL-IoTs. Motivated by this problem, the pest-dense area localization strategy (PALS) based on asymmetric links is proposed. First, the asymmetric nodes in the network are judged by analyzing the one-hop and two-hop information of SIL nodes. Subsequently, the Gabriel graph or relative neighborhood graph planarization algorithm is used to planarize the symmetric links in the network. Then, the quick rejection method and straddle experiment are used to remove the cross sections after planarization. Finally, by counting the number of SIL node discharges and facilitating the left-hand rule, PALS successfully reduces the difference between the calculated and actual pest-dense areas. The experiments showed that PALS achieves an average improvement of 15% and a maximum improvement of up to 42.2% across the four experimental settings, indicating its higher accuracy and robustness compared with the state-of-the-art algorithms.