Abstract
To forecast the population of brown planthopper (BPH), a major insect pest of rice in Mekong Delta in Viet Nam, a light trap network is used in the experiments where the BPH trapped density is considered as monitoring called BPH light trap surveillance network (BSNET). There are two problems in order to deploy the BSNET: the number of the light traps and their positions. In this paper, we propose a new approach to optimize the BSNET by determining the number of light traps needed and the position for every light trap node in the surveillance region based on HoneyComb architecture. The experiment results are performed on the Brown Planthoppers surveillance network for Mekong Delta in Viet Nam.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
