Publication:
Path Loss Model for the Bananas and Weeds Environment Based on Grey System Theory

dc.contributor.authorPisit Phokharatkulen_US
dc.contributor.authorSupachai Phaiboonen_US
dc.contributor.otherKasem Bundit Universityen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2022-08-04T08:37:09Z
dc.date.available2022-08-04T08:37:09Z
dc.date.issued2021-01-01en_US
dc.description.abstractThis paper presents a prediction of path loss for wireless sensor network (WSN) deployment in the bananas and weeds environment. The banana plant and weed density affect banana quality and productivity. The WSNs applied to detect the banana plant density and weeds density in the farm. The path loss predicted model derived from received signal strength (RSS) measurements at different distances using grey system theory. Grey system theory has the advantage of needing a little sample data and calculating no characteristic quantity. This model use to predict the banana plant density and weeds density. In addition, the proposed model is compared the traditional model. From the model, it found that the RSSs varied according to the density of banana plants and weeds including the height of bananas.en_US
dc.identifier.citationProgress in Electromagnetics Research Symposium. Vol.2021-November, (2021), 413-418en_US
dc.identifier.doi10.1109/PIERS53385.2021.9694777en_US
dc.identifier.issn19317360en_US
dc.identifier.issn15599450en_US
dc.identifier.other2-s2.0-85126396381en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/76962
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85126396381&origin=inwarden_US
dc.subjectEngineeringen_US
dc.subjectMaterials Scienceen_US
dc.titlePath Loss Model for the Bananas and Weeds Environment Based on Grey System Theoryen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85126396381&origin=inwarden_US

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