Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1115
Full metadata record
DC FieldValueLanguage
dc.contributor.authorThalwatte, A. M.-
dc.contributor.authorRanasinghe, U. G. K. L.P. S.-
dc.contributor.authorSakee, M. F. A.-
dc.contributor.authorIkram, M. M. M.-
dc.contributor.authorMahaadikara, H.-
dc.contributor.authorWellalage, S.-
dc.date.accessioned2022-02-14T06:08:06Z-
dc.date.available2022-02-14T06:08:06Z-
dc.date.issued2021-12-09-
dc.identifier.issn978-1-6654-0862-2/21-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1115-
dc.description.abstractFully automated hydroponic system with monitoring and controlling components. This technique of developing plants can be used to develop plants in the flats the improvement is focused on the deployment of agricultural greenhouses into small-scale stages reworking it into a smart greenhouse. The identification system successfully identified the stage of plants well into the sprout stage and primary stage. Using an automated system and assembling the sensors and actuators considered about four factors which mainly impact the plant growing, light intensity level measurement, Temperature level, water level land co2 supply Also implement a pre-harvest disease detection using image processing and machine learning and alert the user regarding the prevention methods. The system counts infected disease plant and gets percentage then graphically represent a comparison of the yield production. Then forecast yield production. Another important component is to identify the Leaf Disease That Has Affected the Plant, Design database to record all data and provide a report for each disease.en_US
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectfully automateden_US
dc.subjectdetection,en_US
dc.subjectimage processingen_US
dc.subjectgreenhouseen_US
dc.subjectalgorithmen_US
dc.subjecthydroponicen_US
dc.titleFully Automatic Hydroponic Cultivation Growth Systemen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671167en_US
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Information Technology-Scopes

Files in This Item:
File Description SizeFormat 
Fully_Automatic_Hydroponic_Cultivation_Growth_System.pdf
  Until 2050-12-31
3.19 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.