Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1115
Title: Fully Automatic Hydroponic Cultivation Growth System
Authors: Thalwatte, A. M.
Ranasinghe, U. G. K. L.P. S.
Sakee, M. F. A.
Ikram, M. M. M.
Mahaadikara, H.
Wellalage, S.
Keywords: fully automated
detection,
image processing
greenhouse
algorithm
hydroponic
Issue Date: 9-Dec-2021
Publisher: 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract: Fully 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.
URI: http://rda.sliit.lk/handle/123456789/1115
ISSN: 978-1-6654-0862-2/21
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Information Technology-Scopes

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