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 |
Files in This Item:
File | Description | Size | Format | |
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Fully_Automatic_Hydroponic_Cultivation_Growth_System.pdf Until 2050-12-31 | 3.19 MB | Adobe PDF | View/Open Request a copy |
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