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Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Charaa, Daouia | - |
dc.contributor.author | Ouled Haddar, Maria | - |
dc.date.accessioned | 2024-10-31T10:05:26Z | - |
dc.date.available | 2024-10-31T10:05:26Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/8823 | - |
dc.description.abstract | Plant diseases cause significant economic losses and pose a threat to sustainable agriculture. Farmers face problems related to crop infections and also during the spraying of pesticides, which can be toxic to them. To address these issues, we have developed an idea called "AGROBOT." The main goal of our idea is to detect the infection rate in plants and provide the appropriate pesticides for the disease. To achieve this, we devised an action plan to scale up our idea by creating a mobile vehicle that can move across a field, identify infected plants, take pictures of them using a camera, and send these images to a control processor (Raspberry Pi 5). The processor analyzes the problem based on the stored data and applies the appropriate pesticides to the farm. | EN_en |
dc.language.iso | en | EN_en |
dc.publisher | université Ghardaia | EN_en |
dc.subject | Plant diseases;Economic losses; Sustainable agriculture; AGROBOT; Raspberry Pi5 | EN_en |
dc.subject | Maladies des plantes ;Pertes économiques ;Agriculture durable ;AGROBOT; Raspberry Pi 5; | EN_en |
dc.title | An Automated Robotic System For Diagnosing And Treating Plant Diseases Using Deep Learning | EN_en |
dc.type | Thesis | EN_en |
Appears in Collections: | Mémoires de Master |
Files in This Item:
File | Description | Size | Format | |
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Final Version Master Thesis CHRAA-OULEDHADDAR - Maria Ouled Haddar (1).pdf | 4.35 MB | Adobe PDF | View/Open |
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