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dc.contributor.authorCharaa, Daouia-
dc.contributor.authorOuled Haddar, Maria-
dc.date.accessioned2024-10-31T10:05:26Z-
dc.date.available2024-10-31T10:05:26Z-
dc.date.issued2024-
dc.identifier.urihttps://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/8823-
dc.description.abstractPlant 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.isoenEN_en
dc.publisheruniversité GhardaiaEN_en
dc.subjectPlant diseases;Economic losses; Sustainable agriculture; AGROBOT; Raspberry Pi5EN_en
dc.subjectMaladies des plantes ;Pertes économiques ;Agriculture durable ;AGROBOT; Raspberry Pi 5;EN_en
dc.titleAn Automated Robotic System For Diagnosing And Treating Plant Diseases Using Deep LearningEN_en
dc.typeThesisEN_en
Appears in Collections:Mémoires de Master

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