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 |