Smart agriculture management system for rice disease detection and fertilizer
This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022.
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| Idioma: | English |
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Brac University
2024
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| Acceso en liña: | http://hdl.handle.net/10361/24005 |
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10361-240052024-10-23T21:01:19Z Smart agriculture management system for rice disease detection and fertilizer Faiyaz, Md Abrar Hossen Mohsin, Maliha Binte Nahreen, Nayeema Oaishi, Sofia Ahmed Mohsin, Abu S.M. Sakib, Taiyeb Hasan Department of Electrical and Electronic Engineering, Brac University UAV Fertilizer Rice-disease Disease-detection Brown-spot Rice--Diseases and pests. Agricultural innovations. Fertilizers. This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022. Cataloged from PDF version of final year design project. Includes bibliographical references (page 67-68). Bangladesh has the ninth-highest population density in the world. Despite significant advancements to meet the expanding food-demand, the nation still relies heavily on agriculture, with unpredictable crop yields and insufficient infrastructure for farming as a result of many sectors adhering to outdated human-centric agricultural practices. A more sustainable agricultural-production could result from the use of smart-farming. Unmanned aerial vehicles (UAVs), a widely used smart-farming technology, are revolutionizing traditional farming methods. Knowing the capabilities of various systems enables the appropriate choice to be made in advance of a particular task, and each task necessitates the appropriate choice of the flight system. In this project, a UAV collected and uploaded images and soil-data from a paddy-field, including NPK, moisture, temperature, and humidity. On this dataset, we conducted an analysis to determine the field's fertility and give fertilizer recommendations. To identify rice diseases like brown spot, we also employed ResNet152V2 model, a deep learning image-based disease detection system. we have used our dataset (images taken with the UAV camera) for training and testing and we have used Google Colab for coding. Although the algorithm was fairly precise, the UAV model was quite unstable and the dataset was relatively tiny, necessitating a significant amount of work in this area in the future. Md Abrar Hossen Faiyaz Maliha Binte Mohsin Nayeema Nahreen Sofia Ahmed Oaishi B. Electrical and Electronic Engineering 2024-09-08T06:24:17Z 2024-09-08T06:24:17Z ©2022 2022-11 Project report ID 18321038 ID 18321010 ID 18321005 ID 18321029 http://hdl.handle.net/10361/24005 en Brac University project reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 123 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
UAV Fertilizer Rice-disease Disease-detection Brown-spot Rice--Diseases and pests. Agricultural innovations. Fertilizers. |
| spellingShingle |
UAV Fertilizer Rice-disease Disease-detection Brown-spot Rice--Diseases and pests. Agricultural innovations. Fertilizers. Faiyaz, Md Abrar Hossen Mohsin, Maliha Binte Nahreen, Nayeema Oaishi, Sofia Ahmed Smart agriculture management system for rice disease detection and fertilizer |
| description |
This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022. |
| author2 |
Mohsin, Abu S.M. |
| author_facet |
Mohsin, Abu S.M. Faiyaz, Md Abrar Hossen Mohsin, Maliha Binte Nahreen, Nayeema Oaishi, Sofia Ahmed |
| format |
Project report |
| author |
Faiyaz, Md Abrar Hossen Mohsin, Maliha Binte Nahreen, Nayeema Oaishi, Sofia Ahmed |
| author_sort |
Faiyaz, Md Abrar Hossen |
| title |
Smart agriculture management system for rice disease detection and fertilizer |
| title_short |
Smart agriculture management system for rice disease detection and fertilizer |
| title_full |
Smart agriculture management system for rice disease detection and fertilizer |
| title_fullStr |
Smart agriculture management system for rice disease detection and fertilizer |
| title_full_unstemmed |
Smart agriculture management system for rice disease detection and fertilizer |
| title_sort |
smart agriculture management system for rice disease detection and fertilizer |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/24005 |
| work_keys_str_mv |
AT faiyazmdabrarhossen smartagriculturemanagementsystemforricediseasedetectionandfertilizer AT mohsinmalihabinte smartagriculturemanagementsystemforricediseasedetectionandfertilizer AT nahreennayeema smartagriculturemanagementsystemforricediseasedetectionandfertilizer AT oaishisofiaahmed smartagriculturemanagementsystemforricediseasedetectionandfertilizer |
| _version_ |
1814307514294992896 |