Smart Farming: Enhancing Urban Agriculture Through Predictive Analytics and Resource Optimization

Smart Farming: Enhancing Urban Agriculture Through Predictive Analytics and Resource Optimization

Optimal agricultural methods need precise crop health and ecological strain monitoring. This study proposes a novel data science strategy to improve crop health prediction and stress assessment. ResXceNet-HBA is a cutting-edge classification model that uses ResNet blocks, Xception modules with Adapt...

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Bibliographic Details
Main Authors: Eman Ali Aldhahri, Abdulwahab Ali Almazroi, Monagi Hassan Alkinani, Nasir Ayub, Elham Abdullah Alghamdi, Nourah Fahad Janbi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Crop health monitoring
environmental stress assessment
ResXceNet-HBA
data imputation
feature selection
precision agriculture
Online Access:https://ieeexplore.ieee.org/document/10843189/
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https://ieeexplore.ieee.org/document/10843189/

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