IoT solutions with artificial intelligence technologies for precision agriculture: Definitions, applications, challenges, and opportunities

EEK Senoo, L Anggraini, JA Kumi, BK Luna… - …, 2024 - search.proquest.com
The global agricultural sector confronts significant obstacles such as population growth,
climate change, and natural disasters, which negatively impact food production and pose a …

Advancements in Precision Spraying of Agricultural Robots: A Comprehensive Review

K Lochan, A Khan, I Elsayed, B Suthar… - IEEE …, 2024 - ieeexplore.ieee.org
Through mechanization, automation, and intensification, there has been a substantial
increase in agricultural production over time. The efficiency, reliability, and precision of …

A Comparative Analysis of XGBoost and Neural Network Models for Predicting Some Tomato Fruit Quality Traits from Environmental and Meteorological Data

O M'hamdi, S Takács, G Palotás, R Ilahy, L Helyes… - Plants, 2024 - mdpi.com
The tomato as a raw material for processing is globally important and is pivotal in dietary
and agronomic research due to its nutritional, economic, and health significance. This study …

Classification of non-infected and infected with basal stem rot disease using thermal images and imbalanced data approach

IC Hashim, ARM Shariff, SK Bejo, FM Muharam… - Agronomy, 2021 - mdpi.com
Basal stem rot (BSR) disease occurs due to the most aggressive and threatening fungal
attack of the oil palm plant known as Ganoderma boninense (G. boninense). BSR is a …

Impact of economic indicators on rice production: A machine learning approach in Sri Lanka

S Kularathne, N Rathnayake, M Herath… - PLOS …, 2024 - journals.plos.org
Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic
landscapes. This study delves into the complex interplay between economic indicators and …

[HTML][HTML] Predicting Green Water Footprint of Sugarcane Crop Using Multi-Source Data-Based and Hybrid Machine Learning Algorithms in White Nile State, Sudan

RH Al-Taher, ME Abuarab, AARS Ahmed, MM Hamed… - Water, 2024 - mdpi.com
Water scarcity and climate change present substantial obstacles for Sudan, resulting in
extensive migration. This study seeks to evaluate the effectiveness of machine learning …

Basal Stem Rot Disease Classification by Machine Learning Using Thermal Images and an Imbalanced Data Approach

IC Hashim, ARM Shariff, SK Bejo, FM Muharam… - IoT and AI in Agriculture …, 2023 - Springer
Oil palm has become a commodity of global strategic importance due to its rapid expansion.
Palm oil is widely utilised in food and as a biodiesel precursor. The oil boosts several …

Global schema as local data integrator using active learning to identify candidates attributes

C Santos, C Dorneles - International Journal of Applied …, 2023 - inderscienceonline.com
Data integration represents a challenge in application development. Although there are
several alternatives to data integration, such as federated and distributed databases, there …

Tomato Plant Leaf Disease Detection Using Image Recognition: A Case Study of Mlali in Morogoro Region, Tanzania

JP Chipuli, GW Luwemba - European Journal of Information …, 2023 - ej-compute.org
Tomato plant diseases pose a big problem as they drastically reduce the quantity of a farm's
yield and also result in poor tomato quality, which may affect users. Detecting and identifying …

[PDF][PDF] Unveiling the Potential of Artificial Intelligence in Agriculture

M Hesham - 2023 - easychair.org
Abstract The convergence of Artificial Intelligence (AI) and agriculture has catalyzed a
paradigm shift in the way we perceive and engage with modern farming practices. This …