Embedded Machine-Learning For Variable-Rate Fertiliser Systems: A Model-Driven Approach To Precision Agriculture

JM Stover, G Falzon, D Lamb - 2019 - rune.une.edu.au
Efficient use of fertilisers, in particular the use of Nitrogen (N), is one of the rate-limiting
factors in meeting global food production requirements. While N is a key driver in increasing …

[PDF][PDF] Hardware and embedded algorithms for real time variable rate fertiliser applications

J Stover, G Falzon, T Jensen… - The International Tri …, 2017 - researchgate.net
Efficient use of fertilisers, in particular the use of Nitrogen (N), is one of the rate-limiting
factors in meeting global food production requirements. While N is a key driver in increasing …

Evaluation of Machine Learning approaches for precision Farming in Smart Agriculture System-A comprehensive Review

G Mohyuddin, MA Khan, A Haseeb, S Mahpara… - IEEE …, 2024 - ieeexplore.ieee.org
In the era of digital data proliferation, agriculture stands on the cusp of a transformative
revolution driven by Machine Learning (ML). This study delves into the intricate interplay …

[PDF][PDF] Integrating Variable Rate Application with Machine Learning Algorithms for Intelligent and Responsive Agriculture

P Mishra, S Nagarkar, V Gaikwad - JOURNAL OF TECHNICAL … - researchgate.net
The agricultural sector is experiencing a revolutionary transformation propelled by the
intersection of advanced technologies and data-driven decision-making. A leading …

[HTML][HTML] Modeling and simulation of a multi-parametric fuzzy expert system for variable rate nitrogen application

A Heiß, DS Paraforos, GM Sharipov… - … and Electronics in …, 2021 - Elsevier
Nitrogen (N) excess due to mineral fertilization in conventional crop farming has a significant
negative impact on the environment. Variable rate N application (VRNA) is a promising tool …

Machine Learning for Smart Agriculture: A Comprehensive Survey

MR Mahmood, MA Matin, SK Goudos… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
As communication technologies and equipment evolve, smart assets become smarter. The
agricultural industry is also evolving in line with the implementation of modern …

Smart agricultural system for crop monitoring and soil analysis

B Das, TZ Ul Hoq Sayor, RJ Nijhum, MT Tishun - 2022 - dspace.bracu.ac.bd
Agriculture is the base of the economy in Bangladesh, however, 90% of the farmers are not
familiar with modern-technological tools. That is the reason why we see very-little usage of …

[HTML][HTML] The application of machine learning techniques for Smart Irrigation Systems: a systematic literature review

A Younes, ZE Abou Elassad, O El Meslouhi… - Smart Agricultural …, 2024 - Elsevier
Abstract Smart Irrigation System is a complex concept used to control, monitor and automate
the irrigation of yields by integrating artificial intelligence techniques such as Machine …

Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review

A Chlingaryan, S Sukkarieh, B Whelan - Computers and electronics in …, 2018 - Elsevier
Accurate yield estimation and optimised nitrogen management is essential in agriculture.
Remote sensing (RS) systems are being more widely used in building decision support tools …

SiLab: A Neural Network-based Precision Agriculture System for Siling Labuyo (Capsicum frutescens)

JJMD Cruz, JU De Leon, CAA Bundoc… - 2023 International …, 2023 - ieeexplore.ieee.org
The declining role of the agricultural sector in the country's economy can be attributed to low
productivity. This has significantly impacted the overall economy, as seen in the scarcity and …