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Neural Network Pattern Classification and Weather Dependent Fuzzy Logic Model for Irrigation Control in WSN Based Precision Agriculture
2016
Procedia Computer Science
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The best technique is used for the final prediction, and the predicted soil MC is utilized for generating appropriate notifications using fuzzy logic based weather model. ...
This article focuses on two optimization strategies, for example, Scaled Conjugate Gradient and BFGS Quasi-Newton based neural network algorithms utilized to predict hourly requirement of soil MC. ...
Acknowledgement The authors thank to All India Council for Technical Education (AICTE), New Delhi, India to provide support under Career Award for Young Teachers (CAYT) scheme 2013-2014 and help for continuing ...
doi:10.1016/j.procs.2016.02.094
fatcat:rbjxiialwfas3erxpx6w5odhca
A Literature Survey on Precision Crop Prediction Using Soil and Environmental Analysis
2024
International Journal of Advanced Research in Science, Communication and Technology
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The objective of the research project, titled "Precision Crop Prediction using Soil and Environmental Analysis," is to develop a system that utilizes machine learning algorithms and extensive datasets ...
By offering a comprehensive and data-driven solution, farmers can make more informed decisions, optimize resource allocation, and enhance overall agricultural productivity. ...
The MSVM model is optimized using the FFO algorithm for precise soil characterization and crop recommendations. ...
doi:10.48175/ijarsct-15341
fatcat:prbrad345rattgrzs6lakjq4wy
Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks
2024
Journal of Cloud Computing: Advances, Systems and Applications
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Fuzzy optimization models were formulated using domain expertise for three key supply chain decision problems. Auction markets discover optimal crop demand–supply balancing and pricing signals. ...
Although the edge computing framework manages real-time crop monitoring and data collection, market-based mechanisms, such as auctions and fuzzy optimization models, support decision-making for smooth ...
optimization models, support decision-making for smooth agricultural supply chain operations. ...
doi:10.1186/s13677-024-00626-8
fatcat:cu2gxmahs5d6bkhbkmbrn7hzri
Use of Artificial Intelligence and Precision Strategies in Various Aspects of Agriculture
2024
International Research Journal of Modernization in Engineering Technology and Science
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Agriculture is the bedrock of the economy's sustainability. It plays a major role in the economic growth of any country. ...
This paper provides a review of the precision strategies and applications of AI in crop monitoring, pest control, irrigation, weed control, the use of robots and some challenges and solutions. ...
These can process Predicting the large amounts of crop yield, soil Collecting a large amount data, learn the moisture, of data for training is a 5 Artificial Neural Networks patterns and relationships ...
doi:10.56726/irjmets48111
fatcat:f22luqiifrh4daambqk6e6s73u
Precision Irrigation Management Using Machine Learning and Digital Farming Solutions
2022
AgriEngineering
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This article reviews the research trend and applicability of machine learning techniques, as well as the deployment of developed machine learning models for use by farmers toward sustainable irrigation ...
Agricultural activities utilize around 70% of the available freshwater. This underscores the importance of responsible management, using smart agricultural water technologies. ...
Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable. ...
doi:10.3390/agriengineering4010006
fatcat:ld6yznzpkvcppn6zfxwpsfoyuq
Integration Of Machine Learning Techniques in Banana Production: A Literature Review
2024
Zenodo
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Utilizing machine learning techniques to their fullest potential can aid future studies tackling issues pertaining to food security and sustainable agriculture. ...
As an emerging technology, machine learning have been employed in agriculture by assessing different factors brought about by a crop. ...
methods The proposed model Findings Saranya, N. (2023) Shaheb, R. (2021) FBCNN-TSA: An optimal deep learning model for banana ripening stages classification Precision Agriculture for Sustainable Soil ...
doi:10.5281/zenodo.10667894
fatcat:d7cgztdp2zc4fp7vr23qfnrufu
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management
[article]
2022
arXiv
pre-print
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This project aims to forecast soil moisture using domain knowledge and machine learning for crop management decisions that enable sustainable farming. ...
Our approach involves clustering units based on time-varying hydrological properties, constructing graph topologies for each cluster, and forecasting soil moisture using graph convolutions and a gated ...
We use the temporal graph convolution neural network detailed in (Zhao et al. 2020) for predicting soil moisture at each node. ...
arXiv:2212.06565v1
fatcat:ctwj4vwr7fbitff6mwmx7c3oqm
D2.1 Report on state-of-the-art algorithms
2022
Zenodo
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This article presents a selective survey on articles for Data Mining in the field of Agriculture. ...
The main purpose f the article is to research what algorithms are the most used in this field for different aspects like temperature, humidity, but also predictions like crop yield and crop health. ...
Hardware components and their connections in Agriculture 4.0
Table 1 : 1 Crop Rec -Crop Recommendation, CDP -Crop Disease Prediction, SVM -Support Vector Machines, SMP -Soil Moisture Prediction, CYP ...
doi:10.5281/zenodo.7432873
fatcat:ur7efkhuzrdhjnnezhielkf5d4
A Deep Learning-Based Sensor Modeling for Smart Irrigation System
2022
Agronomy
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The LM35 sensor is used for temperature, DHT-22 for humidity, and we designed a customized sensor in our lab for the acquisition of moisture values. ...
Our results highlight the possibility of using a neural network, referred to as a neural sensor here, to complement the functioning of a physical sensor deployed in an agriculture field in order to make ...
Acknowledgments: The authors would like to thank Smart City Lab, National Center for Artificial Intelligence, Computer and Information Systems Department, NED University of Engineering and Technology, ...
doi:10.3390/agronomy12010212
fatcat:dnx3tpnlgfbeplou3wzh3ee7hq
Intelligent Agricultural Greenhouse Control System Based on Internet of Things and Machine Learning
[article]
2024
arXiv
pre-print
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to augmenting the efficiency and sustainability of agricultural production. ...
Against this backdrop, greenhouse agriculture emerges as a viable solution, proffering a controlled milieu for crop cultivation to augment yields, refine quality, and diminish reliance on natural resources ...
agricultural system (Air Humidity, Soil Moisture (left)and Soil Temperatire, Air Temperature (right)
Figure 4 : 4 Figure 4: Measurement results using the smart agricultural system (Soil pH value, Light ...
arXiv:2402.09488v1
fatcat:w4webhgoezeg3juvkpjciediqu
How much is enough in watering plants? State-of-the-art in irrigation control: Advances, challenges, and opportunities with respect to precision irrigation
2022
Frontiers in Control Engineering
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Reliance on soil moisture measurements to establish irrigation water demand inadequately addresses heterogenous distribution of water in soil. ...
A discussion of the observed strengths and shortcomings and technological advances supporting the various methods used to quantify plant water status extends the review. ...
Acknowledgments The authors wish to acknowledge the support provided the Deutscher Akademischer Austauschdienst (DAAD) and the Kenya National Research Fund (NRF) by means of a scholarship covering the ...
doi:10.3389/fcteg.2022.982463
fatcat:2paz2cvtgjhevmhecu3wezwvom
IMPLICATIONS OF NEURAL NETWORK AS A DECISION-MAKING TOOL IN MANAGING KAZAKHSTAN'S AGRICULTURAL ECONOMY
2024
Applied Computer Science
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This study investigates the application of Artificial Neural Networks (ANN) in forecasting agricultural yields in Kazakhstan, highlighting its implications for economic management and policy-making. ...
The findings have significant implications for Kazakhstan's economy. Accurate yield predictions can optimize agricultural planning, contribute to food security, and inform policy decisions. ...
using indicators of vegetation index NDVI and average temperature, surface soil moisture and wind speed. ...
doi:10.35784/acs-2023-39
fatcat:725aus27tjgmzgfskonoyjcjra
Water Allocation and Integrative Management of Precision Irrigation: A Systematic Review
2020
Water
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, integrative, and evolutionary irrigation system while providing the higher quality and efficiency needed for a full application of precision irrigation. ...
attention in agricultural production and crop cultivation. ...
Acknowledgments: We thank the editors for their hard work and the referees for their comments and valuable suggestions that helped to improve this paper. ...
doi:10.3390/w12113135
fatcat:q3ftrtlafzf2bikxrh2a5jnfce
Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation
2017
Sustainability
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The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil-plant-atmosphere system while considering ...
Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. ...
Acknowledgments: The authors wish to acknowledge John Oldacre Foundation for funding this research project. The reviewers are also acknowledged for their insight on improving this article. ...
doi:10.3390/su9030353
fatcat:i4i34fqu7jadviukfstrxdtk5e
Internet of Things and Machine Learning Applications for Smart Precision Agriculture
[chapter]
2021
Ubiquitous Computing [Working Title]
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Application of remote sensors like temperature, humidity, soil moisture, water level sensors and pH value will provide an idea to on active farming, which will show accuracy as well as practical agriculture ...
Besides, it elucidates the problems, specific potential solutions, and future directions for the agriculture sector using Machine Learning and the Internet of things. ...
Support vector regression (S. V.R.) a variant of SVM used for crop yield prediction. ...
doi:10.5772/intechopen.97679
fatcat:2stbj72a3bf67bgs72swxtglf4
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