Internet and Computers for Agriculture

Given the current growth in global challenges, the need for smart agriculture practices and effective strategies is emerging as an imminent issue at a planetary scale. Agriculture 4.0 involves a large variety of mobile apps, web applications, Internet of Things (IoT) devices and platforms, drones, r...

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Format eBook
LanguageEnglish
Published Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects
IoT
n/a
VMD
WSN
Online AccessGet full text
ISBN3036566317
9783036566313
3036566309
9783036566306
DOI10.3390/books978-3-0365-6631-3

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Abstract Given the current growth in global challenges, the need for smart agriculture practices and effective strategies is emerging as an imminent issue at a planetary scale. Agriculture 4.0 involves a large variety of mobile apps, web applications, Internet of Things (IoT) devices and platforms, drones, robots, and smart machinery for precision agriculture. The expansion of cloud technologies, artificial intelligence (AI), machine learning (ML), deep learning (DL), and big data collection are setting the stage for Agriculture 5.0. Agriculture science and natural sciences are further promoting this trend with the development of leading-edge scientific models and platforms, including stochastic, process-based, and data-driven machine learning modeling. This Special Issue covers the most recent and up-to-date progress in all aspects of internet and computer software applications in agriculture, focusing on the development of web applications and mobile apps, smart IoT devices and platforms, AI, ML and DL solutions in precision agriculture for detection, recognition, classification, monitoring, cultivation, harvesting, and marketing; development of cloud technologies for smart agriculture; computer and machine vision methods and applications for drones and smart machinery, and sensors for field operations; diagnostics and data collection; big data science; scientific process-based and stochastic modeling; and machine learning modeling for agriculture, agroecosystems and natural ecosystems. The research in this Special Issue will contribute to the promotion of modern agriculture practices in the current climate and in the future.
AbstractList Given the current growth in global challenges, the need for smart agriculture practices and effective strategies is emerging as an imminent issue at a planetary scale. Agriculture 4.0 involves a large variety of mobile apps, web applications, Internet of Things (IoT) devices and platforms, drones, robots, and smart machinery for precision agriculture. The expansion of cloud technologies, artificial intelligence (AI), machine learning (ML), deep learning (DL), and big data collection are setting the stage for Agriculture 5.0. Agriculture science and natural sciences are further promoting this trend with the development of leading-edge scientific models and platforms, including stochastic, process-based, and data-driven machine learning modeling. This Special Issue covers the most recent and up-to-date progress in all aspects of internet and computer software applications in agriculture, focusing on the development of web applications and mobile apps, smart IoT devices and platforms, AI, ML and DL solutions in precision agriculture for detection, recognition, classification, monitoring, cultivation, harvesting, and marketing; development of cloud technologies for smart agriculture; computer and machine vision methods and applications for drones and smart machinery, and sensors for field operations; diagnostics and data collection; big data science; scientific process-based and stochastic modeling; and machine learning modeling for agriculture, agroecosystems and natural ecosystems. The research in this Special Issue will contribute to the promotion of modern agriculture practices in the current climate and in the future.
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SubjectTerms adversarial training
agricultural water management
Android apps
aquatic products price forecast
attention mechanism
Biology, life sciences
buffalo breeds
Canonical Correlation Analysis (CCA)
Chinese agricultural diseases and pests
classification
climate extreme
conceptual model
conceptual resilience model
containerization
convolutional neural network
Convolutional Neural Network (CNN)
COVID-19 pandemic
data-driven modeling
decision support
decision support systems
deep feature fusion
deep learning
DeepLabv3
digital agriculture
e-commerce interest linkage
early prediction of crop yield
evolutionary game model
farm management information system
farmers’ cognition
farmers’ information needs assessment
food processing
fresh agricultural products
fuzzy collaborative intelligence
government policies
grape detection
grape leaf disease
grape varieties identification
hemp duck count
horticulture
hybrid model
IBES
Indonesian chili farmers
input uncertainty
interactive interface
IoT
leisure agricultural park
logistics
LoRaWAN
LSTM
machine learning
machine vision
maize seeds
Mathematics and Science
multi-agent
n/a
named entity recognition
neural network
Neural Networks
NSGA-II algorithm
object detection
operations
participation willingness and behaviors
picking point identification
planning framework
precision agriculture
process-based modeling
Reference, Information and Interdisciplinary subjects
regression algorithms
Research and information: general
residual block
Self Activated CNN
self-attention
semantic enhancement
semantic segmentation
semi-literate farmers
sensor network
smallholder farmers
smart agriculture
smart farming
smart machinery
soft system methodology
split delivery
structural equation model
supply chain
Support Vector Machine (SVM)
sustainable food systems
technology innovation
Technology, Engineering, Agriculture, Industrial processes
transformation
transition pathways
traveler group
User Interface (UI)
vehicle routing problem
VMD
water security
water status
web application
WSN
YOLOv7
Title Internet and Computers for Agriculture
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