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A comprehensive survey on tinyml
Recent spectacular progress in computational technologies has led to an unprecedented
boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas …
boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas …
Harvesting a sustainable future: An overview of smart agriculture's role in social, economic, and environmental sustainability
As climate change and population growth intensify, the agricultural sector's need for
sustainable solutions is paramount. This paper presents an overview of smart agriculture, a …
sustainable solutions is paramount. This paper presents an overview of smart agriculture, a …
A survey on artificial intelligence in cybersecurity for smart agriculture: State-of-the-art, cyber threats, artificial intelligence applications, and ethical concerns
Wireless sensor networks and Internet of Things devices are revolutionizing the smart
agriculture industry by increasing production, sustainability, and profitability as connectivity …
agriculture industry by increasing production, sustainability, and profitability as connectivity …
Smart farming monitoring using ML and MLOps
Smart farming includes various operations like crop yield prediction, soil fertility analysis,
crop recommendation, water management, and many activities. Researchers are …
crop recommendation, water management, and many activities. Researchers are …
Tiny machine learning on the edge: A framework for transfer learning empowered unmanned aerial vehicle assisted smart farming
Emerging technologies are continually redefining the paradigms of smart farming and
opening up avenues for more precise and informed farming practices. A tiny machine …
opening up avenues for more precise and informed farming practices. A tiny machine …
IoT solutions with artificial intelligence technologies for precision agriculture: definitions, applications, challenges, and opportunities
The global agricultural sector confronts significant obstacles such as population growth,
climate change, and natural disasters, which negatively impact food production and pose a …
climate change, and natural disasters, which negatively impact food production and pose a …
A comparative analysis of XGBoost and neural network models for predicting some tomato fruit quality traits from environmental and meteorological data
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 …
and agronomic research due to its nutritional, economic, and health significance. This study …
IoT-driven machine learning for precision viticulture optimization
Precision agriculture (PA), also known as smart farming, has emerged as an innovative
solution to address contemporary challenges in agricultural sustainability. A particular sector …
solution to address contemporary challenges in agricultural sustainability. A particular sector …
Group-conditional conformal prediction via quantile regression calibration for crop and weed classification
As deep learning predictive models become an integral part of a large spectrum of precision
agricultural systems, a barrier to the adoption of such automated solutions is the lack of user …
agricultural systems, a barrier to the adoption of such automated solutions is the lack of user …
Evaluating the intention to use Industry 5.0 (I5. 0) drones for cleaner production in Sustainable Food Supply Chains: an emerging economy context
K Mahroof, A Omar, E Vann Yaroson… - Supply Chain …, 2024 - emerald.com
Purpose The purpose of this study is to evaluate food supply chain stakeholders' intention to
use Industry 5.0 (I5. 0) drones for cleaner production in food supply chains …
use Industry 5.0 (I5. 0) drones for cleaner production in food supply chains …