A comprehensive survey on tinyml

Y Abadade, A Temouden, H Bamoumen… - IEEE …, 2023 - ieeexplore.ieee.org
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 …

Harvesting a sustainable future: An overview of smart agriculture's role in social, economic, and environmental sustainability

ZHZ Azlan, SN Junaini, NA Bolhassan, R Wahi… - Journal of Cleaner …, 2024 - Elsevier
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 …

A survey on artificial intelligence in cybersecurity for smart agriculture: State-of-the-art, cyber threats, artificial intelligence applications, and ethical concerns

G Ali, MM Mijwil, BA Buruga… - Mesopotamian …, 2024 - journals.mesopotamian.press
Wireless sensor networks and Internet of Things devices are revolutionizing the smart
agriculture industry by increasing production, sustainability, and profitability as connectivity …

Smart farming monitoring using ML and MLOps

Y Akkem, SK Biswas, A Varanasi - International conference on innovative …, 2023 - Springer
Smart farming includes various operations like crop yield prediction, soil fertility analysis,
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

AM Hayajneh, SA Aldalahmeh, F Alasali… - IET Smart …, 2024 - Wiley Online Library
Emerging technologies are continually redefining the paradigms of smart farming and
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

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 …

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 …

IoT-driven machine learning for precision viticulture optimization

C Pero, S Bakshi, M Nappi… - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Precision agriculture (PA), also known as smart farming, has emerged as an innovative
solution to address contemporary challenges in agricultural sustainability. A particular sector …

Group-conditional conformal prediction via quantile regression calibration for crop and weed classification

P Melki, L Bombrun, B Diallo, J Dias… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

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 …