[HTML][HTML] Internet of things for the future of smart agriculture: A comprehensive survey of emerging technologies

O Friha, MA Ferrag, L Shu, L Maglaras… - IEEE/CAA Journal of …, 2021 - ieee-jas.net
This paper presents a comprehensive review of emerging technologies for the internet of
things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and …

Classification and detection of insects from field images using deep learning for smart pest management: A systematic review

W Li, T Zheng, Z Yang, M Li, C Sun, X Yang - Ecological Informatics, 2021 - Elsevier
Insect pest is one of the main causes affecting agricultural crop yield and quality all over the
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …

[HTML][HTML] Deep learning based detector YOLOv5 for identifying insect pests

I Ahmad, Y Yang, Y Yue, C Ye, M Hassan, X Cheng… - Applied Sciences, 2022 - mdpi.com
Insect pests are a major element influencing agricultural production. According to the Food
and Agriculture Organization (FAO), an estimated 20–40% of pest damage occurs each …

Transfer learning-based deep ensemble neural network for plant leaf disease detection

S Vallabhajosyula, V Sistla, VKK Kolli - Journal of Plant Diseases and …, 2022 - Springer
Plant diseases are a vital risk to crop yield and early detection of plant diseases remains a
complex task for the farmers due to the similar appearance in color, shape, and texture. In …

[HTML][HTML] A new mobile application of agricultural pests recognition using deep learning in cloud computing system

ME Karar, F Alsunaydi, S Albusaymi… - Alexandria Engineering …, 2021 - Elsevier
Agricultural pests cause between 20 and 40 percent loss of global crop production every
year as reported by the Food and Agriculture Organization (FAO). Therefore, smart …

Advances in deep concealed scene understanding

DP Fan, GP Ji, P Xu, MM Cheng, C Sakaridis… - Visual Intelligence, 2023 - Springer
Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive
objects exhibiting camouflage. The current boom in terms of techniques and applications …

Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review

GA Mesías-Ruiz, M Pérez-Ortiz, J Dorado… - Frontiers in Plant …, 2023 - frontiersin.org
Crop protection is a key activity for the sustainability and feasibility of agriculture in a current
context of climate change, which is causing the destabilization of agricultural practices and …

A systematic review on automatic insect detection using deep learning

AC Teixeira, J Ribeiro, R Morais, JJ Sousa, A Cunha - Agriculture, 2023 - mdpi.com
Globally, insect pests are the primary reason for reduced crop yield and quality. Although
pesticides are commonly used to control and eliminate these pests, they can have adverse …

Automated pest detection with DNN on the edge for precision agriculture

A Albanese, M Nardello… - IEEE Journal on Emerging …, 2021 - ieeexplore.ieee.org
Artificial intelligence has smoothly penetrated several economic activities, especially
monitoring and control applications, including the agriculture sector. However, research …

[HTML][HTML] Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions

D Muhammed, E Ahvar, S Ahvar, M Trocan… - Journal of Network and …, 2024 - Elsevier
Abstract The Artificial Intelligence of Things (AIoT), a combination of the Internet of Things
(IoT) and Artificial Intelligence (AI), plays an increasingly important role in smart agriculture …