[HTML][HTML] Automation and digitization of agriculture using artificial intelligence and internet of things

A Subeesh, CR Mehta - Artificial Intelligence in Agriculture, 2021 - Elsevier
The growing population and effect of climate change have put a huge responsibility on the
agriculture sector to increase food-grain production and productivity. In most of the countries …

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] 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 …

[HTML][HTML] Smart farming using machine learning and deep learning techniques

SKS Durai, MD Shamili - Decision Analytics Journal, 2022 - Elsevier
The practice of cultivating the soil, producing crops, and keeping livestock is referred to as
farming. Agriculture is critical to a country's economic development. Nearly 58 percent of a …

Pesticide spraying robot for precision agriculture: A categorical literature review and future trends

AT Meshram, AV Vanalkar, KB Kalambe… - Journal of Field …, 2022 - Wiley Online Library
Pesticide spraying is one of the risky and very essential task in agriculture to protect plants
from harmful organisms. Many farmers are used manual pesticide spraying devices that they …

High performing ensemble of convolutional neural networks for insect pest image detection

L Nanni, A Manfè, G Maguolo, A Lumini… - Ecological Informatics, 2022 - Elsevier
Pest infestation is a major cause of crop damage and lost revenues worldwide. Automatic
identification of invasive insects would significantly speed up the recognition of pests and …

An efficient approach for crops pests recognition and classification based on novel DeepPestNet deep learning model

N Ullah, JA Khan, LA Alharbi, A Raza, W Khan… - IEEE …, 2022 - ieeexplore.ieee.org
Crop pests are to blame for significant economic, social, and environmental losses
worldwide. Various pests have different control strategies, and precisely identifying pests …

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 …

A lightweight YOLOv4-Based forestry pest detection method using coordinate attention and feature fusion

M Zha, W Qian, W Yi, J Hua - Entropy, 2021 - mdpi.com
Traditional pest detection methods are challenging to use in complex forestry environments
due to their low accuracy and speed. To address this issue, this paper proposes the …

Blockchain and artificial intelligence-empowered smart agriculture framework for maximizing human life expectancy

NK Jadav, T Rathod, R Gupta, S Tanwar… - Computers and …, 2023 - Elsevier
The massive population growth and rising environmental issues raise several challenges in
the agriculture sector, such as agricultural land scarcity, overuse of pesticides, and global …