A comprehensive survey on IoT and AI based applications in different pre-harvest, during-harvest and post-harvest activities of smart agriculture

RK Kasera, S Gour, T Acharjee - Computers and Electronics in Agriculture, 2024 - Elsevier
Today farmers around the world are gradually embracing Smart farming assisted by different
cutting-edge technologies. The Internet of Things (IoT) is playing a major role in the …

Modern-age Agriculture with Artificial Intelligence: A review emphasizing Crop Yield Prediction

P Sharma, P Dadheech - 2023 - catalog.lib.kyushu-u.ac.jp
Agriculture is a key employment in several countries throughout the globe. AI is increasingly
becoming a part of agriculture industry as traditional methods are insufficient to supply the …

Tomato plant disease classification using multilevel feature fusion with adaptive channel spatial and pixel attention mechanism

CK Sunil, CD Jaidhar, N Patil - Expert Systems with Applications, 2023 - Elsevier
Agriculture's productivity has decreased in the last decade due to climate change and
inappropriate usage of water, fertilizer, and pesticides, which stimulate plant diseases. Plant …

Systematic study on deep learning-based plant disease detection or classification

CK Sunil, CD Jaidhar, N Patil - Artificial Intelligence Review, 2023 - Springer
Plant diseases impact extensively on agricultural production growth. It results in a price hike
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …

Field evaluation of smart sensor system for plant disease prediction using LSTM network

KS Patle, R Saini, A Kumar… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Leaf wetness duration (LWD), soil moisture, soil temperature, ambient temperature, and
relative humidity information are the essential factors that leads to germination of plant …

A unified lightweight CNN-based model for disease detection and identification in corn, rice, and wheat

S Verma, P Kumar, JP Singh - IETE Journal of Research, 2024 - Taylor & Francis
Plant diseases are a significant threat to global food security since they directly affect the
quality of crops, leading to a decline in agricultural productivity. Several researchers have …

Machine learning techniques for increasing efficiency of the robot's sensor and control information processing

Y Kondratenko, I Atamanyuk, I Sidenko, G Kondratenko… - Sensors, 2022 - mdpi.com
Real-time systems are widely used in industry, including technological process control
systems, industrial automation systems, SCADA systems, testing, and measuring equipment …

[HTML][HTML] Towards a semantic structure for classifying IoT agriculture sensor datasets: An approach based on machine learning and web semantic technologies

D Lynda, F Brahim, S Hamid, C Hamadoun - Journal of King Saud …, 2023 - Elsevier
With the increase in the number of IoT farming datasets, it has become so difficult to identify
the right data for IoT agriculture applications. Therefore, a meaningful structure is needed to …

IoT Enabled, Leaf Wetness Sensor on the Flexible Substrates for In-Situ Plant Disease Management

KS Patle, R Saini, A Kumar, SG Surya… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Early plant disease detection and providing the control measures have become highly
desirable to improve crop yield. Leaf wetness duration (LWD) is one of the essential …

AI-Enabled Crop Recommendation System Based on Soil and Weather Patterns

P Sharma, P Dadheech, AVSK Senthil - Artificial Intelligence Tools …, 2023 - igi-global.com
Agriculture is the foremost factor which is important for the survival of human beings.
Farming contributes to a very big part of GDP; still, several areas exist where improvements …