AIMC Topic: Farmers

Clear Filters Showing 1 to 10 of 19 articles

Computer intelligence based model for mental health detection among Indian farming communities.

Scientific reports
Mental health challenges among Indian farmers are a critical yet under reviewed public health problem, especially in rural areas where access to men's health professionals is limited. Stress from crop failure, fluctuating prices, debt, and poor socia...

When crops fail, forests follow: Agricultural shocks and deforestation in Zambia.

Proceedings of the National Academy of Sciences of the United States of America
As climate change makes agricultural production shocks more frequent and severe, it is vital to understand their effect on farmer welfare, land use, and deforestation. Theoretically, a change in agricultural productivity could increase or decrease de...

A robust hydroponic system for horticulture farming using deep learning, IoT, and mobile application.

PloS one
Due to limited literacy among root-level farmers, hydroponic farming in Bangladesh faces significant challenges. Therefore, there is a demand for easy-to-use technical systems to help farmers to monitor and operate smart systems. To address the issue...

Incremental and transformational climate change adaptation factors in agriculture worldwide: A comparative analysis using natural language processing.

PloS one
Climate change is projected to adversely affect agriculture worldwide. This requires farmers to adapt incrementally already early in the twenty-first century, and to pursue transformational adaptation to endure future climate-induced damages. Many ar...

German sugar beet farmers' intention to use autonomous field robots for seeding and weeding.

Journal of environmental management
Robotic weed control is not yet widely adopted, despite its technological availability and proven economics and sustainability in crop cultivation by replacing seasonal labor and synthetic pesticides. This impedes technologically enabled changes towa...

AI-PUCMDL: artificial intelligence assisted plant counting through unmanned aerial vehicles in India's mountainous regions.

Environmental monitoring and assessment
This work introduces a novel approach to remotely count and monitor potato plants in high-altitude regions of India using an unmanned aerial vehicle (UAV) and an artificial intelligence (AI)-based deep learning (DL) network. The proposed methodology ...

The groundbreaking impact of digitalization and artificial intelligence in sheep farming.

Research in veterinary science
The integration of digitalization and Artificial Intelligence (AI) has marked the onset of a new era of efficient sheep farming in multiple aspects ranging from the general well-being of sheep to advanced web-based management applications. The result...

Predicting opinion using deep learning: From burning to sustainable management of organic waste in Indian State of Punjab.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
In winter season, the burning of crop residues for ease of sowing the next crop, along with industrial emissions and vehicular pollution leads to settling of a thick layer of smog in northern part of India. Therefore, to understand the opinion of far...

Developing an automatic warning system for anomalous chicken dispersion and movement using deep learning and machine learning.

Poultry science
Chicken is a major source of dietary protein worldwide. The dispersion and movement of chickens constitute vital indicators of their health and status. This is especially evident in Taiwanese native chickens (TNCs), a local variety which is high in p...

IoT and Deep Learning-Based Farmer Safety System.

Sensors (Basel, Switzerland)
Farming is a fundamental factor driving economic development in most regions of the world. As in agricultural activity, labor has always been hazardous and can result in injury or even death. This perception encourages farmers to use proper tools, re...