A Sustainable Approach of Artificial Neural Network for Prediction of Irrigation, Pesticides, Fertilizers, and Crop Yield

Abstract

Food demand increases as the world's population expands; the world populace will reach 9.9 billion by 2050. India will be the world's largest population by 2024. Agriculture, therefore, should be fruitful and affordable for subsistence. Organic methods of agriculture are still effective for healthier crops. However, production shrinks as it depends wholly on manual labour. Since traditional farming, agriculture has seen various revolutions and developments. Currently, in the era of Agriculture 5.0, precision agriculture principles using artificial intelligence, machine learning, and IoT are being used. India still relies heavily on manual work. Educational level, inadequate training, and indigent farmers put India at a disadvantage. Technology may lead to sustainable agriculture, which means integration of plant and animal production that leaves unshakable benefits on the environment, farmers, and society that essential for the climate change- and disaster-prone world. Machine learning techniques that can possibly cater to various agricultural challenges faced by famers in India are reviewed.