Digital transformation in agriculture powered by Artificial Intelligence and Machine Learning

Abstract

As the population increases and incomes rise, demand for food also increased. In a recent report published by the FAO it is expected that total demand for agricultural products in 2030 will be about 60% higher than today. More than 85% of this additional demand will be in the developing countries, as nearly all population growth will be there. Although there is systemic progress in the potential to increase production, there are many challenges that needs to be addressed such as availability of suitable arable land and productivity decline, availability of water required for irrigation, assessment of climate change impact on food production, prevention of damage to agriculture crops due to pests, and others. Although systemic progress has taken place to the boost the agricultural development digital transformation with the application of artificial intelligence and machine learning has become an imperative for the sustenance making many innovations possible in the field of agriculture. This paper highlights the digital transformation trends and various analytics use cases for digital agriculture highlighting the application of Artificial Intelligence/Machine Learning on the data collected with Internet of Things (IoT) Platform that can providesuitable acceleration to meet the global demand. The paper also highlights the new analyticslifecycle with the advent of IoT and the need to establish agriculture innovation, and excellence centers across the country designed for specific farmer needs.