AI and Data-driven Approaches for Agriculture

According to data from Govt. of India, agriculture is a high-priority sector of the Indian economy, with 58% of all families dependent on it directly or indirectly, for their livelihoods. With increasing world population, climate change and limited arable land, the current practices in agriculture are becoming unsustainable for both people and planet as they incur huge environmental cost and wastage. These in turn leave the small producers at or below the poverty level.

Therefore, there is an urgent need of paradigm shift in this domain, and adoption of digital and AI based technologies can aid in the shift. AI and Data-driven technologies have the potential to enhance productivity and efficiency, thus generating higher farm income, waste reduction and sustainability. By collecting and analyzing data from various sources such as reports, images, sensors, drones, and other sources, farmers can gain a deeper understanding of their fields and crops. This information can then be used to make more precise decisions about irrigation, fertilization, pest control, and other farming practices. AI and data driven techniques are also gaining traction in the precision livestock management. From sensor based farm and animal behavior monitoring to veterinary medicine - AI based systems have found several applications.

In this tutorial we will briefly describe about how we can apply state of the art ML/DL techniques on data from different modalities and different perspective to gain useful insights on enhanced agricultural output.