Google’s new AI-based tool, Agricultural Landscape Understanding Too l will use high-resolution satellite imagery and machine learning to draw boundaries between fields, information on drought readiness, information on irrigation, market access etc.
Google will introduce Agricultural Landscape Understanding (ALU) tool to provide agricultural information to farmers and boost crop yields. It is a limited availability tool aimed at making agricultural practices data-driven.
Google said that the new AI platform will provide information at a granular level, which is essential for the Indian agricultural landscape. It will use high- resolution satellite imagery, machine learning to draw boundaries between fields, information on drought preparedness, irrigation, market access etc.
The Agricultural Landscape Understanding tool will also give detailed information on crop type, field size, availability of water, and access to roads and markets. It is built on Google Cloud with collaborations from Anthro Krishi team and India’s digital AgriStack. The use of Agriculture Landscape information is already being done by Ninjacart, Skymet, Team-Up, IIT Bombay and the Government of India.
Google says that the tool is aimed at addressing the myriad of challenges faced by farmers from accessing capital and subsidies to improving yields by using artificial intelligence and remote sensing to track individual farm fields all across the country.
Apart from Google, the government has also used artificial intelligence to improve farm yields. The government introduced Kisan-e-Mitra, an AI powered chatbot, in multiple languages for farmers to enquire about the PM Kisan Samman Nidhi scheme and other government initiatives.
The National Pest Surveillance System (NPSS) was launched to tackle the issue of loss of crops due to pests. The system uses AI and machine learning to identify crop issues. According to a PIB report, the government uses AI analytics using field photographs and crop health assessment reports for rice and wheat.
Google has also shared new launches in the Indian language space. It has introduced Project Vaani in collaboration with the Indian Institute of Science (IISc). It is a large data sect which has data on 14,000 hours of speech across 58 languages from 80,000 speakers in 80 districts. Google launched IndicGenBench, to assess generation capabilities of Large Language Models (LLMs) on Indic languages. The tool is specifically designed for Indian languages. It will cover 29 languages including the ones that have never been assessed before.
It is also introducing the Composition of Language Models/ CALM tool that will enable coding in regional languages.
