Microsoft CEO Satya Nadella uses the example of an Indian farmer to advocate for AI solutions in the future of agriculture

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Microsoft CEO Satya Nadella uses the example of an Indian farmer to advocate for AI solutions in the future of agriculture

Speaking on day 2 of the World Economic Forum at Davos, Microsoft CEO Satya Nadella narrated an anecdote about how an Indian farmer was seamlessly able to access online government services with the help of ChatGPT. Agriculture contributes 20.19% to India’s GDP and helps maintain the food security of the country. But with the rising demand to meet the needs of an increasing population, conventional farming practices aren’t feasible due to low output, thereby mounting challenges of food inflation, and food security, according to government sources.

Issues like illiteracy among many small farmers, preference for conventional techniques of farming, dearth of investment and capital infrastructure, low agricultural output, climate change disturbances, fragmented landholdings, etc., further complicate the problems in the Indian agricultural landscape. Therefore, technological assistance from Artificial Intelligence is needed to combat many of the issues.

The Indian government invested 1756.3 crore rupees and 2422.7 crore rupees during 2020-21 and 2021-22 respectively in new technologies like remote sensing, blockchain, drones, and GIS. AI helps farmers deal with the numerous uncertainties in agriculture by analysing and providing real-time data like soil conditions, weather, temperature, water usage, etc., and by aiding processes like harvesting, processing, and marketing.

On 19th March 2022, PM Narendra Modi introduced 100 drones that would help farmers through weather predictions. According to other sources, rainfall research, soil reports, insect infections, and drone imagery can be used for crop monitoring, field surveys, and in-depth field analysis; while remote sensing, proximity sensing, image-based precision farming, and Internet of Things (IoT) can be utilised for data integration in regards to historical meteorology. Identifying patterns in voluminous datasets through yield mapping and optimising irrigation systems is indispensable for crop planning.

Apps like KisanHub, Farmonaut, and Orbit Field Scout warn farmers about disease outbreaks in crops or pest attacks by locusts. This helps farmers with crop protection and loss minimisation. The utilization of image recognition by AI is becoming more prevalent for identifying plant types, disease diagnosis, and pest infestation. Surveillance tech powered by machine learning is being employed to monitor crops through real-time video feeds that identify human and animal interference, and immediately notify farmers regarding the same, to avert crop damage.

Cropin, an AI tool, has created a platform that collects data across the globe, connects to the cloud, and maintains a database that agriculturalists can utilise to access farming techniques that best suit the situation they’re facing. AI can also help farmers adopt sustainable agricultural practices by optimising water consumption, creating more resistant plant varieties, and minimising the usage of pesticides.

Tools based on AI and machine learning like smart tractors, robotics and agribots are viable solutions to address the labour shortage in various remote areas of the nation. These robots can locate and remove weeds with high precision, and harvest faster, thus reducing operating costs and dependence on human labour. Further, they can be used for various processes like mowing, seeding, and spraying. Farmers can put forth their queries regarding specific agriculture and yield-related problems to chatbots that provide curated advice and guidance.

Last year, Microsoft provided land, agricultural, and fertiliser advisory services to 175 farmers in Andhra Pradesh, a project that culminated in a 30 percent higher average yield per hectare. Agricultural AI apps facilitated the completion of this pilot project by assisting with soil preparation, soil tests and the subsequent fertilisation, seed treatment, among others. Various advanced computing systems can be used to arrive at probable yield costs, thereby assisting in price forecasting. The Karnataka Government, in collaboration with IBM, is developing an advanced cost forecasting system.

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members