AI Powered Microsoft Sensors to Assist Indian Farmers Digitally Record Information for Smart Farming

In a few dozen villages in Telangana, Maharashtra and Madhya Pradesh, farmers are receiving automated voice calls that tell them whether their cotton crops are at risk of a pest attack, based on weather conditions and crop stage.

Farming output can increase in two basic ways: By increasing the yield per unit area (intensification), or by expanding the area under cultivation (extensification). Increased cereal production has largely been achieved by intensification over the last 50 years (Figure B). Only 16% more land was used for cereals in 2014 than in 1961, for example, while global cereal production increased by 280%. During the same period, the world’s population increased 136%, which means that cereal production per person has increased even as the population has more than doubled.

In Karnataka, the government can get price forecasts for essential commodities such as tur (split red gram) three months in advance for planning the Minimum Support Price (MSP).

In collaboration with ICRISAT, Microsoft has developed an AI-Sowing App powered by Microsoft Cortana Intelligence Suite including Machine Learning and Power BI.

“The app sends sowing advisories to participating farmers on the optimal date to sow. The best part — the farmers don’t need to install any sensors in their fields or incur any capital expenditure. All they need is a feature phone capable of receiving text messages,” the company said.

To calculate the crop-sowing period, historic climate data spanning over 30 years — from 1986 to 2015 — for the Devanakonda area in Andhra Pradesh was analysed using AI. This data is then downscaled to build predictability and guide farmers to pick the ideal sowing week.

This year, ICRISAT has scaled sowing insights to 4,000 farmers across Andhra Pradesh and Karnataka for the Kharif crop cycle (rainy season). The Karnataka government will start using price forecasting for agricultural commodities, in addition to sowing advisories for farmers in the state.

Commodity prices for items such as tur, of which Karnataka is the second largest producer, will be predicted three months in advance for major markets in the state, Microsoft said. Microsoft has developed a multivariate agricultural commodity price forecasting model to predict future commodity arrival and the corresponding prices. The model uses remote sensing data from geo-stationary satellite images to predict crop yields through every stage of farming.