Why in news?
The Ministry of Agriculture and Farmers’ Welfare launched an artificial intelligence‑powered monsoon forecasting system that sends personalised SMS alerts to 3.8 crore farmers across thirteen states. The initiative aims to help farmers plan sowing and irrigation for the Kharif season.
Background
Indian farmers have long relied on monsoon predictions from the India Meteorological Department. However, traditional forecasts often lack granularity and arrive too late for crucial decisions. The m‑Kisan platform, introduced in 2013, delivers advisories via SMS but depends on conventional meteorological models. Advances in machine learning and the increasing availability of weather and crop data prompted the government to explore AI‑based solutions.
How the system works
- Models used: The initiative blends Google’s Neural Global Climate Model and the European Centre for Medium‑Range Weather Forecasts’ Artificial Intelligence Forecasting System to provide four‑week advance forecasts.
- Customised alerts: Forecasts are tailored to local conditions and delivered in simple language through the m‑Kisan SMS platform. Weekly updates inform farmers about potential dry spells, onset of rains and irrigation needs.
- Partnerships: The programme is a collaboration between the Ministry, the Development Innovation Lab – India and Precision Development, bringing together governmental reach and technical expertise.
Objectives and benefits
- Early warning: By warning farmers of the monsoon’s arrival or pauses, the system enables timely sowing and irrigation, reducing crop losses.
- Risk mitigation: Better forecasts help farmers choose suitable crop varieties, plan input purchases and avoid over‑investment during dry spells.
- Climate resilience: Precise information strengthens farmers’ adaptive capacity as climate change intensifies weather variability.
- Economic impact: Improved yields and reduced input waste enhance incomes and support national food security.
By harnessing AI for monsoon prediction, India positions itself as a global pioneer in digital agriculture. The system can be expanded to Rabi crops and extended to more states as accuracy improves.