Farming gets big data deal

Mukesh Ranjan in New Delhi

Prime Minister Narendra Modi’s ambition to double farmers’ income by 2022 appears daunting. Various farm experts are unsure about strategies to increase the crop yield and cut costs to meet the deadline. The government has now turned to big data crunching and cutting-edge Artificial Intelligence (AI) tools.

NITI Aayog member Ramesh Chand recently submitted a report on agrarian distress, which noted that the agricultural income was not adequate to keep as many as 53 per cent farm households out of poverty. He has advocated a seven-pronged approach which covers improving crop productivity and livestock value-addition. He says such an approach can achieve a potential income growth of 75.1 per cent in seven years and 107.5 per cent in 10 years. He has also insisted that agriculture would need to grow at 10.50 per cent each year.

The Prime Minister has asked NITI Aayog to look for effective new technology intervention. The national think-tank body has roped in two information technology giants, IBM and Google, to work out models for real-time prediction of crop yield using AI and big data analyses. “Once the model is developed, it will enable officials of both the government and private extension-service providers to issue advisories to farmers in real time,” says senior NITI Aayog advisor, Dr T Haque. 

“The ten shortlisted Aspirational Districts will be invigorated with cutting-edge technological support to leap-frog development of farm-based economies,” says NITI Aayog CEO Amitabh Kant: The government has identified 115 Aspirational Districts -- the mirror image of areas covered under previous UPA government’s Backward Region Grant Fund (BRGF). These areas are far below the national average on developmental indices including health, education and rural infrastructure. Most such districts belong to Assam, Bihar, Jharkhand, Chhattisgarh, West Bengal, Odisha, Rajasthan, Madhya Pradesh, Maharashtra and Uttar Pradesh. In the northern region comprising Punjab, Haryana, Jammu & Kashmir and Himachal Pradesh, there are only six districts, including two in Punjab and one in Mewat (Haryana).

“The scope of this project is to introduce and make available climate-aware cognitive farming techniques and identifying systems of crop monitoring, early warning on pest/disease outbreak based on advanced AI innovations,” says a senior NITI Aayog official. It will also include deployment of weather advisory, rich satellite and enhanced weather forecast information along with IT and mobile applications with a focus on improving the crop yield and cost savings.

IBM will be using AI to provide all the relevant data and platform for developing technological models for various crops and soil types. NITI Aayog, on its part, will facilitate the inclusion of more stakeholders on the ground for effective last-mile utilization and extension, using the insights generated through these models.

“Most of the data related to soil, pesticides, fertilizers, weather and other farm input are generally scattered. The IBM model using AI will help us integrate all of them for farmers to make precision decisions,” says Dr Haque.

He says the real benefits can only be realised if the proposed model become easily accessible to farmers. But he also insisted: “It will certainly prove a boon for farm input and equipment suppliers, as the ready usable data will help them ensure timely supply so that farmers don’t waste time.”