Clean Future

NITI Aayog Along With IBM To Develop ‘Crop Yield Prediction’ Model

NITI Aayog has signed a deal with IBM India Pvt. Ltd some six months back to develop a prediction model for crop yields using artificial intelligence (AI).

As part of the first phase, the organizations are jointly developing this predictive model for 10 “aspirational” districts across the states of Assam, Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh.

While IBM will be using AI to develop the technological model for improving agricultural output and productivity for various crops and soil types for the identified districts, NITI Aayog will use the data insights generated through these AI models to help farmers and other stakeholders.

A large part of this agriculture platform has been developed by IBM researchers from India. IBM has been focusing on agriculture globally through ‘The Weather Company’, which IBM acquired three years back.

The company provides up to 26 billion weather data and insights daily via Weather’s application programming interface(API) and its own digital products like The Weather Channel (www.weather.com) and Weather Underground(www.wunderground.com).

In the agricultural sector, The Weather Company adopts a “whole ecosystem” approach which includes suppliers, seed and fertilizer companies, farmers, lenders and distributors.

But what exactly is this Platform?

Data is the first part of the platform. It comprises weather data collected from remote sensing and satellite imagery and drones that are being used in some parts of the world.

The second big part is collating localized weather data, which could also be historical. This data helps IBM build an electronic field record to understand the historical context and current scenario.

The third part is extracting insights from that data, which is where machine learning and AI are used.

The last piece is around “Decision Support”—exploring choices and making decisions. It’s here that AI (machine learning) helps in making decisions.

 

 

 

 

 

Reference- Live-Mint, IBM and NITI Aayog website, PIB

Exit mobile version