Digital agriculture: AI, machine learning and robotics can help maximise returns for farmers, says report bl-premium-article-image

K V Kurmanath Updated - February 20, 2024 at 04:36 PM.
 The CII-EY whitepaper calls for immediate efforts to deploy AI solutions, drones, data analytics and other digital technologies to help farmers efficiently use water, fertilisers and map soil health.

With small-holder farmers comprising the majority of the farmers and limited irrigation facilities posing serious challenges, it is time for policymakers and governments to adopt artificial intelligence and other deep technologies, including machine learning and robotics, to ensure efficient use of resources and maximise returns, a CII-EY whitepaper on digital agriculture has said.

These technologies can also help them face price and weather fluctuations, it said. The whitepaper called for immediate efforts to deploy AI solutions, drones, data analytics and other digital technologies to help farmers efficiently use water, fertilisers and map soil health. The report was released at the just concluded CII AgriTech South conference here.

“We need to establish standardised data formats and encourage open-source AI solutions. We should develop modules and equip farmers and rural youth with required AI training in local languages. In order to promote usage of AI-based solutions and technologies, the government can consider offering targeted subsidies for manufacture of affordable devices and develop l internet access,” it said.

Focus on capabilities

The report – Revolutionizing Telangana’s Agriculture: A Digital Approach – mapped different areas where AI and other digital technologies could be deployed.

“The focus isn’t merely on adopting technology arbitrarily but on utilising its capabilities to establish a sustainable, productive, and resilient agricultural environment,” C Shekar Reddy, Chairman, CII Telangana, said.

“Machine learning algorithms can analyse vast amounts of soil data, including composition, fertility, and moisture levels, and recommend optimal crop choices for specific fields. This data-driven approach minimises risks and maximises yield potential,” Ritvik Kashyap and Vanshika Arora of EY, said in the report.

The report felt that data crunching of historical data and real-time weather patterns would help in predicting future climate trends and potential risks.

Capitalise on opportunities

“Farmers can utilise this information to make informed decisions about planting schedules, crop varieties, and resource allocation, mitigating weather-related losses,” it said.

“AI can analyse market trends and predict crop prices, empowering farmers to optimize planting decisions for better returns. This foresight allows them to adapt to market fluctuations and capitalise on profitable opportunities,” he said.

The report asks the stakeholders to roll out pilot projects to demonstrate the value of AI in agriculture and encourage wider adoption. It also wanted to facilitate skill development programmes to equip farmers with the knowledge and skills necessary to operate and leverage these technologies effectively.

Published on February 20, 2024 11:06

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