Updated: November 26, 2020 7:20:22 pm
“I see a big role for AI in empowering agriculture, healthcare, education, creating next-generation urban infrastructure and addressing urban issues,” Prime Minister Narendra Modi said while inaugurating the Responsible AI for Social Empowerment Summit, RAISE 2020. Artificial Intelligence-based agri-tech applications are set to unleash value in agriculture, especially in wake of the recent farm reforms that have opened doors to private sector investments in agriculture.
In the financial year 2019-20, Indian agri-food tech start-ups raised more than $1 billion through 133 deals. India’s exports of agricultural products rose to $37.4 billion in 2019 and with investments in supply chain and better storage and packaging, this is set to increase further. All these steps will go a long way in ensuring remunerative prices for farmers and reduce agrarian stress.
This growth in agricultural output and productivity is being further enhanced by investments in technology. Disruptive technologies like AI are making big positive changes across Indian agriculture, and an increasing number of agri-tech startups in the country are working to develop and implement AI-based solutions. Globally, AI applications in agriculture reached a valuation of $852.2 million in 2019 and this is estimated to grow to almost $8.38 billion by 2030, a nearly 25 per cent growth. The Indian agri-tech market, presently valued at $204 million, has reached just 1 per cent of its estimated potential of $ 24 billion.
Use of technology in agriculture will improve farmers’ access to markets, inputs, data, advisory, credit and insurance. Timely and accurate data coupled with analytics can help build a robust demand-driven efficient supply chain. With the use of sensors, photographs through phones, IoT devices, drones and satellite images, agricultural data can be collected and matched with weather data, soil health card data, mandi prices and help build predictive models that can greatly enhance decisions about seeds, fertilisers, pesticides that are of critical importance in both pre-harvest and post-harvest stages. Most of these AI models are low-cost and affordable and can add a lot of value to the agriculture ecosystem.
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India has made rapid strides in the services sector, yet, agriculture continues to employ 49 per cent of the workforce and contributes 16 per cent of the country’s GDP. Improvement in agriculture would, therefore, positively impact the well-being of a very large section of the Indian population, apart from delivering food security to our country. Feeding over a billion Indians on limited land resources is a big challenge, a task that requires technological intervention on a large scale, to enable a giant leap in agricultural productivity.
Indian agriculture is faced with multiple challenges like high dependence on monsoon, resource intensiveness – heavy use of resources (water, inorganic fertilisers and pesticides), degradation of land and loss of soil fertility, and low per hectare yield, among others.
AI can play a catalytic role in improving farm productivity, removing supply chain constraints and increasing market access. It can positively impact the entire agrarian value chain. It is estimated that AI in global agriculture could be a $4 billion-opportunity by 2026.
Greater use of AI would increase mechanisation of Indian agriculture. It would increase productivity by introducing precision agriculture. Indian agriculture technology startups are trying to integrate AI-based technological solutions across a range of use cases such as monitoring crop productivity and soil fertility, predictive agricultural analytics and ensuring supply chain efficiencies.
In predictive agricultural analytics, various AI and machine learning tools are used to predict the right time to sow seeds, get alerts on impending pest attacks etc. AI in agriculture powers the optimum utilization of farming data to help devices like smart drones, autonomous tractors, soil sensors and Agri-bots function and deliver superlative efficiency in farming.
In what is a great example of innovation for agriculture using AI, industry has joined hands with the government to develop an AI-powered crop yield prediction model to provide real-time advisory services to farmers. The system employs AI-based predictive tools to help increase crop productivity, enhance soil yield, control the wastage of agricultural inputs and warn of pest or disease outbreaks.
This system uses remote sensing data provided by the Indian Space Research Organisation (ISRO), data from soil health cards, the India Meteorological Department’s (IMD) weather prediction and analysis of soil moisture and temperature etc. to give accurate information to farmers.
This project is being implemented in 10 aspirational districts in the country across Assam, Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh.
Similarly, an increasing number of Indian startups are already implementing AI-based solutions in agriculture. A startup has used data science, AI and machine learning algorithms, along with data sets from ISRO to assess damage to crops, compensation payable based on value of the damage that has taken place. Questions around what is being grown, what is the damage, what would the value of the crops damaged be, are answered with reasonably high accuracy.
Another AI startup in India maps farmers’ zones in remote areas, answering questions like who has been farming which land, what is being grown, what is the quality of soil on the land, with great accuracy. Crop insurers, seed suppliers, state governments all want this data and it’s possible to build a business model around this as the data and information has value for everyone. Farmers are also able to get all this valuable information and insights which helps them in making better decisions about their agricultural practices and create value.
other Agri-tech startups who are using predictive analytics and machine learning to solve the problem of volatility in input prices and suboptimal input utilization. Imaging and AI, traceability solutions are being developed for large scale quality testing and post-harvest produce handling and monitoring.
Data is helping to create platforms for price transparency to check malpractices in the supply chain. Similarly, agricultural bots (ag-bots) and drones are being developed to ensure seamless execution of cultivation and harvesting.
In order to help these AI solutions scale, what is needed is to increase investments – both public and private – especially from venture capitalists.
With the recent reforms in the Agriculture sector, there is a likelihood of increased investments in contract farming and infusion of technology for better yields and productivity. This will further push the adoption of AI in agriculture. The recently concluded Responsible AI for Social Empowerment Summit – RAISE – 2020 Summit has helped provide a platform for global stakeholders to come together to finalize the roadmap for using AI for public good. As many as 321 global AI experts from 21 countries, and sectors including agriculture, converged onto the RAISE 2020 platform to firm up plans for developing path-breaking AI-based tools and for improving the adoption of AI across sectors.
Thanks to the diversity of its soil types, climate and topography, India provides a great opportunity for the data scientists and AI experts to develop state of the art AI tools and solutions for agriculture. Indian farms and farmers provide vast and rich data to help create AI solutions for not just the country but the world at large. And this is one of the factors that makes the opportunity for AI in Indian agriculture unparalleled.
The writer is CEO MyGov; President & CEO NeGD; MD & CEO Digital India Corporation (DIC), Government of India
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