As our country is acing towards modernisation in each and every sector, be it private sector, automobile sector, corporate sector; then why let the agricultural sector stay behind the curtains of transformation going around everywhere. For a fact, the agriculture sector contributes around 17% of the GDP and more than 60% towards employment of our country.  Over 58% of the rural households depend on agriculture as their principal means of livelihood, according to an IBEF report.

WHAT IS THE NEED OF AI IN AGRI SECTOR ?

The thought of introducing Artificial Intelligence in the agriculture sector would bring about a revolutionary change not only in our country but to the lives of each and every farmer as well. Artificial Intelligence (AI) along with other digital technologies, will play a key role in modernizing agricultural activities and realising the goal of doubling the farmer’s income by 2022. The global ‘AI in agriculture’ market size is expected to be worth USD 2.6 billion by 2025.  Artificial intelligence (AI) being a game-changer in other industries, the Indian government has realised the importance and started to leverage this technology in developing the sector.  Doesn’t it seem to be a great achievement?

Talking about how AI can flourish our agriculture sector, so it would basically target the important factors that helps in the growth and production of crops like climate, water management, weed control, seeds production etc. There are many companies and start-ups who are already working under this to prevent the farmers of our country suffering from crop failure due to unforeseeable circumstances like unpredictable climate changes, pest attack, water scarcity, forest fires etc.

FACTORS ON WHICH THE AI WOULD FOCUS ON-

  • Improving crop productivity: Climate change has resulted in making traditional agricultural outdated, especially for forecasting weather patterns that determine farming practices for the season. The usage of predictive analysis with the help of AI could be extremely helpful for farmers and help determine appropriate crops to grow in a favourable climate on a productive terrain and the sowing methodology to enhance productivity and reduce costs.
  • Soil health monitoring: Soil health comprising of an adequate level of moisture and nutrient holds the key to getting the best yield. Distributed soil monitoring performed via image recognition and deep learning models can be used to take corrective measures to restore soil health. Historical data about monsoons, local snapshots of the farm, crop-output information, history of soil health, and more serve as inputs for the creation of AI models.
  • Optimization of pest and weed management: AI can be used for predicting the behaviour of pests which can be beneficial for advanced planning of pest control. Efficient pest management leads to lower crop and environmental damage. A combination of remotely sensed data, efficient image classification tools, and other relevant data points can be used to distinguish the weed from the crop and will confine the usage of weedicide only to the areas that require treatment. Remote satellites can monitor crop health and also warn against pest attacks. An AI-supported technology called ‘See & Spray’ developed by US company is a weed controlling technology that can reduce expenditure on weedicides by 90%.
  • Price realization for farmers: Only about 6% of farmers in India get benefits of Minimum Selling Prices (MSP). A better price realization for farmer would be a boon to their lives. Predictive modelling using AI can be instrumental in presenting more accurate demand-supply information and predicting demand for agricultural produce to farmers. Many of these start-ups are leveraging technologies like AI, machine learning, etc. for improving efficiency, yield, speeding up agricultural finance, and other functions that are vital for India’s agricultural growth
  • Water Management: Efficient water management in agriculture can have a huge impact on the looming problem of water scarcity. Water usage in agricultural land can be optimized by using thermal imaging cameras that continuously monitor if crops are getting sufficient amount of water.

As mentioned earlier, the few start-ups which has already started working upon are-

Intello Labs: A Bengaluru based startup by IIT-Bombay alumnus Milan Sharma claims to provides advanced image recognition technology that can recognize objects, faces, flora fauna. The company mainly focuses in providing agricultural product grading and alerts on crop infestation.

Microsoft India: The app sends sowing advisories to participating farmers on the optimal date to sow where the farmers don’t need to install any sensors in their fields or incur any capital expenditure. All they need is a feature phone capable of receiving text messages. Microsoft in collaboration with ICRISAT developed an AI Sowing App that uses machine learning and business intelligence from the Microsoft Cortana Intelligence Suite.

CHALLENEGES

Agriculture is one of the most difficult sector where AI could work upon because within a single field, the conditions are changing from one section to the next in the blink of an eye. The problem of deploying machine learning and artificial intelligence in agriculture is not that the scientists lack the capacity to develop programs and protocols; the main cause of concern is that NO TWO ENVIRONMENTS WILL BE EXACTLY ALIKE, which makes testing, working and validation more laborious as compared to other sectors. Although AI and machine learning are teaching us many things about how to understand environment, we are still far from being able to predict critical outcomes as no one has able to tackle out God’s creation not even machines. AI will definitely bring the digital agriculture revolution but the road ahead is not very smooth as people think it to be. No doubt, barriers would be there but yes as every big change passes through it.

GOVERNMENT’S TAKE ON AI IN THE AGRI SECTOR

Seeing that the Agricultural sector exports constitute 10% of the country’s exports and being the fourth-largest exported principal commodity category in India.

The Government planned to introduce a scheme called AGRI-UDYAAN where it would help start-ups connect with potential investors. NITI Aayog came up with a National Strategy for Artificial Intelligence in India, which aims at focusing on economic growth and social inclusion. According to Agriculture Secretary Sanjay Aggarwal, “AI and big data are going to be a game-changer in the agriculture sector and the government is aiming to collate about 80% of such data by 2020.” The government of India has signed an MOU with IBM to use artificial intelligence (AI) to secure the farming capabilities of Indian farmers. IBM has started a pilot study to use AI-based technology and satellite technology to monitor the agriculture sector of the country. The pilot study will be conducted in states like Madhya Pradesh, Gujarat and Maharashtra. This initiative was aimed at improving the future of farming by harnessing multiple data points and combine predictive analytics, AI, satellite data, and IoT sensors to give farmers insights on ploughing, choosing crops, spraying pesticides, and harvesting.

PMFBY (Pradhan Mantri Fasal Bima Yojana) is a government-sponsored crop insurance scheme that integrates multiple stakeholders on a single platform. To improve the crop sector, the government will now envisage the use of innovative technologies like AI, remote sensing imageries, and modelling tools to reduce the time lag for settling of claims of the farmers. By analysing the data collected, the scheme aims at increasing the crop insurance penetration in India by increasing farmer awareness and reducing farmer premium rates.  The scheme will also encourage farmers to adopt innovative technologies and modern agricultural practices. It also ensures the flow of credit to the agriculture sector, which will contribute to food security, crop diversification and enhancing growth and competitiveness of the agriculture sector besides protecting farmers from production risks.

By leveraging the benefits of AI, the government of India has rolled out a scheme — PM-KISAN, where every farmer is going to receive Rs. 6000 annually to support their farming abilities. The government is aimed to leverage the huge amount of collected data by several agri-schemes and use the same to better target the farmer who requires the benefit of PM-KISAN.

CONCLUSION

With the recent advancements in technology coupled with conducive government policies, we have seen many agtech startups emerge in the country which is a great starting point for the penetration of advanced technologies like AI in agriculture. The AI technology is used to the maximum so that both farmers and consumers can make the most of it without reducing the manpower or increasing the unemployment. Instead, AI comes as a great boon to the agricultural sector which is heavily dependent on climatic conditions which are often unpredictable. the modern technological advancement reduces the troubles faced by farmers like poor irrigation facilities, floods, droughts, pest attack, etc. Also, there are 1.8 per 100,000 total population of farmers in our country that commits suicide due to crop failure and debt burden issues. At the end of the article, the mentioned facts and figures would make one realise how important is Artificial Intelligence in our country. Other countries adopted this technology way before than us, Australia being the first and now it’s our time to see the digitalisation in our agricultural sector.

This article has been written by Shreya Singh studying at Janki Devi Memorial College (JDMC).

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