India’s agriculture challenges can be addressed with AI

Artificial intelligence (AI) and digital technology have the potential to support our farmers in overcoming a range of challenges. These technologies provide farmers with enhanced decision-making as one of their core benefits. Increased access to markets, inputs, data, guidance, loans, and insurance would benefit farmers in India’s agricultural sector. Smallholder farming in India may benefit significantly from having access to AI models that may boost farm revenue, optimize input costs, and de-risk agriculture through quick data intervention.

Before farmers fully embrace digital technology, it is crucial to educate them and help them realize the advantages it will bring to agriculture. The success of this endeavour depends on machine learning (ML) and artificial intelligence (AI). For the usage of AI in agriculture, data points are crucial. These technologies can assist in tracking a variety of data, including input application, the area being produced, farm borders, farmer profiles, crop and soil health, losses, and hyperlocal weather. A complete value chain that includes pre- and post-harvest, quality, grades, traceability, and failures, as well as retail and export markets, will also be created using digital technology.

A strong emphasis on agri-tech might greatly help our nation. Accurate weather, insect attack, harvest, and agricultural output forecasting also need a data-centric strategy. The rapid acceptance of these technologies in farming is crucial for a nation like India to ensure speedier adoption.

The challenges

Making accurate forecasts is difficult for several reasons, including access to high-quality data and modelling. Additionally, rather than focusing on data modelling, most startups spend excessive time and energy collecting data. Utilizing already available data is essential, as is developing a public ecosystem of data repositories.

It’s also necessary to create centres of excellence that combine data scientists, soil scientists, agronomists, meteorologists, hydrologists, and other multidisciplinary experts to enhance AI technology in agriculture. While the procedure could be time-consuming and expensive, the long-term advantages will be enormous. Additionally, AI models may provide rapid, affordable, portable, and accurate solutions for determining crop health, soil moisture, nutrition, and other variables.

Additionally, we can assure digital adoption and educate small landowner farmers using information and communication technology (ICT), blockchain, Internet of Things (IoT), AI, and machine learning (ML). Stakeholders from every link in the value chain will be able to contribute to developing a sustainable, self-sufficient, and successful agri-ecosystem using technology.

Digitization-based transformation

The bulk of Indian farms are tiny; therefore, they lack the resources needed to obtain the requisite technological knowledge, skills, and other essential inputs. A resource-sharing initiative, or ″Digital Cooperative Society,″ will be very beneficial in this regard. Collaboration is essential to give farmers access to the benefits of digitization, AI, farm mechanization, and ML.

To tackle data challenges, permitting more PPPs and collaborations amongst commercial research institutes is crucial. Another essential element is coordinating with governmental organizations to establish information repositories that act as sources of information. We must also develop location-indifferent AI algorithms and open up the agricultural ecosystem, and they will support device interoperability as a unit.

It is essential to think about developing inclusive and uniform agricultural policy and fostering the development of tools that will help farmers engage in digital transformation. Farmers will benefit from the training these facilitators provide to maximize the usage of available technologies during cultivation.

Collectivise and digitize

A new generation of agricultural startups and AgriTech firms are making significant investments in digital initiatives to solve these difficulties. In order to choose the appropriate solutions, they want to harness these technologies and use them for precision farming, improved crop monitoring, soil health, and plant health.

Indian agriculture has to be collectivized and digitalized to become more sustainable. AI is a significant facilitator in all of these initiatives. It can potentially be a valuable tool for farmers to boost output, reduce costs, and raise productivity. Agriculture will undergo a radical change as a result of AI and ML.

By providing up-to-date details on the various factors that impact productivity, Artificial intelligence (AI) driven solutions can simplify the processes and be advantageous for both. Such technologies will significantly alter the situation by enhancing food management and reducing losses along the whole value chain, from the farm to the ultimate consumer. According to an ICAR-CIPET analysis, it will also significantly affect the avoidance of commodity losses, which are predicted to total about INR 92,651 crore. Using cutting-edge technologies to reduce such food loss would also boost farmer revenue.

A combination of real-time sensor data and drone observation analytics may be very advantageous for smallholder farmers and product development companies. Pesticide applications in fields may be automated with drones equipped with AI computer vision. With real-time information, spraying may be more precise and effective regarding the area and volume to be covered. Since they improve yields, which lead to better income, as well as our farmers’ health and quality of life, deploying such technologies can result in considerable cost savings for smallholder farmers.

Farmers will be able to make significant decisions based on information thanks to the application of AI in agriculture. Farmers and agri-solutions providers may benefit from a data-centric strategy as well since it will help them determine how financially successful a crop cycle has been.

According to a new report, AI and technology can help Indian agriculture overcome challenges

According to researchers, the entire system must change to a comprehensive strategy based on indigenous and traditional agricultural knowledge and innovative, intelligent farming practices, including applying Artificial Intelligence (AI) technologies and techniques. Even though agriculture, which employs around 58 per cent of the workforce, continues to be a top priority, technology adoption in the industry is at a crossroads due to some issues across the value chain.

According to research by PwC & FICCI, India’s agriculture industry is facing several issues throughout the value chain even though the country is in a transitional stage with an emphasis on technology integration for improved operations.

The paper ″Redefining Agriculture Through Artificial Intelligence: Predicting the Unpredictable″ claims that in order to overcome these difficulties, disruptive interferences are required, which technology solutions may offer.

According to the paper, the entire agricultural system has to change to a holistic strategy based on indigenous and traditional farming knowledge mixed with innovative, clever farming methods, including the use of Artificial Intelligence (AI) technologies and techniques.

According to the paper, the use of AI technology would open the door for increased output with optimal resource use, as well as make predictive analysis, crop health management, quality, and traceability easier, among other things. The adoption of novel and revolutionary clever agricultural techniques in the nation is reportedly progressively emerging as a significant trend.

The report lists a number of actions being taken to promote intelligent farming practices, including resource management that is technology-driven, supply chain modernization for the ag industry, climate risk mitigation plans, digitization of farm collectives as farmer producer organizations, the emergence of a startup ecosystem, and government initiatives in digital farming.

The global Agri value chain is being redesigned as a result of recent technology breakthroughs in both the upstream and downstream segments. The report claims that the use of cutting-edge AI technologies like the Internet of Things (IoT), machine learning (ML), cloud computing, statistical computing, deep learning, virtual reality (VR), and augmented reality (AR) is enabling the industry to overcome issues with productivity, quality, traceability, and carbon emissions while boosting profitability.

Uncrewed aerial vehicles (UAVs), which also go by the name of drones, are utilized primarily in agriculture.

The usage of drones in farming techniques is anticipated to rise as the nation’s agricultural sector expands further, with numerous entrepreneurs investing in affordable drones that may assist farmers, advance their expertise, and generate employment for young people in rural areas. According to the statement, the government is also facilitating an institutional ecosystem for agritech firms through incubators. It has embraced the slogan ″AI for everyone″ through the NITI Aayog and provided sweeping proposals for fostering India’s AI ecosystem.

Despite advancements in creating and sustaining an ecosystem powered by AI, the research notes that there are still a number of problems and difficulties in the agriculture industry that need to be resolved in order to ensure a seamless transition.

A small pool of AI and sectoral experience, current gaps in public AI research, low data quality, and lack of access to data, as well as a lack of coordination and cross-border collaboration, are the main issues with the agriculture sector’s AI innovation and technological elements. In accordance with the report, these difficulties can be overcome by implementing a ″3S″ strategy that uses the levers of Scale, Skill, and Service to transform AI into Agri intelligence, resulting in the ecosystem’s broad adoption of the technology through the joint efforts of key actors acting as change agents.

India’s difficulties and potential with AI in agriculture

In India, agriculture has long been the country’s primary industry. There is proof that agricultural activity existed even before the Indus Valley Civilization, between 8000 and 6000 BCE. The great Indian civilization flourished with a rich culture of agriculture and related industries because, most crucially, the traditional agricultural techniques we have been using have always strived to maintain the balance between farming and nature. Moving forward to the present, we observe the farm industry’s various ups and downs during this time.

The impact of the Industrial Revolution on Indian agriculture and related businesses shows sharply in the 19th century, a time of both good and evil rulers, exploiters, and supporters. Following independence, there have been several colourful revolutions: white (dairy), green (industrialization – usage of hybrids), yellow (oil seeds), and blue (fishery). Additionally, they have pushed certain crops, farming techniques, and related sectors with the goal of raising production.

Therefore, it should come as no surprise that the fourth industrial revolution will have an influence on global agriculture as we witness so many new technologies emerge. The technology divide between nations has significantly narrowed as a result of globalization, and change is occurring at an alarmingly quick rate.

Numerous businesses, including both established industrial giants and fresh startups, have already recognized this potential and are bringing AI/ML, IoT, autonomous driving, and a plethora of other recently available and reasonably priced technology to the field of agriculture.

Here are some examples of use cases for AI in agriculture that we have seen:

• Weather forecast: The most apparent application of AI is in weather forecasting since climate affects agriculture globally. There are several similar attempts throughout nations to forecast the weather, both at the level of the government and by businesses like IBM.

• Crop Monitoring with Image Processing: Whether we collect photographs with a robot, a drone, or a satellite, there are instances when image processing is being utilized to evaluate the crop. In addition to monitoring for pests, yield size, yield forecast, soil evaluation, and a variety of other use cases, this also incorporates real-time crop vegetation index monitoring using satellite photos. Robots being developed for harvesting produce include a variety of machines.

• Tractors without drivers: Due to a shortage of farm labour, several businesses throughout the world have begun to produce tractors without drivers. Even Mahindra and Mahindra Ltd., India’s largest tractor maker, debuted its first autonomous tractor in September 2019. Via GPS-based technology, Mahindra’s tractor can navigate itself, pick up equipment from the ground, recognize the limits of a field, and be controlled remotely using a tablet. But from the standpoint of India, the crucial query is: Will Indian farmers be able to employ and benefit from the newest instruments and techniques? Will they be inside their budgets?
   

Indian agriculture’s current state

While we are enthused by what human minds are capable of, we also find ourselves reflecting on the reality of Indian agriculture. As we all know, our farmers still bear all of the risks associated with their business operations. They are totally reliant on outside factors to produce anything on their property, including weather, lack of trained labour, paucity of water, money to buy seeds, fertilizer, pesticides, and so forth. Due to a lack of storage facilities, even the revenue from their products is not assured, and because it is perishable, they must accept whatever amount they receive.

The majority of Indian farmers have extremely tiny landholdings, which is crucial when using technology since they cannot afford the price of purchasing seeds and other necessities. Can we really expect them to invest in a costly, unproven, and perhaps unreliable technology in such a situation?

What about sustainability?

This is another crucial factor that agriculture frequently overlooks. It is common knowledge that the usage of fertilizers and pesticides contributes significantly to global pollution. A significant quantity of food is wasted in attempts to industrialize agriculture through increased production, standards for the production of a particular size, colour, etc., while on the other hand, many people do not receive a daily square meal.

There is growing support for the idea that having a lot of food with little or no nutritional value is not significant. Instead, it is necessary to have a sufficient amount of produce that has the fewest contaminants and offers the most nourishment. Today’s technology doesn’t take this reality into account to a large extent. Therefore, despite an emphasis on developing technologies to precisely target fertilizers and pesticides, we are still a long way from a breakthrough in sustainable results.

Technology as a facilitator

Science and technology have always been a topic of dispute, but as time goes on and we look back, the more we realize that it is up to us to decide whether they are a blessing or a curse. Therefore, it is exceptionally likely that enhanced agriculture will be made feasible with the application of the appropriate number of technologies that are geared toward a sustainable future. Examples of this may include using AI/ML to accurately forecast local weather, guiding farmers toward eco-friendly pest management practices, using robots to harvest in multi-crop farms, and using AI to estimate demand based on available supplies, exports, and local requirements, among other things.

The most significant thing is that technology can make education and training possible, enabling the current need for an essential trained workforce. And while doing this, the course’s sustainability components might be seen as its primary focus. The development of these skills has the potential to provide jobs for at least 10 lakh people while also reducing the population density in urban regions, improving the sustainability of both urban and rural areas.

Technology is also necessary to enable farmers to view agriculture as a business and to utilize it to raise their profits in a sustainable manner. As a result, farmers will be able to make a profit, and more people will find farming to be a lucrative industry.

Data’s function

It is generally known that AI totally depends on the quality of the data that is available, despite the fact that we view AI as a technology with the ability to provide us with game-changing solutions in the sector of agriculture. Obtaining the pertinent information at the farmer level in the Indian setting is also a great difficulty. People are reluctant to disclose their data, which makes it challenging to obtain accessible data. Thus, data collecting also requires a technological solution. We must come up with automated methods for data collection that don’t invade the farmers’ privacy.

Indian farming methods

Real-world problems must be resolved through technology. It must be relevant, accessible, inexpensive, feasible, and sustainable. Although the globe can be seen as a single family, most problems are still local and must be resolved locally. Therefore, our goal at Tech Mahindra’s Makers Lab, where agritech is a crucial focus of study, is to develop technology that can significantly improve the lives of farmers.

For instance, we are developing a solution to assist farmers with managing their businesses, seeing their own accounts, receiving crop-related recommendations, engaging in training, preventing the intrusion of wild and domestic animals onto their farms, and much more. In order to determine whether our rich Indian ancestry has the solutions to some of the problems out there, we are also diving into ancient Indian culture and farming methods.

For instance, according to specific research, the Panchang (the Hindu calendar and almanac) offers a very accurate prediction. As a result, we are investigating any factors that we might be able to incorporate into our system for forecasting the weather.

Furthermore, we want to provide solutions that are easily accessible, locally feasible, and highly economical. In addition to developing our own solutions, we also advocate collaborating with partners and startups whose goods are consistent with our concept of promoting sustainable agriculture. This is done as part of our open innovation culture. In order to accomplish this, we collaborate with experts in agriculture who have years of hands-on experience working with farmers.

Conclusion

In conclusion, we think that the world of AI/ML, IoT, and more may actually bring a step-change in the lives of farmers and really alter agriculture, bringing us to a sustainable future through a two-pronged strategy of employing the newest technology and a sustainable path.