As the world population continues to grow at an annual rate of 1.05 per cent, the global demand for food crops has also grown exponentially. According to the United Nations, the world population is predicted to increase to 9.8 billion by 2050. Consequently, crop production will demand growth between 60 to 100 per cent to feed everybody on the planet, creating tremendous challenges for the agricultural industry. The present projections point that the world is at risk of Malthusian Crisis, a state in which population growth outpaces the increase in food supply resulting in large scale famines. 

The lack of arable lands still remains a huge concern. However, it's the urbanisation driven shortage of human resources to carry out day-to-day farming activities is what needed to be addressed immediately. More and more farmers are today facing the difficulty of supervising and managing acres of land. And for better farm management and to increase productivity, they are turning towards emerging technologies such as AI, IoT, and drone.

By incorporating all the technologies, in conjunction with AI, we are today able to answer many of the age-old questions in agriculture such as:

• Which crops to focus on?
• Which crops are less prone to being attacked by weeds?
• Which plants can be influenced by the weather?
• How profitable would it be for the farmer to divide his farm into several zones for diverse activities, such as poultry, livestock, horticulture, etc.?

Furthermore, AI could also be used to incentivise the youth to go to the rural side and experience agricultural activities first hand.

AI-powered IoT and drones: One stop solution for effort-less farming?

Today, it has been proven that a combination of AI technologies such as machine learning, computer vision, along with IoT and drones, can help farmers increase output and expedite the production of the crops. When combined with drones, computer vision technology can render a wide range of indispensable data that can help farmers find a better time for harvesting and as well as make irrigation process seamless. 

These drones can also detect an early infestation with the same technology and identify appropriate pesticide according to the problem. They can also scan the entire land for infestation and spray the pesticides only on the areas that are infested, thus helping enhance the crop yields and minimising the additional cost incurred in a manual calibrating quantity of pesticide. 

Furthermore, as these drones can circumnavigate as high or as low as needed, they can help farmers identify issues that can be overlooked by the human eye and provide essential data, such as:

• Revealing specific patterns on the crops which may act as a catalyst for pest infestations, as well as colour variation and irrigation leaks. 
• Land geography and soil composition data with 3d-mapping, which could help farmers zero in on the best place to sow the seeds.

Use-Cases

As many of the startups and companies are starting to rely on AI and drones to boost agricultural production, it is vital to analyse the challenges the farming industry facing and how these new generation tools are becoming a transformative force.

• Fasal: It is a climate-smart, precision AI-powered, agriculture platform that has been using IoT and data science as its building blocks to provide factual information to the farmers at a precise time. Fasal helps in providing real-time data about crops and weather, pest and disease management, irrigation management etc., by capturing the land data and uploading it to the Fasal cloud platform, the data is then analysed and presented on the app to give farmers an analysis of the crop's health for data-driven decisions and strategy. Farm data is further used by Fasal's prediction engine to predict a good scenario for the crop's ideal growth conditions and other resource necessities such as irrigation, fertilisers and pesticides etc. Using Fasal, farmers have been able to mow down their crop's disease management cost and irrigation cost by 50%.
• Werobotics: Werobotics (a division of India flying labs) has been educating the farmers from the tribal village of Dahanu-Palghar region in Maharashtra, in using advanced and feasible drone-based technologies on their lands and orchards for remote sensing the data. So far, farmers from that area have already acquired the knowledge of crop rotation, fish farming, organic agriculture, bio-waste management, and bio-based crop protection utilising drones. 
• Garuda Aerospace: Garuda Aerospace is a drone manufacturing start-up providing solutions-based services to several public departments such as forest department, police department, electricity department, agricultural department etc. In the agricultural space, Garuda is using its drones for the purpose of pesticide spraying to help farmers in improving the efficiency and productivity of crops. Currently, the team at Garuda is extensively working with the government of Tamil Nadu to provide sanitation and surveillance services using drones in the fight against Covid-19.

Despite some challenges in Indian agronomy industry such as lack of agricultural data, agritech policies and frameworks etc. these startups can leverage technology in the market domains of retail, B2B, B2C and other digital agronomy channels. It can also address input challenges of agriculture in India by providing apt information, techniques and efficiencies to farmers both for pre- and post-harvest scenarios.

Pitfalls

From the above use case, one can easily conclude that there are tons of possibilities for farmers to make the most of these emerging technologies and set their new agricultural plan in motion. For many traditional farmers, though, this degree of technical knowledge may seem quite baffling. Hiring third-party service is one solution but in the part of the farmers, hiring third-party resource means spending even more – an idea that makes agriculture drone technology even less attractive. Thus, it would be vital to impart fundamental knowledge to them or their family members on managing this technology. Veritably, this domain could also help women if we provide enough training to them to make this domain more female-oriented and help them participate in more skilled labour sectors.

Conclusion

Despite the shortcomings in the agricultural system, the advent of drones in collaboration with other AI technologies can help farmers generate more food and empower them by efficaciously improving the entire cycle of crop production using a data-driven process. Even though these technologies are still to be adopted by the agribusiness world on a global scale, what is more important is that these technologies are already on a path to mould the way we cultivate crops and to provide a solution to feed billions of people. With the impact of AI in agriculture, it would be interesting to see how this industry will soon evolve and how the farmers are going to adopt these technologies for a better farming experience.