Caselet of India Vision 2035: Agriculture

Harjinder Kaur came from a family of farmers but was now the only one among her extended family to still do farming. She had done her masters in agriculture and was skilled in using the government and private sector systems and technologies to manage over a thousand acres of farmland. Ofcourse, only a small part of the thousand acres was her own, the rest is what she had contracted through the model contract act through the online government portal. Her family and other farmers had given their land to Harjinder for farming. 

Harjinder started her day by checking on the exception alerts coming from the array of sensors in her farm and from the cattle and chickens that she was rearing. She also got the analysis of her farm from the images taken from the Agricultural Drone company that was contracted by the government to take periodic check on farms in Punjab, which also provided early warning to the government on spread of pests and animal diseases. 

Harjinder also had to take a call on what to plant in a new part of her farm. She quickly checked the prices of various agricultural crops in the futures market, then checked on the database of how much of each agricultural crop has been already planted in the country and globally and then took advice from the AI system to decide what crop to plant so as to get the best returns. As she decided on her planting, she saw the autonomic tractor humming at a distance, ensuring that every inch of the farm is utilized by leveraging GPS and other data, while her micro-irrigation system that was hooked on to the precision farming system, continued to provide just the right amount of water to every part of her farm. The farm equipment came to her from the equipment-sharing company that was hooked to a government system that provide the backend to all such systems. And then she got an alarm from the systems that a tiny part of her farm that was producing cotton, has just been infected by pink ball worm. She took immediate action to contain the situation using the correct pesticides, so that only a small part of her crops got exposed to pesticides.

She ended her day thanking the background systems that helped her orchestrate her farming in a seamless manner. 

Caselet of India Vision 2035: Education

Meenakshi was doing well in 7th grade in her school but she had developed a sudden interest in hyperbolic geometry. While her robotic teacher was good in handling regular queries in the class, it was not programmed to provide special interest classes as that would disturb the rest of the class. The government had taken an early decision to develop silicone based robotic teachers that looked very real to children, driven by AI, to aide in teaching as clearly, it was impossible to churn out high quality teachers for the 200 million students of the country. In addition, there was a challenge to provide high quality higher education, vocational education and continuing education to a large population, that was hungry for education in a world where skills were getting outdated fast.

However, in this case, Meenakshi needed support from an expert in hyperbolic geometry, who could guide her to write her research paper on the ideas that she had developed. The National Education System, which powered the robotic teachers, automatically assigned her to Prof. Mithi in Itanagar, a world-renowned scientist in hyperbolic geometry. Prof. Mithi has been mentoring a few students who came from India, Egypt and Uzbekistan.  

In a few months, Meenakshi’s research paper on hyberbolic geometry was published in the National Online Open Journal as well as in the renowned Journal of Geometrical Calculations. Her research could be accessed freely by other students in India.