Caselet of India Vision 2035: Healthcare

Jamuna Tudu was wearing the bio-sensor vest as she was overseeing her agricultural patch in Armo in Jharkhand. Jamuna was expecting and so the monitoring vest given to her by the PHC at Bermo. She was thinking about names to keep for the baby when she got a call from the Centralized Health Monitoring System that informed her that her vitals indicated she will be delivering soon and should move to the PHC. Her nominated ASHA worker and family also received a similar call, thanks to the AI system that was monitoring over 100 m expectant mothers and senior citizens on a continuous real-time basis, over a complex 7G mobile and satellite system. By the time she reached the local PHC, she received request for consent for the PHC doctors to access her medical records that were stored in the national health system. Her verbal consent over the phone ensured that the PHC was ready with all the medical information required to aid her in her delivery. It turned out that Jamuna had a special condition for which the Medical AI system recommended an expert opinion from Dr. Aleem, who was based out of Dhaka. 

Dr. Aleem specialized in the genotypes of the sub-population that Jamuna came from. Thanks to the trans-national medical interchange system built, it took a few minutes for Dr. Aleem to get into the records of Jamuna to provide his expert opinion on the medical situation. It turned out that Dr. Aleem would have to do an immediate procedure on Jamuna, which he immediately initiated using the remote robotic systems that allowed him to control the robotic surgeon at the PHC at Bermo. Thanks to the IT standards that have been agreed upon between the south Asian countries, it was seamless for Dr. Aleem to do the remote robotic procedure from Dhaka. 

The day ended with Jamuna being a proud mother of a healthy baby. 

Needless to say, the local school systems were automatically informed of a child who will join their school in four years’ time. In the meantime, Jamuna continued to get regular reminders for her child’s inoculation from the Central health System as part of the Cognitive Nation initiative.

Caselet of India Vision 2035: Blue Collared worker

Hargovind had taken up vocational training early in his career and took pride in being a blue-collared worked. He especially liked cleaning the drains of Delhi. So on new year day in 2035, he got up late to go for work and the city systems informed him of potential drain clogs detected. He did a quick visual inspection of the drains in the NDMC area using the built-in cameras and notices that the revelers of previous night and thrown in paper plates and paper spoons into the drains, with possibility of clogging them. Hargovind eased himself into his chair and remotely activated the mechanical cleaning “snake” that would slither into the drains and start cleaning up the material that would clog them. As the “mechanical snake” pumped out the bio-degradable clogging material from the drains, it got ferried straight into the micro-STP nearby which would convert the material into cooking gas for the nearby restaurants and into fertilizers for the NDMC maintained parks.

Hargovind thanked the prescient government for setting up the technical orchestration that helped cameras, sensors, robots and communication technologies to help him accomplish his job without getting into the drain as his predecessors would do.

India Vision 2035: White-collar Workspace

                           Caselets of how India should be in Year 2035

In 2035, India and the world would have fast moved into the gig economy playing a considerable role. So when Nazia, a digital supply chain expert, got a mandate from a leading FMCG company to re-design their hybrid supply chain within the next 2 months, she quickly put together the details of the kind the people she would need to deliver on the project. She then opened up a project in one of her preferred online systems which in turn was linked to the national human resource database, that was hosted by the government. 

In the next 10 minutes, with the help of AI-aided systems, she could identify the right set of people who will join her project, fix their rates and schedule the project workplan. Nazia was able to finish off her project within the 2 months with a team of 7 people whom she never met face to face, and was aided by the online systems, processes and open data available from private sector, institutions and the government, including anonymous taxation data, that helped her design an extremely optimized supply chain for her client. 

Her system would contribute to increasing the efficiency of the national economy.