In the Future
This is a short story set in the near future.
Jeni, the eCommerce head at A1 Books who has just recently deployed a revolutionary system, iDarpan, is brimming with anticipation to witness its performance in action.
On a calm evening across the city, Arun, an enthusiastic reader and a regular patron of the A1 Books website, nestles comfortably for his nightly digital exploration. Unbeknownst to him, as his fingers dance on his tablet’s screen, his digital alter ego, ArunDT, springs to life in the iDarpan mirror world, a virtual echo of the A1 Books store.
The digital twin, ArunDT, is a precise replica of Arun’s literary predilections and buying tendencies. Interacting in real-time with A1 Books’ virtual catalog, ArunDT began to browse through a collection of the latest mystery novels—Arun’s favourite genre. It is a step ahead of Arun, anticipating his actions and ready with the next books Arun needs to buy.
Back in the physical world, Arun activates the A1 Books app on his tablet. A personalised message welcomes him, followed by a meticulously curated list of mystery novels, including beloved authors and promising newcomers that cater to his literary palate. His eyes sparkle with delight, wondering how the website has intuited his reading mood. He eagerly adds several books to his cart.
Back at the helm, Jeni observes the seamless operation from the control centre, a satisfied smile gracing her face. iDarpan is performing flawlessly. Its AI has astutely predicted Arun’s preferences, enhancing his browsing experience and increasing his likelihood of making a purchase. The promise of a superior, tailored customer experience is being fulfilled.
As Arun lingers on the site, real-time insights gleaned from ArunDT enables A1 Books to offer timely recommendations. The moment Arun concludes perusing a book description, a tactfully placed pop-up emerges, suggesting another novel that might pique his interest. Intrigued, Arun engages, eventually adding two more books to his cart than he had initially anticipated.
The results delight Jeni. Arun’s browsing session duration has lengthened by 15%, and the value of his purchase escalated by 30%. The credit, she knows, is due to the iDarpan system and ArunDT’s predictive accuracy. iDarpan is fulfilling its promise as an experience gamechanger and a profit amplifier – PxL, as Jeni affectionately dubbed it. It is the dawn of a new eCommerce era.
That night, Arun drifts to sleep, his dreams populated by the enthralling narratives and new worlds awaiting him in his new books. In the digital expanse, ArunDT emulates its counterpart, metaphorically shutting down for the day. However, in a few days, when Arun will be ready to reach for his tablet again to uncover more literary gems, ArunDT would be primed and prepared, steps ahead, armed with a perfectly tailored just-in-time email to seamlessly transition Arun’s commerce experience to his inbox. For Jeni, iDarpan is her secret weapon, working tirelessly to ensure that Arun and every customer’s experience with A1 Books is nothing short of exceptional.
The rest of this series is about how to bring this future to life.
I read the concept Digital Twins before and sketched how to apply it.
But, your story has made the operation extremely clear and I see how it can be applied to more complex but highly beneficial areas.
Let us apply it to the farming area.
A farmer Ramesh starts a crop of onions. His digital twin iRamesh does the same and follows Ramesh’s actions as well as the environmental conditions.
Many other farmers also start growing onions on their farms. iOTF’s (the digital twins of those other farmers) follow their actions. All these farms will need water, fertilizers, pesticides, electricity, manual labor, finances, and so on.
Rains may vary and the iRamesh and iOTFs follow the environmental and market situations. They alert Ramesh and the various other actors that support the farmers.
As time passes, the onion crops start to grow and their status is monitored. their growth depends on the environmental conditions, actions taken by the various actors, and the predicted quantity, quality, and date of onion yield is predicted by the iOTFs and the various actors are informed.
Depending on the situation, farmer Ramesh and every other farmer is informed on what he must do, what he may do, and so on. Ramesh and other farmers take certain actions. (hopefully, they will follow all the recommendations from the IOTFs, if they can.)
The conditions and the actions will determine the unit cost of the onions and the price that the farmer may get when the onions reach the market.
At the same time, the onion traders will look at the supplies they will get and how they can take them to the markets.The government is interested in the supply of onions and the price of onions.
{Onion crop is chosen as an example as the supply and prices of onions have led to the defeat of governments in some states some years ago! Voters are so sensitive to the supply of onions, tomatoes, potatoes, etc!}
The story applies to a variety of crops and markets.Supply chain businesses, traders, governments, agricultural service providers, and governments play their respective roles. The weather and environment also are actors. They can be predicted but they also act on their own whims.
Is it possible to apply the Digital Twins to the scenario?
I used the Farming operations as one example of the IOT-DT method I described over a year ago. I will be glad to share it with you if you are interested to look at it.
I believe that as people use the technologies and methods available to create novel applications, the economy will benefit and people will have jobs and better incomes. If they wait for things to happen by chance, people and the nation will be at the mercy of nature.