Registering Key Experiences of drones, robots and Machines

Robots look the same when configured in an industrial location. But they are all meant to go to new places. They all are meant to work with distinct unique people, as we all are distinct. Humans would make them work across different domains, tasks, and landscapes. So, machine experiences are unique. Each, hence, needs a fingerprint unique to itself, a ledger that records its accomplishments, and at the same time accounts that tracks its shortcomings.

Fingerprinting a device, drone, or robotic machine is essential for tracking its capabilities, shortfalls, bugs and errors, lifelines, merits, future training, compatibility with certain environments, and interactions with humans, among other things.

Not just robots; we need to identify drones, machines, and other smart devices that will be part of people’s lives in the coming decades, if not in the coming years.

In one of my previous articles, I wrote about robot passports. Here I am extending the identity assessment of even devices, machines, and drones, not just robots.

Why?

As drones and machines gain locomotive capabilities, they will be present in society, so we need them to have an identity, just like humans have a voter ID or a citizenship ID.

In the same way, drones and machines need to be identifiable.

For this, each drone and machine needs a digital fingerprint, composed of what it is made of and what it can do and what it has done.

This digital fingerprint can be a hashcode, and we can use blockchain capabilities to implement it.

If we encounter a drone with accessible permissions in its blockchain, we can learn what the drone is all about. The drone can carry its name, not just a fingerprint.

The drone capabilities can be assessed through its blockchain.

For example, the experience of handling various types of delivery parcels can be tracked using blockchain.

Its unique capabilities are embedded in this blockchain, which can be private or public, depending on whether you allow the drone to be used publicly or privately. In each case, the machine or drone needs to register its key capabilities.

An example of this is a robot that delivered essential files to a meeting, which is an edge over an essential government task over a robot that delivered a pizza to the team’s lunch out. Given in the important task the robot was guided by experts and climbed certain benchmarks.

Similarly, machines such as a mechanical dog can be considered robotics, but are not humanoid robots, as they have their own technical marvels. All would go to waste if this is not registered in its blockchain.

In the same way, failed transactions, viz., failed assignments, also need to be registered for future use or training purposes. For example, a robot was assigned the task of making coffee, but it spilled it. This means we need to retrain this particular robot to make coffee, and it can’t be assigned the task in an urgent requirement in the near future, per the ledgers.

Blockchains are a good way to keep track of machines, robots, and drones. Given the advent of IoT, we shall see many devices in our lives.

Some people want to keep AI out of their lives; they would surely not hire a ride from a machine that is not authenticated by registered, hashed transactions on a blockchain.

So, not just robots need to enter their hashed experiences; drones’ experiences matter too. They need timelines, too. We should be able to access the timelines of when the task was done. For example, an important file needs to be manually sent from Chicago to the company’s New York office, and then the robot can just authorize it when it sends such files to far-off places. Once a robot is shortlisted based on past experience, it is assigned this task.

Order of transactions in blockchain matters; for example, this way we can also know when a robot falls short of some specialization: is it a part issue, meaning it is a malfunction of, say, the left arm, or some other part? This can be used to debug why the robot fell short of an experience it was excellent at in previous attempts.

A machine’s lifelines can be studied from the blockchains of other machines of the same kind when it needs services, and retraining can be done by examining the lifelines of other machines with a different fingerprint but similar blockchains. Each machine is a separate individual.

Hence, fingerprinting a device, drone, or robotic machine is essential for tracking its capabilities, shortfalls, bugs and errors, lifelines, merits, future training, compatibility with certain environments, and interactions with humans, to mention a few.

To a world where machines are fingerprinted, experience is recorded in their blockchain. They, the machines can be resold, hired, or accessed based on these blockchain authentications. They all look the same, but they are different, shaped by the paths they traveled with the humans they work for.