Help is on the way to lift IoT out of its “trough of disillusionment” . . .

In the past week, I saw two articles on LinkedIn where “IoT” and the phrase, “trough of disillusionment”, appeared together.

As a long-term participant in the IoT ecosystem focused on Digital Twins, I have dealt with the reasons for this disillusionment for some 20 years now! After deploying plant-wide IoT system and display digital twin, my client’s excitement faded quickly after the initial warm feeling seeing real-time data from all the equipment in one place . . . Beyond “visibility”, where is the beef? We didn’t have really good answers . . .

Even now, digital twins are based on thresholding or banding sensor amplitudes (or some point-measurements on their FFTs) which are replete with False Positives. Technician runs on to the plant floor based on an alarm and finds that it is a false positive – this happens a few more times and people start ignoring the alarms; soon after they are ready to chuck the software out of the window! I don’t blame them.

The other bugaboo is the business model of large IoT companies that present Digital Twin (and IoT) as a “No-code” or “Low-code” self-installed system. This appeal to “democratization” is understandable from their business model – they want a huge installed base without an army of field application engineers (FAEs).

IoT works in highly verticalized and compartmentalized business domains. FAEs for Machinery vertical have very different track record from Building monitoring FAEs, for example. The REAL business model story is this –

IoT provides real-time visibility into production operations – a “democratized” solution with a handful of Solution Engineers CAN deliver revenue to the IoT platform company.

Digital Twins on the other hand need crafting on a usecase – per – usecase basis! Other than a basic digital twin (that provides low value to the client), the real value generating digital twin is a CONSULTING business!

In short, digital twin has not progressed due poor choice of business model and lack of performance information extraction ability. I am glad to report that Eminds.ai has solved both these issues. We hope that this will open the flood-gates of Digital Twin applications that provides real business value to the customers, thus pulling IoT out of the doldrums.

Eminds.ai takes a “product-enabled” service consulting model. Admittedly, this is not a massively scalable model. Our vision is to scale by partnering with many more firms like us and use our base product for their consulting services in verticals where they are super-specialized.

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How does TwinARC work?

Your current IoT platform only enables observation of raw data on a?dashboard that leaves a lot of questions unanswered.?A call to our secure API summons the power of TwinARC into your existing IoT platform.

Our solution combines Rules Digital Twin that DETECTS ISSUES, Stats Digital Twin that ASSIGNS PROBABILITIES and using a META LEARNER, makes the traditional “brittle” digital twin outputs a thing of the past. Once the Data clears certain technical hurdles, our CAUSAL Digital Twin allows you to perform “Root-cause” and “What-if” analysis that leads to deeper performance understanding and unprecedented improvement!

Eminds.ai invites IoT Platform providers and IoT Consultants to jointly sell a high-value, end-to-end solution integrated with TwinARC to meet your customers’ need for performance understanding and improvement!

For more information, visit: https://www.eminds.ai/DT.html?

Write to [email protected] for engaging with us for a NO-COST test deployment of TwinARC in your physical product manufacturing enterprise!

?#digitaltwin #iot #causal #manufacturing #twinarc