IBM Watson IoT

When the IT analysts at Gartner presented their top 10 strategic IoT technology trends for 2018 to 2023, one trend topped the list: AI and IoT.

Gartner forecasts the total number of connected devices will reach 25 billion by 2021, producing immense volume of data. “Data is the fuel that powers the IoT and the organization’s ability to derive meaning from it will define their long-term success,” said Nick Jones, research vice president at Gartner. “AI will be applied to a wide range of IoT information, including video, still images, speech, network traffic activity and sensor data.”

To deliver on the promise of AI-enabled IoT, Persistent Systems applies more than a decade of experience integrating Watson into a variety of applications to support four key functions:


Analyze and interpret all your data just as humans
do, including:

  • Unstructured text
  • Images
  • Audio
  • Video


Use machine learning to grow subject matter expertise
in your apps and systems using:

  • Data points
  • Interactions
  • Outcomes


Infer and extract ideas and provide recommendations
by understanding a user’s:

  • Personality
  • Tone
  • Emotion


Communicate naturally 24/7 via speech or in native applications via:

  • Robots
  • Chatbots
  • Social media
  • M2M

Our Unique Flywheel Approach

Persistent Systems relies on our proven Flywheel Approach that blends IoT, data, APIs, machine learning/AI and continuous engineering to build great customer experiences and helps transform customer business.

Examples of Watson-based solutions developed by Persistent Systems include:

SEAMless: Smarter Enterprise Asset Management from Persistent Systems

A circular solution for AI-enabled asset performance, requirements and lifecycle management.

Enterprise asset management (EAM) platforms are purpose-built to help utilities and energy companies maximize the value and performance of their assets, vehicles and physical locations.

But the growth of IoT has opened up new asset lifecycle performance and management opportunities for forward-thinking organizations looking to extend the life and performance of these assets. To unlock the full potential of enterprise assets in the IoT era, Persistent Systems created SEAMless, a complete AI-enabled asset performance, requirements and lifecycle management solution.

Why use SEAMless from Persistent Systems?

Enterprises that embrace SEAMless from Persistent Systems will experience the following business benefits:

  • Tighter integration: Bringing together Design, Operate and Maintain functions into one lifecycle management solution
  • Disruptive technology: Harnessing AI and ML to deliver breakthrough insight
  • Accelerated innovation: Leverages the “digital twin” concept to speed improvements and decrease development expenses
  • Improved worker safety: SEAMless’s natural voice interface allows technicians to focus on their safety and the job at hand, not how to interact with the technology.
  • Optimize your operations: Break down silos to improve assets performance and employee productivity
  • More efficient processes: Reduce expenses across the lifecycle
  • Reduced customer total cost of ownership: Higher asset uptime and longer asset lifecycle

Machine Maintenance Cloud from Persistent Systems

Anticipate maintenance. Practice repairs in advance. Eliminate downtime.

Unexpected breakdowns of industrial machinery can have costly and long-lasting ramifications for any business. But today’s Internet of Things (IoT) capabilities allow equipment in the field to:

  • Continually diagnose itself
  • Notify you when maintenance was required
  • Alert you when a failure was imminent

The Machine Maintenance Cloud is the next revolution in the quest to eliminate costly downtime, blending four leading-edge technologies to keep your industrial machinery performing at its best:

  1. IoT: Connected devices monitor their own systems and report back to a centralized location.
  2. Cloud Computing: In the event one or more units drop off the network, neighboring units work to heal the connection and restore the flow of data.
  3. Machine Learning: The connected units learn from the performance of each other, continually improving their ability to diagnose maintenance needs and potential causes for failure over time.
  4. Augmented Reality: If repairs are needed, field service technicians can use augmented reality to conduct virtual repairs before they head out to the field, ensuring that the technicians have the repair parts they need and are capable of fixing it the first time.

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