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The top 4 industrial enterprise requirements of IoT application enablement platforms (AEP)

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Relying on hands-on usability and functionality tests to understand IoT AEPs is the best way to differentiate the true capabilities of platforms on the market.

industrial enterprise requirements of IoT application

industrial enterprise requirements of IoT application

With over 400 self-proclaimed IoT platforms in the market, it doesn’t surprise me that industrial enterprises are hindered trying to identify, test and select a high quality IoT platform. Platform vendors’ marketing materials contain the same messages, their RFX responses always affirm “full compliance” with all requested capabilities and they have partnerships with the same cloud vendors. With over 400 self-proclaimed IoT platforms in the market, the only way to truly know each platform is to use it.

What makes a great IoT AEP?

An Application Enablement Platform (AEP) is a technology-centric offering optimized to deliver a best-of-breed, industry-agnostic, extensible middleware core for building a set of interconnected or independent IoT solutions for customers. An AEP links IoT devices and applications, delivering data to allow industrial enterprises to implement predictive maintenance, machine learning, factory automation, asset logistics, surveillance and many other applications. With IoT platform revenue slated to grow to USD 63.4 billion by 2026, IoT application enablement is one of the most highly demanded enterprise IoT platforms.

Industrial enterprises like heavy equipment manufacturers, petrochemical firm, robotics manufacturers and others spend a tremendous amount of time using their IoT platforms. According to hands-on tests of IoT platforms in MachNation’s IoT Test Environment (MIT-E), an enterprise user will spend an average of 61 minutes executing 7 of the most common IoT data management tasks on an IoT platform. However, an enterprise user can complete these seven tasks in only 10 minutes on the best designed IoT platform while spending 181 minutes on the most cumbersome platforms.

These tasks include:

  • Configuring persistent on-platform data storage
  • Forwarding live sensor data to external endpoints
  • Viewing historical sensor data from a single device
  • Viewing historical sensor data from a group of devices
  • Computing aggregate statistics for a single data point
  • Computing aggregate statistics for multiple data points
  • Deleting a single historical sensor data point

Since picking a best-in-class IoT AEP is critical for industrial enterprises deploying IoT solutions, the top four requirements of an IoT AEP based on enterprise users’ experiences with these platforms.

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Article Credit: Network World

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