Harnessing IoT at the Edge to Deliver the Autonomous Digital Enterprise of the Future

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Illustration: © IoT for all

Over the next five years, businesses will continue to generate massive amounts of data from devices connected to the Internet of Things (IoT). While much of the IoT conversation has focused on these devices, we are seeing a shift as more businesses become data-driven. Business owners now realize that the biggest opportunity to accelerate their business comes from the data generated, not from the devices themselves.

As organizations look to IoT to accelerate business initiatives, IT leaders need to ensure that devices, architecture, automation, and human intelligence work in harmony to create superior employee experiences. and customers. In this way, IT managers can improve operational efficiency, reduce the time spent on mundane administrative tasks, and strengthen network security to deliver an improved user experience. It’s the self-sustaining digital enterprise framework that we’ll continue to see come to life in stores, schools and cities for years to come.

We predict that by 2025, as big data reaches unprecedented levels, technology will underpin all business functions. The IoT will be the foundation for this reality, and businesses that learn to harness it effectively will not only survive but thrive.

Define IoT edge computing

The heart of an IoT solution is typically a central IT system for storing, processing, and analyzing IoT data. Much of this IoT data is often located in the cloud, far from the core. This can lead to devices spending more time in the cloud, resulting in slower reaction times, less reliable operations, and a lot of employee and customer frustrations. Edge treatment can meet these challenges.

Edge IT services and IoT go hand in hand. Communications are facilitated by advanced IT services and digital transactions are facilitated by IoT. As a result, edge services act as a valuable stand-alone digital source that can greatly improve an organization’s ability to process, store, and analyze data from IoT devices. This can help organizations more effectively manage and control these devices, protect them from vulnerabilities, and glean valuable information from the data they generate.

Processing IoT data at the edge remains crucial

The term “edge computing” is arguably just as misinterpreted as “IoT” in the marketplace, as it means different things to different people, organizations, and industries.

Edge computing is generally applied to certain elements of processing, sensing and actuation of commands to monitor, control and optimize certain functions at the point of origin with calculations at the sensor or device level and via other on-site infrastructure (server cabinets, gateways, etc.).

It could be a smart meter on a power grid, a sensor on a remote oil rig, a CNC machine in a car factory, or even the PLC that controls it and other machines. in an assembly line.

The Autonomous Digital Company and IoT edge computing

The ultimate stand-alone digital enterprise will run on a transparent IoT Edge-AI-based IT solution that enables IT administrators to:

  • Configure what data should be stored locally and define a data aging policy.
  • Set conditions with adjustable time windows to identify patterns in incoming IoT data as the basis for automated events. For example, certain conditions may initiate transactions and notify the appropriate parties.
  • Perform business transactions at the edge to ensure continuity of critical business functions, even when the edge is disconnected from the core.
  • Use predictive models that are constantly “trained” to analyze IoT data. The predictive algorithm would be trained in the heart and then applied to the periphery.
  • Apply deep learning algorithms at the edge specifically for image and video analysis.
  • Visually inspect data collected at the edge. For example, after an alert has been sent to the core, an analyst can dig into the details that led to the alert.

The features listed above help businesses seamlessly converge, analyze, and prioritize operational and IT data. As such, they can perform two essential functions: (1) better prediction and resolution of potential problems before they cause disruption to customers and (2) the ability to generate more valuable information and exploitable from the data.

These two elements are essential to delivering a superior employee experience that retains and attracts talent, creating a transcendent customer experience that forges long-term loyalty and, ultimately, moves the business forward.

Conclusion

Going forward, we are poised to see more devices deployed across the enterprise to meet business needs, such as occupancy sensors, asset tracking devices, asset monitoring industrial and other solutions to ensure productivity and efficient use of resources.

Advanced IoT computing is playing an increasingly important role in the business as IoT technology becomes more and more entrenched in our daily lives. Some businesses may experience even more acute networking and device adoption needs if they choose to embrace long-term remote working or flexible work-from-home policies. As the type of devices and the volume of data generated by them increase, advanced computing will become increasingly essential to maintain operational speed and efficiency throughout the enterprise.

Today’s emerging autonomous digital businesses recognize that devices are not the end of the game. As each organization becomes a data-driven technology company by 2025, the real market leaders will be those who strategically leverage the IoT to efficiently collect, analyze and apply large amounts of data faster and smarter than their competition.

Written by Sam Lakkundi, Vice President, Innovation and Head of BMC Innovation Labs, BMC software


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