The Intelligent Edge: What it is, what it's not, and why it's useful

November 30, 2018

The Intelligent Edge: What it is, what it’s not, and why it’s useful

Organizations are using edge computing to create smarter buildings, cities, work spaces, retail experiences, factory floors, and more. Explore how the Intelligent Edge can yield deeper insights faster to transform your business.

What is Intelligent Edge?

The term “Intelligent Edge” is used in many ways, but perhaps the best way to think of it is as a place. The edge is where the action is. It’s a manufacturing floor, a building, a campus, a city, your house, a crop field, a wind farm, a power plant, an oil rig, a telecommunications outpost, a sports arena, a battlefield, in your car, in the sky, or under the sea. It’s everywhere everything is, and it’s where the “things” are in the Internet of Things (IoT).

The edge is “intelligent” because now there’s technology in these places that’s smart, connected, computational, and controlling. Crucially, the Intelligent Edge provides analytics capabilities that were formerly confined to on-premises or cloud data centers.

The 3 Cs of the Intelligent Edge

The usefulness of the Intelligent Edge is revealed when we unpack the three Cs:

Connect:

When devices, people, or things connect via networks, it facilitates data exchanges that promote new sources and quantities of data.

Compute

Systems can then compute this data, provide access to applications, and reveal deep insights concerning the connected things, devices, and the surrounding environment.

Control

These computed insights can then be used to take action, control the devices and things at the edge, or prompt other types of control actions associated with the business or enterprise to which the edge is connected.

The 3 Cs of the Intelligent Edge in action

A retail store connects cold drinks and digital price displays on its shelves to a network. Now the retailer can instantly track inventory and see how long it takes for each drink to sell. This information, combined with outside temperature and sales data from other locations, can be used to adjust and control drink prices in real time. In this IoT application, the drinks and price displays are “things” connected to the network. This connectivity allows the retailer to maximize sales and minimize shipping costs, while enabling new customer experiences.

Now consider how an employee with a smartphone app entering a large office building or campus with wireless location services can find a conference room, printer, or people without asking directions. This immediate insight into where the employee resides in relation to these other connected things greatly enhances the experience in this intelligent building. It’s very similar to the retail shopping experience offered by many large retailers, where customers can access turn-by-turn directions on their phones to locate products, figure out what’s on sale, or find the restroom.

The media and telecom industries face growing distribution pressures from increased video resolution, new formats, expanding bandwidth, and the need for better security and reliability. As a result, telecom service providers are placing sophisticated compute and control systems in businesses and homes. These distributed intelligent edges make the services more competitive and improve customer experiences.

Intelligence at these various edges continues to improve, supported by emerging industry standards and software stacks similar to those formerly reserved for the data center. This distributed compute trend is driven by the need to deliver better services at the point of consumption, and to avoid the limitations imposed by remote data centers or clouds.

Different types of Intelligent Edges

There are three broad categories of Intelligent Edge: operational technology (OT) edges, IoT edges, and information technology (IT) edges. OT edges commonly contain intelligence and controls but have been traditionally limited in connectivity and compute power.

OT edge examples include power plants and offshore oil rigs. IT edges are common in the telecommunications and media industries for distributed data transfer and processing, as well as distributed computing in branch offices and campuses.

The IoT edge is of great interest today, as the IoT has achieved celebrity status. In many instances, the IoT is a combination of OT and IT. When discussing the IoT, it’s instructive to first understand the generalized four-stage IoT solutions architecture depicted in Figure 3. “Things” are connected to sensors for data capture and actuators to control the things—either wired or wirelessly. These sensors and actuators connect to gateways, switches, and data acquisition systems in stage 2. Stage 3 is comprised of IT systems that are at the edge, and stage 4 is the remote data center or cloud. Not all IoT solutions include all four stages (e.g., some are sensor-to-cloud solutions), but a large portion of IoT solutions can be mapped into this architecture.

Industrial IoT (IIoT) solutions can generate significant business value when sensors are connected to rotating machinery such as turbines in an electric power plant. Physical data extracted from the turbines, such as temperature, moisture, and vibration, provides valuable insight into the machine’s health. Prognostic analytic programs process this data and provide immediate insight into the turbines’ health status. This affords better control over the maintenance routines and helps predict failure associated with brownouts or blackouts.

The 7 reasons to compute at the intelligent edge

Although all three Cs (connect, compute, and control) contribute to edge intelligence, compute improvements are especially important because they can yield immediate insights from edge data at relatively low cost. Edge compute can be improved by shifting enterprise-class compute, storage, and management from the data center out to the edge. Organizations can leverage compute at the edge to:

1. Minimize latency

There are many applications that require immediate insight and control. For some mission-critical functions, compute must take place at the edge because any latency is intolerable. Consider a robot arm in a shop process that requires precision adjustments and calibration to maintain product quality. If the factory is churning out 50 products per minute, it’s important the calibrations be done in real time to minimize defects.

2. Reduce bandwidth

Sending big data back and forth from things to the cloud can consume enormous bandwidth. Future edge computing is the easiest solution to this problem.

3. Lower cost

Even if bandwidth is available, it can be costly. Efficiency is an important element of any corporate IoT strategy.

4. Reduce threats

When you transfer data across the campus, state, country, or ocean, it is simply more prone to attacks and breaches. Processing data at the edge can reduce security vulnerabilities. More about the Three Types of Security in IoT

5. Avoid duplication

If all the data is collected and sent to the cloud, there will likely be some equipment duplication in memory, storage, networking equipment, and software. If this duplication is not needed, then the associated increases in capital and operating expenditures are unwarranted.

6. Improve reliability

Even without any nefarious activity from hackers, data can be corrupted on its own. Retries, drops, and missed connections will plague edge-to-data-center communications. Even today, cell phone calls can be broken up or dropped.

7. Maintain compliance

Laws and corporate policies govern the remote transfer of data. For example, certain countries forbid companies from moving the personal data of their citizens outside their borders.

7 reasons to compute at the edge

Getting started with intelligent IoT

Once the value of exploiting the action and insights at the edge is understood, it’s important to shift the focus to quantifying the return on investment (ROI) of a specific edge deployment. This can be done by initiating a formal and controlled IoT proof-of-concept project that will help alleviate concerns about working with unfamiliar, emerging technology as well as security issues around protecting the network and data. For businesses, ROI usually translates to improved financial performance due to lower operational expenses, deeper customer insights for up-selling, or increased production. In scientific and engineering enterprises, ROI can be associated with accelerating innovation and human progress.

Start by identifying a focused business, engineering, or scientific benefit to be derived from the project. Assess how it will impact your enterprise when successful. Connect a few things, such as corporate assets or products.

Analyze or compute the data from these newly connected things, and assess whether the insights you expected are revealed. Control your things to improve their operation or help adjust your business processes by shifting inventory, adding personnel, or re-pricing products. If the small project looks promising, scale up slowly with more connected things and additional data capture, and reassess the value as you go along.

You also need to promote OT and IT convergence and cooperation. Engineering and OT professionals must consider how to work side by side with IT professionals. IT professionals must consider reciprocating. For example, OT executives might add a senior engineer from IT to the IoT deployment team. This kind of cooperation is crucial because successful, end-to-end IoT solutions must integrate OT sensors, actuation, data and control systems, and acquisition systems with IT compute, storage, and networking.

Predicting the future

Much of the Intelligent Edge and IoT experience is based on its perpetual connectivity to things, people, and the environment. This in turn will produce growing volumes and varieties of edge data. If you like big data, you’ll love the Intelligent Edge and the IoT. The data sources at the edge are older because they are predominately natural data that originated with the universe, such as light, sound, radio waves, location, time, pressure, and velocity. They are also captured at higher speeds and will be bigger than all other types of big data combined.

Diversity of data at the Intelligent Edge, predominately physical world data

Because large and diverse data sets improve the statistical accuracy of predictions and conclusions, we can expect more reliable medical prognoses, clarity on when equipment failures will happen, and precision on what people will buy, who will win elections, and where people will go on vacations.

In the future, we’ll be able to predict the future more accurately. If data scientists can monitor your behavioral and consumption patterns along with your blogs, comments, posts, and tweets, they can start to predict what you’re going to do next. Growing and increasingly diverse data sets will make their jobs easier.

The Intelligent Edge is an exciting place. Organizations that have rolled out IoT projects have seen returns in the form of cost savings, efficiency improvements, and higher customer satisfaction scores. If you haven’t mapped out your IoT strategy, it’s time to start thinking about how your organization might benefit from the Intelligent Edge.

Originally this article was published here.

Tom Bradicich is Vice President and General Manager at Hewlett Packard Enterprise (HPE), leading the global business unit dense scalable servers and IoT Systems and Software, with P&L, worldwide product development, and customer experience ownership. He directs the HPE Discovery Labs and IoT Innovation Labs in the US, Europe, and Asia, for partner and customer collaborations. HPE Edgeline Converged Edge Systems is powered by Intel® Xeon®.

The Intelligent Edge: What it is, what it’s not, and why it’s useful

What is Intelligent Edge?