When IoT Expands its Reach and Intelligence with "Rugged Edge Computing"

The Internet of Things Becomes a “Smart thing” - Capable to leverage Data Aggregation and Real-Time Analytics

In the last decade the hype and buzz from the internet of things or “IoT” has rapidly erupted into a digital transformation data-driven assets in specific industries like manufacturing, transportation, and public utilities to name a few. Until recently many of these industries did not experience any major disruption in technology until leading innovative organizations spearheaded business objectives to explore the value of data and its enormous potential. This shift to IoT alongside the combination of newer technologies in computational processing, large-volume data storage, and mobile high-speed connectivity has enabled these industries into a perfect model of data-centric automation and efficiency. For example, to provide some background of the overall business opportunity, the International Data Corporation (IDC) reports in their worldwide forecast that “spending on the Internet of Things (IoT) is forecasted to reach $745 billion in 2019, an increase of 15.4% over the $646 billion spent in 2018…IDC expects worldwide IoT spending will maintain a double-digit annual growth rate throughout the 2017-2022 forecast period and surpass the $1 trillion mark in 2022.”¹ This continuous trend and demand for valuable insights from IoT is now at the forefront of strategic objectives. Even though these statistics project a bright future for IoT, it’s important to evaluate how enterprise organizations are implementing and deploying new innovations and processes across their operational infrastructures for success. Therefore, by clearly understanding where budgets and investments for IoT solutions are being spent, the entire ecosystem from both hardware and software solutions can provide better ideas for the next wave of IoT technology and connectivity.

When evaluating industries or markets being shaped by IoT, it’s important to highlight specific industries that are leading the charge with their hefty spending budgets. In the forecast from IDC, the overall project spends for 2019 is projected to reach $745 billion, which a large percentage stem from manufacturing. For example, the IDC report also lists out spending for 2019 on specific industries like discrete manufacturing ($119 billion), process manufacturing ($78 billion), transportation ($71 billion), and utilities ($61 billion). These projections are a clear indication that manufacturing and industrial automation is about a 1/4 of projected spending on IoT solutions; a major opportunity for many solutions focused in industrial automation equipment. As a result, IDC also states that there is a focus on “solutions that support manufacturing operations and production asset management,” which is a major goal for this industry. Overall, manufacturing as a whole, is one of the key markets that are aggressively looking to utilize newer IoT solutions for better productivity and efficiency into existing legacy infrastructure – now also being coined the “Industrial Internet of Things” or (IIoT).

"IDC projections are a clear indication that manufacturing and industrial automation is about a 1/4 of projected spending on IoT solutions"

Amidst the backdrop of this digital and data-centric transformation, manufacturing markets are adopting IIoT technologies to stay on top of their respective competition. IIoT devices are different from other IoT applications as it focuses on connecting machines in more rugged industries and bridging the gap between legacy infrastructure with new technologies. Traditionally tech-driven industries like manufacturing and automation have started integrating IIoT devices into their everyday operations, which is reported to cost upwards of $200 billion from IDC analysts.¹For this reason, leading IT research companies like IDC are researching the necessary hardware and software tools to deliver a successful integration of IIoT available in the market because “hardware spending will be close behind at $250 billion led by more than $200 billion in module and sensor purchases” and “IoT software spending will total $154 billion in 2019 and will see the fastest growth over the five-year forecast period with a CAGR of 16.6%.”¹. These type of statistics show proof that there is a high demand for the right type of hardware and software solutions for IIoT. But most importantly, these direct decisions to upgrade and capitalize on preexisting data management infrastructure represents a significant need for new IIoT hardware focused on industrial ruggedness, stability, and reliability for a much longer service life.

Currently, IIoT hardware or devices play a vital role in the overall growth towards automation and Industry 4.0, a revolutionary framework for data and real-time connectivity driving machine-to-machine intelligence in factory automation environments. For example, picture hundreds and perhaps thousands of individual endpoints communicating with each other in real-time but now having the computational power and high-quality vision features to drive automated decision making in real-time. This results in allowing enterprise applications to track and analyze operational statuses on a granular level in order to improve operational efficiency; but also enabling business executives to increase their productivity for better business outcomes. By implementing IIoT and deploying new technologies that help connect the physical and digital world into one, businesses now have the raw data to gain insights and quickly respond to change on the fly. In order highlight the important of this change, another IDC study states “2,300 executives across 15 countries, 48% of decision makers have already deployed IoT solutions within their organizations, and another 58% indicated that IoT is central to their business strategies.”²

 Image Source  - IDC²

Empowering the “Edge”, and why it’s shaping the market for hardware manufactures?

Today, unaggregated data from the past is now strategically collected from devices in exponential volume used for analyzing trends and maximizing better business outcomes. The explosion of data and its proven value is pushing existing business models to change at a rapid pace; a transformative change that not only evaluates the importance of data but also how efficiently it can be processed near the source of generation. The ability for features like real-time machine intelligence, computer vision, and high-speed wireless connectivity through 5G networks, is becoming known as the “edge” or “edge computing.” The edge computing market explores unique requirements for new opportunities in a changing business model that leverages the power of centralized “cloud computing”, but now empowers the mobility and flexibility of decentralized “edge computing”. According to Gartner, a leading IT research company "estimates that by 2025, 75% of data will be processed outside the centralized data center or cloud.”³Most importantly, with an abundance of data now shifting away from the cloud, new opportunities exist for embedded hardware manufactures to solve challenges with robust computing solutions in an exploding market. These type of solutions can range from low-power gateways to high-performance edge servers that all have the common ability for localized compute and a framework for high-speed cache. But one thing is clear, these solutions will be designed for real-time insights and powerful localized compute for mobility and remote deployment. In a recent Gartner IT Symposium, the leading IT research firm announced its “Top Ten Strategic Technology Trends for 2020.” One of the standout trends that was listed envisioned a popular trend in edge computing for its ability for decentralized computing topology. According to a post on Forbes.com about the Gartner IT Symposium, David Cearley, a vice president at Garner said about edge computing “Much of the current focus on edge computing comes from the need for IoT systems to deliver disconnected or distributed capabilities into the embedded IoT world for specific industries such as manufacturing or retail. However, edge computing will become a dominant factor across virtually all industries and use cases as the edge is empowered with increasingly more sophisticated and specialized compute resources and more data storage. Complex edge devices, including robots, drones, autonomous vehicles and operational systems will accelerate this shift.”⁴

Edge computing has recently been a popular topic in the technology arena, specifically around benefits from 5G connectivity. For starters, the “edge” has been presented in many discussions as a new model to complement the benefits from the cloud, but also in its own unique value in terms of local computational capacity. According to Gartner, edge computing is defined “as solutions that facilitate data processing at or near the source of data generation…for example, in the context of the Internet of Things (IoT), the sources of data generation are usually things with sensors or embedded devices,” that are decentralized from data center infrastructure or the cloud.5 This new concept of edge computing is very different than the conversations in the last decade, much of the investment and thought leadership put its long-term strategy on enormous storage capacity and computational power of the cloud, or the eventual promise of artificial intelligence. And rightfully so, its clearly undeniable that the benefits of the cloud can be attributed to the explosive growth from major cloud service providers such as Amazon’s “AWS -Amazon Web Services” and Microsoft’s “Azure”- that are used by many enterprise businesses today. But most importantly, why the edge computing model is so transformative for many industries is because of its intelligence to analyze data and act in real-time for deeper insights, but also its ability to now balance and offload a wide-range of workloads at low latency speeds.

These key benefits are becoming deployable in today’s landscape thanks to the rapid innovation of specialized compute power in multi-core processors and enormous data storage that provide machine intelligence and real-time decision making. Especially as 5G connectivity comes online, there is a huge market and new opportunities for edge computing use cases for applications in many industries (Exhibit 1). Therefore, hardware device manufactures are gearing up with specialized edge computing solutions in order to meet the demand for connected devices generating meaningful data. There are some key factors driving edge computing and its expanding markets, especially with new technologies. In a article from McKinsey & Company , another leading research consulting firm believes there are 5 key factor driving edge computing:

1. Varied connectivity and data mobility – Edge computing will rely on remote networks that leverage wireless connectivity; this will allow data to move freely and efficiency without latency issues from the cloud
   
   
2. Ability for real-time decision making - Edge computing in autonomous and mobile deployments require aggregated data to be processed in real-time. With newer muli-core processors and GPU technology, analytics and mission-critical workloads can now be processed in real-time
   
   
3. Decentralized and Localized compute power – Edge computing devices will not be able to rely on a controlled environment like the cloud and its massive resources; these rugged computers will feature robust compute power but also in low power consumption working conditions
   
   
4. High-capacity storage and data security – the ability to store and access data in a secure manner will be a critical element to edge computing; Larger capacity solid-state hard drives with dense multi-bit options and faster Read/write protocols like NVMe technology will allow for access when needed.
   
   
5. Wide Voltage Input support for intermittent power – As edge computing deployments push the boundaries into mobile and remote locations, many of these edge devices will need to operate in environments where the power supply may be unstable.

Exhibit  1  Image Source  - McKinsey and Company⁶

Edge Computing but at “The Rugged Edge” - Why specialized Rugged Edge Computers are needed?

This new shift in the network topology of how data is collected but processed is driving major changes for edge computing, especially in mobile and remote deployments. Since data center or cloud infrastructures are realistically being reserved for specific functions that rely on network transmission, the market for edge computing solutions are currently limitless and open for new specialized solutions, for rugged and remote applications.

The background of the “rugged edge” of edge computing was previously mentioned in a previous blog post detailing the distinct market shift from the cloud to the edge. Read more about that here7In summary, the benefits of incorporating edge computing is clear, however, when deployed in real-world environments that are harmful to electronic components, a specialized rugged industrial computer is required to bring mobile edge computing capabilities to new frontiers.

For example, one unique area of rugged edge computing that is growing with opportunities is embedded industrial computers and gateways that are required to operate in extreme environmental conditions. One distinct characteristic for smart IoT devices or edge computers is the unique use conditions different from the controlled environments of offices or data centers. In addition to the environmental stresses, edge computing devices or computers also come with requirements for specific technological features and characteristics at the complete system level.

Rugged edge computers are specifically developed to withstand the rigors of harsh usage conditions and are able to achieve a high level of durability through incorporating ruggedized features throughout its entire product design. From the external enclosure to the internal components, every piece of a rugged edge computer is purpose-built through a combination of mechanical and thermal engineering to address the issues of strong vibrations, extreme temperatures and wet or dusty situations.

5 Must Have Hardware Requirements for Rugged Edge Computing:

1. Wireless Connectivity

2. Mobility and Remote Deployment

3. Performance Accelerators

4. Variety of I/O Ports and PCIe/PCI Expansion Slots

5. Ruggedness and Security

Learn more about the 5 Must Have Hardware Requirements for Rugged Edge Computing (Infographic Available)

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