Making ‘Inference Computing Anywhere’ a Reality with the Rugged Edge

Making ‘Inference Computing Anywhere’ A Reality With The Rugged Edge

How partnering with Premio brings the benefits of edge computing to heavy industrial applications

The massive amount of data generated by intelligent, connected devices is well served by high-performance edge computing – so long as its environment is stable and unchanging. But what happens in harsh, unreliable settings? While heavy industry can certainly benefit from the edge, it requires more. More performance. More processing power. More reliability. More everything. This where rugged edge computing is gaining traction.

By efficiently transporting data back and forth to the core, rugged edge computing makes the most of low latency, fast processing, and increased data storage capacity at the point of need. Convergence of the latest IoT developments is driving a new level of reliability in harsh, mobile, and remote settings. But what are the design tenets that allow systems to endure and thrive at the rugged edge? Telematics and autonomous fleet routing are emerging IoT applications in which in-vehicle computer hardware can support inference analysis and machine learning. In autonomous fleet routing, sensors throughout the vehicle reveal what is happening in real time. these data sources are helpful in tracking, routing, reporting, and even determining vehicle service requirements. Monitoring of weather and traffic conditions can impact fuel consumption, efficiency and fleet safety.

Once upon a time edge computers collected information exclusively from IoT devices. This is no longer the case. Today’s edge computing hardware advancements have upped the ante, blending performance accelerators for reliable real-time processing. Even so, systems operating in volatile surroundings must also address the realities of their physical computing environments – fanless design along with cableless design combats challenges like shock, vibration, dust, debris, and temperature extremes. Decisions around memory and storage have direct impact on a system’s responsiveness to accessible workloads for immediate data cache. Whether to choose HDDs (hard drives) and/or SSDs (solid-state drives) depends on the application. Further enhancements come into play when a rugged PC is configured with NVMe SSDs, extremely fast storage devices capable of faster read/write speeds in an ultra-rugged small form factor. A broad array of power options protects performance in mission-critical enterprise deployments. And new and legacy factory equipment is likely to require a range of I/O ports making plug-and-play options vital.

Just as factory equipment learns to recognize objects on the manufacturing line, telematics leverages machine learning for better operability and responsiveness. A deeper understanding of the rugged edge can help designers meet the challenges presented by a growing slate of new and exciting inference computing applications destined for the harshest remote and mobile environments. For a deeper dive into the rugged edge and what it can mean for your organization, check out our article in Design World.

Connect with the Premio engineering team to gain insight into how smart hardware strategies can enable AI and machine learning for telematics success. Our team is ready to collaborate, from design to manufacturing to deployment, guiding your heavy industrial operations to real-time decision making fueled by inference computing at or near the data source.