ADLINK joins IBM Edge Ecosystem for AI enablement-ADLINK Blog

The requirement to remotely manage resources was born from many needs. The need to improve worker productivity by reducing the time it takes to travel to multiple locations to gather disparate device data or make device-level updates. The need to access and react to data in real-time to prevent disasters and downtime. The need to more frequently gather data points for accurate predictive modeling for operational requirements such as inventory management or equipment maintenance. And the need to prevent workers from putting themselves at risk by being near potentially dangerous equipment such as grain bins and combines, or accessing benign equipment in dangerous locations such as oil drilling platforms or telephone poles.

True remote resource management, whether those resources be devices or people, has never been a more critical need than it is today. With our current global situation driving people to socially distance, every industry is seeing what may once have been a theoretical use case play out in their factories, warehouses and retail spaces: how do we manage resources when we can’t get anywhere near them or each other?

For everyone in technology, our ultimate goal is to make the right data available at the right time in the right place with the right compute to make the right decisions. According to Gartner, 75 percent of enterprise data will be processed at the edge by 2025. Edge computing brings data processing and storage closer to where data is created by people, places and things; this reduces latency issues that come with pushing large amounts of data to the cloud, enabling faster business insights and actions and the ability to maintain continuous operations.

At ADLINK, we realize that no single vendor can reach that ultimate goal alone, which is why we’re pleased to be part of the IBM Edge Ecosystem to collaborate on new applications to easily run from anywhere on our ADLINK platforms. We share a common view that enterprises need an environment where they can build once and deploy to and manage from anywhere – across public or private clouds, on-premises and onto our edge devices.

The new IBM Edge Application Manager automates and enables AI, analytics and IoT workloads to be securely deployed and remotely managed, delivering real-time analysis and insight at scale – up to 10,000 devices simultaneously. Together with our partner, Arrow Electronics, we are certifying IBM Edge Application Manager with a variety of ADLINK edge devices, starting with our NEON-i Series of industrial cameras designed for machine vision and AI.

ADLINK’s NEON-i cameras provide a high-performance GPU-based training platform to help organizations accelerate deep learning workloads for object detection, recognition and classification - creating sense-making systems for situational awareness. Depending on the model, ADLINK's NEON-i offers NVIDIA® Jetson™ TX2, NVIDIA® Jetson™ Nano or Intel® Movidius™ Myriad™ VPU to serve as AI-enabled image sensors for flexibility across vertical applications.

The NEON-i cameras enable users to deploy with different neural networks created by NVIDIA TensorRT™ built on CUDA, the Intel® OpenVINO™ toolkit or PowerAI Vision on Open GL – Edge AI powered by the most powerful NVIDIA, Intel or IBM inference at the edge technologies. The AI-enabled industrial cameras also incorporate ADLINK Edge™ software, which allows the connection of previously unconnected operational equipment, sensors and devices with no programming required. This enables data to flow freely northbound or southbound to and from any cloud analytics platform database, as well as east and west between devices to control operations at the edge.

And we’re not stopping at cameras. We will continue to grow our base of supported devices and begin to engage with new clients in target industries such as manufacturing and oil & gas. ADLINK as a company has championed and participated in development of open standards likewise supported by IBM and many others in the IT industry; it only makes sense that we enable integration of our devices and solutions to support these efforts.

Train in the cloud. Deploy to the edge. Manage at scale. And perhaps the most critical piece – do it all remotely. Because while these new advancements will ultimately increase efficiency and productivity, reduce machine downtime, improve product quality, reduce time-to-market and total-cost-of-ownership and all of the other benefits that are promised with the implementation of innovative technology, it will also provide businesses with a better way to manage both daily operations and unforeseeable circumstances without compromising the safety of their workforce.

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