On the opening day of Industrial Internet of Things (IIoT) platform provider Advantech's online conference, company representatives and other industry experts gathered to discuss new developments on the horizon for IIoT, artificial intelligence (AI), and industrial networking. In particular, many sessions focused on the hurdles that still remain if IIoT and associated Industry 4.0 technologies are to see ubiquitous adoption in the future. The Advantech Connect conference continues online through May 6. Perhaps the greatest take-away from the first day of the event was that, while the real bedrock of value provided by IIoT is to be found in the data it generates, nothing can be attained from it unless that data is effectively gathered, communicated, and analyzed. Through the improvements these technologies enable in data gathering, transmission, and analytics, Advantech envisions industry moving beyond IIoT and toward an Artificial Intelligence of Things (AIoT) that allows cloud-delivered applications to make real-time, autonomous decisions at the device level.

While most consumers may find Internet of Things (IoT) devices like Google's Nest or Ring's doorbells new and exciting technology, the manufacturing world has embraced the IoT to optimize discrete and process manufacturing operations for decades. The industrial IoT (IIoT), which started as remote sensing of things like temperature and pressure, has today matured into a way of linking operational systems that control production with the wider world of applications outside of the control room like ERP platforms and supply chain management systems. "The major benefits of the industrial IoT is to bring more visibility to existing processes," said report author Jaques Durand, director of Standards and Engineering at Fujitsu North America and a member of the Industrial Internet Consortium Steering Committee. People want to understand what's going on." Getting to an advanced state of IIoT usage can be difficult without understanding the mistakes to avoid along the way. That's why the Industrial Internet Consortium (IIC), has spent the last six years developing and deploying testbeds for manufacturers to use when evaluating different IIoT technologies, platforms, designs, products, architectures, and use cases. Based on the results of these testbed proofs-of-concept (POC), today the IIC released a white paper, A Compilation of Testbed Results: Toward Best Practices for Developing and Deploying IIoT Solutions, detailing the best practices companies should adopt to ensure successful IIoT deployments. "The IoT problem that each company is facing or each organization is facing is different," Durand said. "Even if they use the same technologies, which is not granted, they are facing very different conditions and priorities in real-world conditions.

With a couple of notable exceptions (like big data processing using artificial intelligence algorithms), increases in computing power and improvements in storage technology have not necessarily meant that humans could work any faster or harder. But instead that technology is now able to shorten time-to-value for new apps and services, and managing that provision's infrastructure has got easier. In data centers, software-defined structures like convergence, hyperconvergence, and service abstractions are becoming more prevalent and mainstream. Perhaps the earliest example of software abstraction was the virtual server. Virtual machines now predominate in local, remote cloud and edge data centers/microcenters, and their presence has led to an uptick in utilization metrics.