Industry IoT Consortium
Organizations can either adopt change willingly and proactively, or forcibly by market demand. Any choice in the matter faced an unlikely dictator this year in the form of a worldwide pandemic. One that some organizations had no choice but to scale in ways they had only previously envisaged, within the context of a long-term strategy.
Once recognized as slow to adapt to technology, the construction segment is now an industry on the fast track. By connecting start-ups with major industry organizations, the Industrial Internet Consortium’s Smart Construction Challenge enabled implementations of the next-gen smart construction digital ecosystems.
Disruptive technologies are transforming all industries into digital industries and repositioning them to reap the benefits of Industry 4.0. In the industrial context, digital transformation (DX) is primarily a business objective.The IIC has captured the many challenges and technological hurdles that accompany this journey along with guidance in their recently published white paper, Digital Transformation in Industry.
We pride ourselves in our resilience and our ability to think and invent our way out of a crisis. Technological optimism has been one of the engines of modern life, and its promise has often held true in the past. Time and again, technology has helped us master the challenges of history. At the same time, we have become reliant on it, and too often willfully ignorant of the consequences.
Wireless connectivity is needed to achieve the agility demanded by Industry 4.0, particularly in large scale manufacturing facilities. Currently wireless is only used sparingly, typically with unlicensed spectrum technologies. Several competing wireless technologies are emerging as candidates for Industry 4.0, including WiFi-6 for unlicensed spectrum, and 4G-LTE and 5G in licensed spectrum bands. Recent 5G technology releases have incorporated key capabilities for Industry 4.0, such as ultra-reliable low latency connectivity, Ethernet-TSN integration, and a variety of features for massive machine type communications.
We lost a beloved colleague earlier this week. I wanted to take this time and space to express our gratitude for having the great fortune to have known Brett Murphy in his too-short life and share how important he has been to us. Brett Murphy has been a member of
Software trustworthiness – what does it mean for developers, owner-operators and decision makers in Industrial Internet of Things (IIoT) systems? The Industrial Internet Consortium (IIC) recently published a white paper, Software Trustworthiness Best Practices, that delved into the complete software lifecycle process, including such practical issues as software updates and end-of-life strategies, as well as among many other issues, considering vulnerabilities in the system environment and the consequences of failure in such environments. The overall objective of the white paper was to take a comprehensive look at all of the elements involved in achieving the ultimate goal of trustworthy software and protection mechanisms that produce predictable and desirable business and operational outcomes in the IIoT.
We are excited to announce the official launch of the IIC Community Forum for you, the IIoT community. We invite you all to be part of this initiative and to spread the word to your colleagues, peers and customers.
Since it was founded in March 2014, the Industrial Internet Consortium (IIC) has been tested and proven to bring together organizations and technologies necessary to accelerate the growth of the industrial internet. The organization has become the largest IIoT consortium in the world and proven to be a thought leader repeatedly through identifying, assembling, testing and promoting best practices. 2019 was indubitably one of the most transformative, influential years so far.
Artificial intelligence (AI) and machine learning (ML) have made huge gains over the last few years, thanks to the vast amount of data available and to the gains made in raw hardware processing power. The success of AI and ML also comes with certain risks, however – in particular the risks around privacy of the collected data