Collaborating Authors

Survey: Industrial IoT deployment thriving


This ebook, based on the latest ZDNet / TechRepublic special feature, explores how infrastructure around the world is being linked together via sensors, machine learning and analytics. The Industrial Internet of Things (IIoT) adds significant value to businesses, and industries such as manufacturing, transportation, utilities and more, are taking full advantage of IIoT's capabilities. In January 2019, Tech Pro Research surveyed professionals to measure how, why and what lessons were learned from Industrial IoT deployments. Questions included why an organization would adopt IIoT, what type of data is collected from IIoT, and how the data is used. Industries are eagerly approaching IIoT adoption, as 82 percent of survey respondents have either implemented IIoT, are running a pilot project, or are considering it.

Safety and Reliability as a Cornerstone of Industrial IoT Deployments


People often see the Industrial Internet of Things in a narrow view, namely, the ability to increase efficiency, productivity and cost savings. While that is true, it is a limited list of benefits based upon one's understanding of connectivity, data and information to influence behavior. There are several ways to lead organizational change, and it all depends on one's role and how they view their role in the organization. As an example, this month I attended a NORA (National Oil Recyclers Association) Environmental, Health & Safety workshop as a speaker. NORA represents the leading liquid recycling companies in used oil, antifreeze, oil filters & absorbents, parts cleaning, wastewater and chemicals.

The Industrial Internet of Things - Data Science Automation


The manufacturing industry is leading the way in IIoT (the Industrial Internet of Things) deployments. The key to a successful and rewarding deployment is an integrated approach, further including technologies such as big data analytics, cloud, robotics and, most importantly perhaps, the integration of IT (Information Technology) and OT (Operational Technology). For decades, the skilled data experts at Data Science Automation (DSA) have been making a big public impact with data acquisition and data analytics applied to diverse and challenging medical device, transportation, military, and energy applications. But today's challenge is to expand sensor-sourced and product-sourced data coverage, and to meaningfully leverage those extensive and growing data repositories with automation and analytics for deeper and more insightful correlations. Such advanced applications of Data Science will drive the next, and sure to be rapid, revolution in continuous improvements.

The Internet of Things in 2017: trends, technologies, market data and evolutions


In March 2017, market research firm Ovum released a list of essential Internet of Things trends for 2017, in collaboration with Internet of Things World. That seemed like a good opportunity to cover some major key IoT trends and predictions too. We tackle the 5 essential Internet of Things (IoT) trends worth watching in the overall Internet of Things market according to the the organizers of Internet of Things World 2017 and Ovum, add some context and comments and, while we were at it, add over a dozen IoT trends. First things first: the 5 IoT trends as reported by the two mentioned parties. Ovum stresses that 2016 was an important year for the Internet of Things but that 2017 is even more important and disruptive, both for the IoT technology players and the many industries where IoT projects are being deployed.

The Industrial Internet and the Industrial Internet of Things


We've explained what the Industrial Internet of Things (IIoT) is and posted an update on the state (and evolutions) regarding the IIoT market. Maybe you also have come across another term and concept, the Industrial Internet. Is there a difference between the Industrial Internet and the Internet of Things in an industrial context? What is the Industrial Internet anyway and does it matter? Here is what you need to know.