IoT and Cognitive systems

The Internet of Things is in its infancy. Industrial Automation is ahead of most other industries in the readiness for the Internet of Things (IoT) and more specifically for the Industrial Internet of Things (IIoT). 


PLCs have evolved  to provide a dependable and rugged means of monitoring and controlling processes and equipment. By adapting to market demands and emerging connectivity and communication standards, the PLC continues to be widely used by industrial equipment and factory designers. The latest micro and nano form factors should secure the PLC’s position in the IIoT and at the heart of Industry 4.0.

The Industrial Internet of Things will change how Industrial Automation networks are designed and used. IIoT will increase the productivity of the Industrial Automation network. With the large number of currently deployed connected end-devices, the understanding of the value of new data that is available at the end-device, the deployment of cyber security practices, Industrial Automation is already part of the Internet of Things. There are more changes to come for Industrial Automation and IIoT. Industrial Automation is ready for these changes as well.


https://videos.cdn.sap.com/vod/2015/ext/piaggio-group-stepping-into-the-era-of-connected-mobility-with-sap-and-the-internet-of-things-ctv.mp4

Cognitive IoT, AI and machine learning enable enterprises to unlock IoT value. An exploding amount of IoT data requires a new approach to gather, analyze and understand. And that massive amount of sensor and device information can be used to enhance what’s already known.

While making sense out of dark data and edge data paves our way to revolutionary ideas and technologies, it requires a cognitive approach. One that can effectively handle increasingly large inputs while generating meaningful output. Programmable systems thrive on prescribed scenarios using predictable data. But their rigidity can limit their usefulness when addressing the ambiguity and uncertainty of IoT data. Cognitive systems, however, are not explicitly programmed. They learn from interactions with people and from experiences with their environment. And in doing so, they become able to keep pace with the complexity of the Internet of things, identifying data correlations that would otherwise go unnoticed.

“It is using new technologies such as data analytics, the cloud, and the Internet of Things (IoT) to merge the virtual and real worlds. It enables manufacturers to increase productivity across their entire value chain, from design and engineering to sales, production, and service. In concrete terms, this means faster time-to-market, greater flexibility, and enhanced availability of systems on the plant floor.” --Jeff Hall, a Siemens global account manager

“Cognitive systems are probabilistic, meaning they are designed to adapt and make sense of the complexity and unpredictability of unstructured information. They can ‘read’ text, ‘see’ images, and ‘hear’ natural speech. And they interpret that information, organize it, and offer explanations of what it means, along with the rationale for their conclusions.” --
Dr. John E. Kelly III, Senior Vice President, IBM Research.