The next generation of industrial systems is going to be data-driven. Sensor data driven by the Internet of Things, both inside and outside of factories, will provide a digital thread connecting the factory floor with its products and customers. These “chatty” factories present immense opportunities for innovation, from improving products based on their use, to digital twins that fuse product redesign with intelligent re-manufacturing, all connected via industrial optimisation, and relationships between intelligent robotics and their human counterparts that are yet to be determined.
The opportunities are clear. However, with digital innovation comes inherent cyber risk. Sensor data from the wild can only be used if it flows into decision-making processes linked to industrial modernisation. How do we know that the integrity of sensor data is not being corrupted, either deliberately or otherwise? What are the cyber risks to digital twins and how could these impact industrial elements of new production processes? How do we ensure that data-driven decisions are transparent and auditable? Will the convergence of technology in the wild with traditionally isolated operational technology prove too high-risk for widespread adoption?
This Special Issue aims to provide a forum for the discussion of both opportunity and cyber risk arising from data-driven industrial Internet of Things, with a key focus on the critical factors that will both enable and restrict adoption.
Prof. Dr. Pete Burnap