2018 | OriginalPaper | Chapter
5. Internet of Things (IoT)
Published in:
Mit Innovationsmanagement zu Industrie 4.0
Zusammenfassung
IoT – the Internet of Things – is part of the dramatic changes sometimes referred to as “digital transformation” or “digital disruption”. The combination of new disruptive business models based upon networked environments, an ubiquitous sensor and actuator infrastructure and the availability of “limitless” computing power and data storage are key drivers of IoT. All of this combined with a socio-economic environment to exploit the potentials of all systems (power grids, hospitals, banks, fleets of locomotives, cars, airplanes, aso.)
for all users (manufacturers, operators, professionals, consumers) have created the current IoT hype.
Dealing with IoT we learned that four key issues require special attention when dealing with IoT solutions: Standards, Security, Code and Knowledge and the Integration of Humans.
Performance, cost and feasibility to connect sensors, actuators, existing and new infrastructure on a global basis to collect data and implement means to intelligently react upon such information depends among other things on the availability of ready to use, proven and robust standards. Unfortunately there is not a single standard to do the job and only part of the installed base really consists of devices and (software) applications that adhere to such standards. The ability to deal with proprietary interfaces in the field is therefore extremely important while at the same time knowledge about existing standards and driving new standards is of key importance when implementing IoT projects.
Another extremely important subject is “security”. IoT requires to deal with all aspects of security in an extremely professional way, i.e. computer and network security, data privacy and protection, both by design and from a day-to-day operational perspective. EU’s new General Data Protection Regulation (GDPR) will come into force on the 25th of May 2018. This and increasing cyber crime activities mandate appropriate security measures.
IoT is tightly connected with data analysis and machine learning. This is one of the reasons why we need to have a clear understanding about code and knowledge and how to distinguish between and deal with the two disciplines.
And last but not least IoT is not limited to 100% automated robotic environments. We (humans) are still part of the equation, be it as those who invent and manufacture components or design the IoT solution, humans are operating complex IoT infrastructure or we are users. It is thus extremely important to have a crystal clear picture about roles of human beings and the way how we interact in IoT environments with complex machinery.
