IoT

Whilst bIoTope should be understood as a highly flexible and dynamic ecosystem capable of seamlessly integrating arbitrary proprietary IoT platforms, it nevertheless builds upon several core components, which provide essential functionality. Those functionalities referenced in this article, are agnostic to other ecosystem-external systems. Inside of the ecosystem, a micro-service-architecture MSA approach is applied. Using O-MI for technical Interoperability and O-DF for syntactic and semantic interoperability are foundation pillars of the ecosystem.

Securing the IoT poses specific challenges which are still only partially solved. These include the often very limited computing, storage, and energy resources of wirelessly connected IoT devices, the high demands on the user-friendliness, as well as the high-cost pressure. Upon this background, the research project PROPHYLAXE (“Providing Physical Layer Security for the Internet of Things”), funded by the BMBF, pursued a novel approach in which the physical properties of the wireless transmission link between two devices are exploited. Based on these properties, cryptographic keys can be generated that are known only to the communicating devices and can be used to secure and authenticate a connection.

Intensified networking and digitalization of systems affect an increasing number of sectors. At the same time a great variety of different concepts, ideas, expectations as well as fears have emerged around Industry 4.0. A look into the newspapers is enough to understand that the profound connection of critical structures does also hold profound dangers. For the future it is crucial to consider a way of using the new mass of data and information to protect these structures. Evaluating big data and transforming it into smart data with support of Artificial Intelligence will be a significant security factor in the future.

Predictive, or condition-based, maintenance is a shining goal for industrial customers and the Industrie 4.0 initiative. Supplementing, or even replacing, inefficient schedule-based maintenance with software promises to reduce equipment failures and unplanned downtime, improve safety and ultimately help the bottom line in an era of unstable prices and uncertain budgets. Predictive maintenance might be taking longer than expected, but in the next five years you might see it move faster than expected.