Intelligent space

The Operator 4.0 Concept and Intelligent Space

The most significant trend is related to the development of human-machine interfaces that embrace interaction in a set of novel ways. As the operator performs tasks, real-time information is provided about the production system and real-time support is received from it.

Interactive human-machine systems had already been introduced in the Hashimoto Laboratory at the of University of Tokyo where an Intelligent Space (iSpace) system has been designed for the virtual and physical support of people and mobile robots. Intelligent interaction space supports the operators to complete their work with high efficiency, high success rate, and low burden. The iSpace framework is shown in Figure~\ref{fig:framework}.

The events within iSpace are continuously monitored by Distributed Intelligent Network Devices (DINDs) consisting of various networked sensors, e.g. indoor positioning systems and cameras for localization. DINDs interpret events in the physical space and provide services (feedback) to operators using physical devices, e.g. microphones, displays, etc. According to the horizontal integration concept, the proposed iSpace is also connected to suppliers and customers. This concept highlights that iSpace should relay on CloudThings architecture that integrates Internet of Things (IoT) and Cloud Computing , as cloud computing enables a convenient, on demand, and scalable network access to a shared pool of configurable computing resources.

Resources, users, and tasks are the three core elements of intelligent interaction space. The user-resource-task model supports the design of interaction among these components which interactions should handle how resources trigger the tasks and how the tasks are assigned to the operators based on their availability, performance, and competence.

Intelligent space should respond to requests from people, so the activities of the operators must be identified by cameras, internal positioning systems, or based on voice signals, and these multi-sensory data should be processed by artificial intelligence and machine learning solutions. The acquired information is transmitted via a wireless network and processed by dedicated computers, so any event involving or change in the monitored parameters inside the space is carefully analyzed and processed.

Further information: