Internet of Things (IoT) systems are becoming increasingly complex due to heterogeneity of devices and requirements for real-time processing and decision making. In this context, Artificial Intelligence (AI) technologies provide powerful capabilities for endowing IoT devices with intelligent services, leading to the so-called Artificial Intelligence of Things (AIoT). The operator is in the middle of this complexity, trying to understand the situation and make effective real-time decisions. Hence, human factors, especially cognitive ones, are a major issue to be addressed. The human cognitive part must be framed together with intelligent artefacts, requiring a systematic approach in the domain of joint cognitive systems. New software development methods in the form of assistants and wizards are necessary to help operators to be context-aware and reduce their technical workload regarding coding or computer-oriented skills, focusing on the task or service at hand. Building on previous research on the role of the human worker in an AIoT environment, this article analyses the described situation in terms of human cyber–physical systems, with the aim of proposing a conceptual framework for these assistance systems at the cognitive level. Two illustrative examples are described to validate the effectiveness of the proposed framework in collaborative tasks.

The use of collaborative robots (cobots) in industrial and academic settings facilitates physical and cognitive interaction with operators. This framework is a challenge to determine how measures on concepts, such as usability, can be adapted to these new environments. Usability is a quality attribute prevalent in the field of human-computer interaction concerning the context of use and the measure of effectiveness, efficiency, and satisfaction of products and systems. In this work, the importance of the role of benchmarking usability with collaborative robots is discussed. The introduced approach is part of a general methodology for studying people and robots’ performance in collaboration. It is being designed and developed on a concrete experience into a human-robot collaborative workspace. Outcomes from the study include a list of steps, resources, recommendations, and some customized questionnaires to obtain cobot-oriented usability analysis and case study results.

In human–robot collaborative assembly tasks, it is necessary to properly balance skills to maximize productivity. Human operators can contribute with their abilities in dexterous manipulation, reasoning and problem solving, but a bounded workload (cognitive, physical, and timing) should be assigned for the task. Collaborative robots can provide accurate, quick and precise physical work skills, but they have constrained cognitive interaction capacity and low dexterous ability. In this work, an experimental setup is introduced in the form of a laboratory case study in which the task performance of the human–robot team and the mental workload of the humans are analyzed for an assembly task. We demonstrate that an operator working on a main high-demanding cognitive task can also comply with a secondary task (assembly) mainly developed for a robot asking for some cognitive and dexterous human capacities producing a very low impact on the primary task. In this form, skills are well balanced, and the operator is satisfied with the working conditions.

In the industrial domain, one important research activity for cognitive robotics is the development of assistant robots. In this work, we show how the use of a cognitive assistant robot can contribute to (i) improving task effectiveness and productivity, (ii) providing autonomy for the human supervisor to make decisions, providing or improving human operators' skills, and (iii) giving feedback to the human operator in the loop. Our approach is evaluated on variability reduction in a manual assembly system. The overall study and analysis are performed on a model of the assembly system obtained using the Functional Resonance Analysis Method (FRAM) and tested in a robotic simulated scenario. Results show that a cognitive assistant robot is a useful partner in the role of improving the task effectiveness of human operators and supervisors.

Human cyber-physical systems (CPS) are an important component in the development of Industry 4.0.The paradigm shift of doing to thinking has allowed the emergence of cognition as a new perspective for intelligent systems.Currently, different platforms offer several cognitive solutions.Within this space, user assistance systems become increasingly necessary not as a tool but as a function that amplifies the capabilities of the operator in the work environment.There exist different perspectives of cognition.In this study cognition is introduced from the point of view of joint cognitive systems (JCSs); the synergistic combination of different technologies such as artificial intelligence (AI), the Internet of Things (IoT) and multi-agent systems (MAS) allows the operator and the process to provide the necessary conditions to do their work effectively and efficiently.

Este trabajo presenta una experiencia colaborativa en el ambito de la aplicaci6n del diseno de sistemas interactivos automatizados. EI seguimiento de directrices de diseno de interfaces ha perrnitido disminuir la complejidad de la interfaz de supervisi6n y facilitar el acceso a la gesti6n de las alarmas del sistema.