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This study focuses on the question of how humans can be inherently integrated into cyber-physical systems (CPS) to reinforce their involvement in the increasingly automated industrial processes. After a use-case oriented review of the related research literature, a human-integration framework and associated data models are presented as part of a multi-agent IoT middleware called CHARIOT. The framework enables human actors to be semantically represented and registered, together with other IoT entities, in a common service directory, thereby facilitating their inclusion in complex service chains. To validate and evaluate the proposed framework, a user study is conducted on a setup where a human and a robot arm collaborate on a “pick-assemble-place” job on a conveyor belt. Based on the human skill set parameters obtained from the user study, online and offline variants of task assignment on the conveyor belt setup are implemented and analyzed over the presented framework. The results illustrate possible efficiency gains through the consolidated online monitoring and control of all cyber-physical system entities, including human actors.

Connecting a massive number of sensors and actuators with energy and transmission constraints is only possible by providing a reliable connection despite the increase in data traffic due to the Internet of Things, and by guaranteeing a maximum end-to-end delay for applications with real-time constraints. Next generation network architectures need to satisfy these two requirements while connecting IoT sources producing data at massive scales to cloud resources that provide the capability to process and store this data. For this reason, realization of IoT in next generation cellular networks faces the problem of delivering cloud services over the network to things that are placed anywhere. In this study, we explain how the technologies envisioned for next generation networks can respond to the challenge of realizing IoT over a use case prepared for the IoT smart home platform called IOLITE. We start by discussing capacity requirements and focus on network densification as a promising solution method. The challenges of network densification can be overcome by integrating the technological enablers such as SDN, C-RAN, SON, and mobile edge computing. For this reason, we provide a thorough survey on the state of the art in integrating these enablers for a flexible network architecture at all network segments. Finally, we discuss how the needs of the IOLITE community use case scenario can be satisfied by implementing a service- centric abstraction layer on top of a flexible infrastructure for beyond 5G IoT applications.

The Internet of Things (IoT) is envisioned to facilitate rich interactions among heterogeneous entities, ranging from simple sensing devices to complex robotic devices and from autonomous service agents to human actors. The complexity and multimodality of human actors require specific interfaces for their integration with IoT frameworks that provide suitable software architectures, data models, protocols, message types, and applications. This study focuses on the requirements and design approaches for integrating human actors in a Cyber-Physical System (CPS) within the application domain of Industry 4.0. After a systematic review and taxonomy of the related research literature, the design and implementation of a comprehensive human-integration framework is presented as part of a multi-agent IoT middleware called CHARIOT. Example applications that are developed to exploit the human integration capabilities of CHARIOT middleware are then presented, which extract data from human activities, enable multimodal interaction between humans and other IoT entities, and assist different human roles in a smart factory environment to satisfy the human-CPS integration requirements.