Guest Editorial: Computational Intelligence for Human-in-the-Loop Cyber Physical Systems

Abstract

The papers in this special section focus on human-in-the-loop cyber-physical systems. Recent advances in computational intelligence, real-time computing and control, have given momentum to Humanin-the-Loop Cyber Physical Systems (HitLCPS) to enable gamechanging communication and collaboration paradigms that operate in connection with humans’ natural behaviour patterns. Despite the ongoing advancement of computational intelligence techniques for analyzing the interactions between the cognitive and cyber domains, there are growing concerns regarding the security, privacy, and safety of humans when they interact with smart cyber physical environments (IoT ecosystems). The large-scale integration of heterogeneous IoT devices to manage and control a wide variety of sensors and settings will hugely increase the attack surface and the scope for misconfigurations. These could lead to unsafe or conflicting behaviour of various devices and subsystems, which in turn, can place the human in unsafe and hazardous situations, both mentally and physically. It is still unclear how to design optimized collaborative systems between people and machines in a scalable manner, how to design triggers for pro-active engagement and disengagement, and how to handle the consequences of implied actions. For example, when the system misbehaves as a result of erroneous data, it is important to have real-time rules that can guarantee a fail-safe state for the HitLCPS. The verification of operations in a large HitLCPS can be very complex due to the evolving nature of human-in-the-loop networks both in terms of physical aspects and the operational environment. Therefore, understanding the semantics of HitLCPS and the context of control behaviour is critical to detect or entirely avoid incorrect configurations and build a proactive resilience and a reactive defence against evolving threats.