The Internet of Things (IoT) has changed our approach to safety systems by connecting sensors and providing real-time data to managers, rescuers, and endangered people. Hence, designing infrastructures to handle those possible crises has become an ever-increasing need. The increasing natural and man-induced disasters such as fires, earthquakes, floods, hurricanes, overcrowding, or pandemic viruses endanger human lives. We then assess various architectural models with different SW/HW configurations to propose the optimal model based on different scenarios concerning QoS-QoE requirements. Taking advantage of real data, we model scenarios related to humans’ speed, vision variations, grouping, and social attachment, which impact QoE.
We apply our approach to the Uffizi Galleries crowd management system. Our modeling approach facilitates choosing the best architectural model and system configuration to enhance both the humans’ and system’s sustainability. We design a simulation environment that combines agent-based social simulation (ABSS) with architectural models generated through a model-driven engineering approach. Such a modeling approach aligns the architectural design and associated quality of service (QoS) with humans’ quality of experience (QoE). Our approach relates the humans’ characteristics and intentions with the system’s goals, and models such interaction.
This paper highlights humans’ social and mobility behaviors’ role in the continuous engineering of sustainable socio-technical Internet of Things (IoT) systems. Taking advantage of real data, we model different scenarios that impact QoE. Our modeling approach facilitates choosing the best architectural model and system configuration to enhance both the humans' and system's sustainability. Such a modeling approach aligns the architectural design and associated quality of service (QoS) with humans' quality of experience (QoE). Our approach relates the humans' characteristics and intentions with the system's goals, and models such interaction. This paper highlights humans' social and mobility behaviors' role in the continuous engineering of sustainable socio-technical systems. The system was tested on several types of attacks such as network scan, Denial of Service (DOS), and malicious command injections. We present experimental analysis on a power-grid use case using the IEEE-33 bus model. The benefits of the presented approach are: 1) integrated architecture that supports acquisition and real-time analysis of both cyber and physical data 2) a metric for holistic health monitoring that allows for differentiation between physical faults, cyber intrusion, and cyber-physical attacks. We provide a data-driven approach for the detection of cyber and physical anomalies based on machine learning. In this paper, we present an approach for holistic health monitoring of cyber-physical systems based on cyber and physical anomaly detection and correlation. For successful health monitoring of such systems, a holistic approach is needed. However, despite the tight integration of cyber and physical components in modern critical infrastructures, the monitoring of cyber and physical subsystems is still done separately.
#Deisim vr world map software
This work illustrates the CAPS modeling languages used to describe the software architecture, hardware configuration, and physical space views for a situational aware CPS.Ĭoncerns of cyber-security threats are increasingly becoming a part of everyday operations of cyber-physical systems, especially in the context of critical infrastructures. New architectural concerns arise, especially related to the sense, compute & communication paradigm, the use of domain-specific hardware components, and the cyber-physical space dimension. While specializing cyber physical systems, Situational Aware CPS requires the continuous monitoring of environmental conditions and events with respect to time and space.
With the advent of cyber-physical systems (CPS), situational awareness is playing an increasingly important role especially in crowd and fleets management, infrastructure monitoring, and smart city applications. It has been recognized as a critical, yet often elusive, foundation for successful decision-making in complex systems. Situational Awareness involves being aware of what is happening in the surroundings, and using this information to decide and act. This paper proposes CAPS, an architecture-driven modeling framework for the development of Situational Aware Cyber-Physical Systems.