A Cyber-Physical System

The team was tasked with the creation of an autonomous cyber-physical system that could be continually developed as a post-capstone class by future STEM students and as a means to teach future engineering students. The strict definition of a cyber-physical system is a computation machine that networks with an embedded computer that performs a physical function. The autonomous aspect was achieved through two sonic sensors to monitor object distances in order to avoid walls and obstacles. The integrated system was based on the Intel Edison computation module. A primary goal for future addition is automation capabilities and machine learning applications

The Immune System: the ultimate fractionated cyber-physical system

In this little vision paper we analyze the human immune system from a computer science point of view with the aim of understanding the architecture and features that allow robust, effective behavior to emerge from local sensing and actions. We then recall the notion of fractionated cyber-physical systems, and compare and contrast this to the immune system. We conclude with some challenges.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455

Formalizing Cyber--Physical System Model Transformation via Abstract Interpretation

Model transformation tools assist system designers by reducing the labor--intensive task of creating and updating models of various aspects of systems, ensuring that modeling assumptions remain consistent across every model of a system, and identifying constraints on system design imposed by these modeling assumptions. We have proposed a model transformation approach based on abstract interpretation, a static program analysis technique. Abstract interpretation allows us to define transformations that are provably correct and specific. This work develops the foundations of this approach to model transformation. We define model transformation in terms of abstract interpretation and prove the soundness of our approach. Furthermore, we develop formalisms useful for encoding model properties. This work provides a methodology for relating models of different aspects of a system and for applying modeling techniques from one system domain, such as smart power grids, to other domains, such as water distribution networks.Comment: 8 pages, 4 figures; to appear in HASE 2019 proceeding

Design-Time Quantification of Integrity in Cyber-Physical-Systems

In a software system it is possible to quantify the amount of information that is leaked or corrupted by analysing the flows of information present in the source code. In a cyber-physical system, information flows are not only present at the digital level, but also at a physical level, and to and fro the two levels. In this work, we provide a methodology to formally analyse a Cyber-Physical System composite model (combining physics and control) using an information flow-theoretic approach. We use this approach to quantify the level of vulnerability of a system with respect to attackers with different capabilities. We illustrate our approach by means of a water distribution case study

Preventing Hospital Acquired Infections Through a Workflow-Based Cyber-Physical System

Hospital acquired infections (HAI) are infections acquired within the hospital from healthcare workers, patients or from the environment, but which have no connection to the initial reason for the patient's hospital admission. HAI are a serious world-wide problem, leading to an increase in mortality rates, duration of hospitalisation as well as significant economic burden on hospitals. Although clear preventive guidelines exist, studies show that compliance to them is frequently poor. This paper details the software perspective for an innovative, business process software based cyber-physical system that will be implemented as part of a European Union-funded research project. The system is composed of a network of sensors mounted in different sites around the hospital, a series of wearables used by the healthcare workers and a server side workflow engine. For better understanding, we describe the system through the lens of a single, simple clinical workflow that is responsible for a significant portion of all hospital infections. The goal is that when completed, the system will be configurable in the sense of facilitating the creation and automated monitoring of those clinical workflows that when combined, account for over 90\% of hospital infections.Comment: Proceedings of ENASE 2016, ISBN: 978-989-758-189-