How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems

Multi-agent cyberphysical systems enable new capabilities in efficiency, resilience, and security. The unique characteristics of these systems prompt a reevaluation of their security concepts, including their vulnerabilities, and mechanisms to mitigate these vulnerabilities. This survey paper examines how advancement in wireless networking, coupled with the sensing and computing in cyberphysical systems, can foster novel security capabilities. This study delves into three main themes related to securing multi-agent cyberphysical systems. First, we discuss the threats that are particularly relevant to multi-agent cyberphysical systems given the potential lack of trust between agents. Second, we present prospects for sensing, contextual awareness, and authentication, enabling the inference and measurement of ``inter-agent trust" for these systems. Third, we elaborate on the application of quantifiable trust notions to enable ``resilient coordination," where ``resilient" signifies sustained functionality amid attacks on multiagent cyberphysical systems. We refer to the capability of cyberphysical systems to self-organize, and coordinate to achieve a task as autonomy. This survey unveils the cyberphysical character of future interconnected systems as a pivotal catalyst for realizing robust, trust-centered autonomy in tomorrow's world

Принципы создания прототипа цифрового двойника процесса алкилирования бензола пропиленом на основе нейронной сети

Objectives. To identify the principles of creating digital twins of an operating technological unit along the example of the process of liquid-phase alkylation of benzene with propylene, and to establish the sequence of stages of formation of a digital twin, which can be applied to optimize oil and gas chemical production.Methods. The chemical and technological system consisting of reactor, mixer, heat exchangers, separator, rectification columns, and pump is considered as a complex high-level system. Data was acquired in order to describe the functioning of the isopropylbenzene production unit. The main parameters of the process were calculated by simulation modeling using UniSim® Design software. A neural network model was developed and trained. The influence of various factors of the reaction process of alkylation, separation of reaction products, and evaluation of economic factors providing market interest of the industrial process was also considered. The adequacy of calculations was determined by statistics methods. A microcontroller prototype of the process was created.Results. A predictive neural network model and its creation algorithm for the process of benzene alkylation was developed. This model can be loaded into a microcontroller to allow for real-time determination of the economic efficiency of plant operation and automated optimization depending on the following factors: composition of incoming raw materials; the technological mode of the plant; the temperature mode of the process; and the pressure in the reactor.Conclusions. The model of a complex chemicotechnological system of cumene production, created and calibrated on the basis of long-term industrial data and the results of calculations of the output parameters, enables the parameters of the technological process of alkylation to be calculated (yield of reaction products, energy costs, conditional profit at the output of finished products). During the development of a hardware-software prototype, adapted to the operation of the real plant, the principles and stages of creating a digital twin of the operating systems of chemical technology industries were identified and formulated.Цели. Выявление принципов создания цифровых двойников реально действующей технологической установки на примере процесса жидкофазного алкилирования бензола пропиленом и установление последовательности этапов формирования цифрового двойника, которая может быть применима для оптимизации работы нефтегазохимического производства.Методы. Рассмотрена в целом химико-технологическая система, состоящая из реактора, смесителя, теплообменников, сепаратора, ректификационных колонн и насоса, как система высокого уровня. Выполнен сбор данных, описывающих функционирование установки получения изопропилбензола алкилированием бензола пропиленом путем расчета основных параметров процесса с помощью имитационного моделирования с применением специализированного программного обеспечения UniSim® Design. Разработана и обучена нейросетевая модель, учитывающая влияние различных факторов реакционного процесса алкилирования, разделения продуктов реакции и оценки экономических факторов, обеспечивающих рыночную привлекательность рассматриваемого промышленного процесса. Определена адекватность результатов расчетов оптимальных параметров процесса методами математической статистики. Создан прототип цифрового двойника процесса, реализованной на микроконтроллере.Результаты. Создана прогностическая нейросетевая модель и алгоритм ее построения для процесса алкилирования бензола пропиленом, позволяющая при загрузке ее в микроконтроллер обеспечить в режиме реального времени определение экономической эффективности работы установки и автоматическую оптимизацию работы установки в зависимости от состава поступающего сырья технологического режима системы, температурного режима проведения процесса и давления в реакторе.Выводы. Созданная модель сложной химико-технологической системы производства кумола, откалиброванная на основании промышленных данных длительного пробега технологической установки и результатов расчетов выходных параметров процесса при помощи нейронной сети, реализованной на микроконтроллере, позволяет рассчитать параметры технологического процесса алкилирования (выход продуктов реакции, энергетические затраты, условную прибыль при выпуске готовой продукции). В процессе разработки прототипа программно-аппаратного комплекса управления установкой алкилирования бензола пропиленом на основе данных, адаптированных к работе реальной установки, были выявлены и сформулированы принципы и этапы создания цифрового двойника производственных систем отраслей химической технологии

Collective intelligence in self-organized industrial cyber-physical systems

Cyber-physical systems (CPS) play an important role in the implementation of new Industry 4.0 solutions, acting as the backbone infrastructure to host distributed intelligence capabilities and promote the collective intelligence that emerges from the interactions among individuals. This collective intelligence concept provides an alternative way to design complex systems with several benefits, such as modularity, flexibility, robustness, and reconfigurability to condition changes, but it also presents several challenges to be managed (e.g., non-linearity, self-organization, and myopia). With this in mind, this paper discusses the factors that characterize collective intelligence, particularly that associated with industrial CPS, analyzing the enabling concepts, technologies, and application sectors, and providing an illustrative example of its application in an automotive assembly line. The main contribution of the paper focuses on a comprehensive review and analysis of the main aspects, challenges, and research opportunities to be considered for implementing collective intelligence in industrial CPS. The identified challenges are clustered according to five different categories, namely decentralization, emergency, intelligent machines and products, infrastructures and methods, and human integration and ethics. Although the research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, such approaches are still in the early stages, with perspectives to increase in the coming years. Based on that, they need to be further developed considering some main aspects, for example, related to balancing the distribution of intelligence by the vertical and horizontal dimensions and controlling the nervousness in self-organized systems.info:eu-repo/semantics/publishedVersio

Research Priorities for Robust and Beneficial Artificial Intelligence

Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.Comment: This article gives examples of the type of research advocated by the open letter for robust & beneficial AI at http://futureoflife.org/ai-open-lette

Industrial Internet of Things, Big Data, and Artificial Intelligence in the Smart Factory: a survey and perspective

International audienceThanks to the rapid development and applications of advanced technologies, we are experiencing the fourth industrial revolution, or Industry 4.0, which is a revolution towards smart manufacturing. The wide use of cyber physical systems and Internet of Things leads to the era of Big Data in industrial manufacturing. Artificial Intelligence algorithms emerge as powerful analytics tools to process and analyze the Big Data. These advanced technologies result in the introduction of a new concept in the Industry 4.0: the smart Factory. In order to fully understand this new concept in the context of the Industry 4.0, this paper provides a survey on the key components of a smart factory and the link between them, including the Industrial Internet of Things, Big Data and Artificial Intelligence. Several studies and techniques that are used to enable smart manufacturing are reviewed. Finally, we discuss some perspectives for further researches

Toward New Ecologies of Cyberphysical Representational Forms, Scales, and Modalities

Research on tangible user interfaces commonly focuses on tangible interfaces acting alone or in comparison with screen-based multi-touch or graphical interfaces. In contrast, hybrid approaches can be seen as the norm for established mainstream interaction paradigms. This dissertation describes interfaces that support complementary information mediations, representational forms, and scales toward an ecology of systems embodying hybrid interaction modalities. I investigate systems combining tangible and multi-touch, as well as systems combining tangible and virtual reality interaction. For each of them, I describe work focusing on design and fabrication aspects, as well as work focusing on reproducibility, engagement, legibility, and perception aspects

Cyber physical systems: A smart city perspective

Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed