cyber-physical system
description: engineered systems built and operated with seamless integration between physical components and computation
15 results
Fancy Bear Goes Phishing: The Dark History of the Information Age, in Five Extraordinary Hacks
by Scott J. Shapiro · 523pp · 154,042 words
cyber-enabled. Cyber-dependent war, by contrast, doesn’t use computers to control weapons—computers are the weapons. Cyber-dependent war has worried analysts because “cyber-physical” systems—systems that use computers to control physical devices so as to maximize efficiency, reliability, and convenience—have become commonplace. The Internet of Things that Mirai
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choice of which depends on the tactical needs of any military operation. Since stealth is a benefit of cyberweapons, the United States secretly infiltrated the cyber-physical system at the Natanz nuclear facility with Stuxnet to slow the Iranian development of nuclear weapons. For weak states, however, cyberweapons usually are the arsenal. These
Industry 4.0: The Industrial Internet of Things
by Alasdair Gilchrist · 27 Jun 2016
) models. They have driven innovation in the way we deploy multi-sensor devices into industrial system automation and integrate M2M with cyber-physical systems to create Industrial Internet of Things environments. Cyber Physical Systems (CPS) The Industrial Internet has come about due to the rapid advancements in digital computers in all their formats and vast improvements
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physical system–or a system that has all three, physical, network, and digital processing features. If it has, then it is said to be a cyber-physical system. In some definitions, the networking and communications feature is deemed optional, although that raises the question as to how a CPS differs from an embedded
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, are called “embedded systems”. These embedded systems are found in telecommunication, automation, and transport systems, among many others. Lately, a new term has surfaced, the cyber-physical systems (CPS). This distinguishes between microprocessor based embedded systems and more complex information processing systems that actually integrate with their environment. A precise definition of
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cyber-physical systems (CPS) is that they are integrations of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops
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where physical processes affect computations and vice versa. Therefore, a cyber-physical system can be just about anything that has integrated computation, networking, and physical processes. A human operator is a cyber-physical system and so is a smart factory. For example, a human operator has physical and cyber components
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—and they communicate with other humans and the system through HMI (human machine interface) and interact through mechanical interfaces—their hands—to influence their environment. Cyber-physical systems enable the virtual digital world of computers and software to merge through interaction—process management and feedback control—with the physical analogue world, thus leading
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CPS systems, unlike embedded Industry 4.0 systems, are networked, which allows for the possibility of the data being available remotely, even globally. In short, cyber-physical systems make it possible for software applications to interact with events in the physical world. For example, to measure peaks in energy consumption in an electrical
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of the first real smartphone, the IPhone. 39 40 Chapter 3 |TheTechnical and Business Innovators of the Industrial Internet The iPhone is a perfect mobile cyber-physical system with large processing power. It is packed with sensors and is capable of both wireless and cellular communications. It can run complex apps and interact
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great, but also can stretch beyond those boundaries and advance their capabilities and horizons even beyond their own planet. We can develop robots and other cyber-physical systems to do our biding in environments too dangerous or ferocious for life. Furthermore, humans can adapt, learn, and change our behavior and physical characteristics to
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fact that robots are indefatigable is of course their great strength, but they are extremely limited, or are at present. However, if robots or other cyber-physical systems could communicate through advanced M2M learning and communications, perhaps they could work collaboratively as a team, just like humans, but without the unpredictable performance driven
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in the future, industrial businesses will build global networks to connect their machinery, factories, and warehousing facilities as cyber-physical systems, which will connect and control each other intelligently by sharing information that triggers actions. These cyber-physical systems will take the shape of smart factories, smart machines, smart storage facilities, and smart supply chains. This
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the smart factory, which will alter the way production is performed, based on smart machines but also on smart products. It will not be just cyber-physical systems such as smart machinery that will be intelligent; the products being assembled will also have embedded intelligence so that they can be identified and located
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third-party entities in the supply chain through VPNs and Extranets; however, the connectivity was limited to human interaction. With the Industry 4.0 model, cyber-physical systems will interact with one another as well as humans to control the value chain. Benefits to Business One of the common misconceptions regarding Industry 4
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the focus, but Industry 4.0’s impact is more far-reaching than the boundaries of manufacturing. Industry 4.0 affects not only the local cyber-physical systems and local industrial processes but the entire value chain, including the producers and manufacturers, suppliers, and workers. One of the initial concerns raised in early
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, machine-to-machine communication, and within the context of human-machine-interaction, it is a vital component of the smart factory as it forms the cyber-physical systems. The CPS communicate through the Internet and, via the Internet of Things and services, produce new plant models and improves overall equipment effectiveness (OEE). However
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application protocol (CoAP), 128 advanced analytics, 84 queries, 83 storage, persistence, and retrieval serves, 83 Control area network (CAN), 181 Customers’ premise equipment (CPE), 42 Cyber-physical system (CPS), 36 D Data bus, 139 Data distribution service (DDS), 138 Data management, 82 Delay tolerant networks (DTN), 139 Distributed component object model (DCOM), 148
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and vertical system integration, 209 IOT, 209 products, 213 simulation, 209 smart manufacturing, 211 supply chains, 213 use of, robots, 209 workforce, 212 characteristics, 199 cyber-physical systems, 196 definitions, 197 design principles decentralization, 207 interoperability, 207 modularity, 208 real time capability, 208 services, 208 virtualization, 207 dynamic process control, 196 global networks
Building Secure and Reliable Systems: Best Practices for Designing, Implementing, and Maintaining Systems
by Heather Adkins, Betsy Beyer, Paul Blankinship, Ana Oprea, Piotr Lewandowski and Adam Stubblefield · 29 Mar 2020 · 1,380pp · 190,710 words
OpenSSL, and will fail if the results ever differ. 6 For an example, see Bozzano, Marco et al. 2017. “Formal Methods for Aerospace Systems.” In Cyber-Physical System Design from an Architecture Analysis Viewpoint, edited by Shin Nakajima, Jean-Pierre Talpin, Masumi Toyoshima, and Huafeng Yu. Singapore: Springer. 7 You can install Clang
Data Mining: Concepts and Techniques: Concepts and Techniques
by Jiawei Han, Micheline Kamber and Jian Pei · 21 Jun 2011
this book. Such mining includes mining time-series, sequential patterns, and biological sequences; graphs and networks; spatiotemporal data, including geospatial data, moving-object data, and cyber-physical system data; multimedia data; text data; web data; and data streams. Section 13.2 briefly introduces other approaches to data mining, including statistical methods, theoretical foundations
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mining graphs and social and information networks. Section 13.1.3 addresses mining other kinds of data, including spatial data, spatiotemporal data, moving-object data, cyber-physical system data, multimedia data, text data, web data, and data streams. Due to the broad scope of these themes, this section presents only a high-level
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in or dynamically streamed through a system, and call for specialized data mining methodologies. Thus, mining multiple kinds of data, including spatial data, spatiotemporal data, cyber-physical system data, multimedia data, text data, web data, and data streams, are increasingly important tasks in data mining. In this subsection, we overview the methodologies for
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-object data mining include mining periodic patterns for one or a set of moving objects, and mining trajectory patterns, clusters, models, and outliers. Mining Cyber-Physical System Data A cyber-physical system (CPS) typically consists of a large number of interacting physical and information components. CPS systems may be interconnected so as to form large heterogeneous
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a battlefield commander system that links a sensor/reconnaissance network with a battlefield information analysis system. Clearly, cyber-physical systems and networks will be ubiquitous and form a critical component of modern information infrastructure. Data generated in cyber-physical systems are dynamic, volatile, noisy, inconsistent, and interdependent, containing rich spatiotemporal information, and they are critically important
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explored—for example, real-time detection of anomalies in computer network traffic, botnets, text streams, video streams, power-grid flows, web searches, sensor networks, and cyber-physical systems. 13.2. Other Methodologies of Data Mining Due to the broad scope of data mining and the large variety of data mining methodologies, not all
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knowledge discovery methods and applications for large numbers of network data is essential, as outlined in Section 13.1.2. ■ Mining spatiotemporal, moving-objects, and cyber-physical systems: Cyber-physical systems as well as spatiotemporal data are mounting rapidly due to the popular use of cellular phones, GPS, sensors, and other wireless equipment. As outlined in
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mining sequence data such as time series, symbolic sequences, and biological sequences; mining graphs and networks; and mining other kinds of data, including spatiotemporal and cyber-physical system data, multimedia, text and Web data, and data streams. ■ Several well-established statistical methods have been proposed for data analysis such as regression, generalized linear
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data mining with web service, database, warehousing, and cloud computing systems; and mining social and information networks. Other trends include the mining of spatiotemporal and cyber-physical system data, biological data, software/system engineering data, and multimedia and text data, in addition to web mining, distributed and real-time data stream mining, visual
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subset selection 160see alsodata cubes curse of dimensionality 158, 179 customer relationship management (CRM) 619 customer retention analysis 610 CVQE. seeConstrained Vector Quantization Error algorithm cyber-physical systems (CPS) 596, 623–624 D data antimonotonicity 300 archeology 6 biological sequence 586, 590–591 complexity 32 conversion to knowledge 2
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cyber-physical system 596 for data mining 8 data warehouse 13–15 database 9–10 discrimination 16 dredging 6 generalizing 150 graph 14 growth 2 linearly inseparable 413–
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migration tools 93 data mining 5–8, 33, 598, 623 ad hoc 31 applications 607–618 biological data 624 complex data types 585–598, 625 cyber-physical system data 596 data streams 598 data types for 8 data warehouses for 154 database types and 32 descriptive 15 distributed 615, 624 efficiency 31 foundations
Chaos Engineering: System Resiliency in Practice
by Casey Rosenthal and Nora Jones · 27 Apr 2020 · 419pp · 102,488 words
at scale. The following chapter, Chapter 17, “Let’s Get Cyber-Physical,” takes a half-step away from software into the realm of hardware with cyber-physical systems (CPSs). “It turns out that when you get a lot of highly experienced, cross-disciplinary people together over a long enough period of time to
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while chasing the next great breakthrough innovations We consider these topics within the context of cyber-physical systems. The Rise of Cyber-Physical Systems There are many ecosystems unfamiliar to most software engineers where software is still the centerpiece driving innovation. Cyber-physical systems (CPSs) comprise one such ecosystem. A CPS is an interconnected hardware-software system that is
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entirely from the loop or are interacting at much further distance, often through multiple system abstractions, from the critical interfaces and operations within. Software in Cyber-Physical Systems Software has some unique properties that make it especially problematic when there are residual faults in its implementation (known issues), latent faults in its implementation
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, Economic Pillars of Complexity Applied to Software goals of, Formalizing the Discipline, Breaking Stuff, Chaos Engineering and Resilience, ROI of Chaos Engineering, The Rise of Cyber-Physical Systems history of, Introduction: Birth of Chaos-Fast Evolution Human and Organizational Performance (HOP) and, HOP Meets Chaos Engineering-Chaos Engineering and HOP in Practice in
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systemsaccidental complexity in, Accidental Complexity consequences of, Contemplating Complexity, Why Is Everything So Complicated?-A Simple System Is the Tip of the Iceberg Cyber-Physical Systems (CPS), The Rise of Cyber-Physical Systems defined, Setting the Stage Economic Pillars of Complexity model, Economic Pillars of Complexity-Economic Pillars of Complexity Applied to Software embracing complexity, Embracing
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Are a System of Systems correctness, continuous verification for, Correctness Crowley, Richard, Principles in Action, Slack’s Disasterpiece Theater-Conclusion Customer Resource Definition (CRD) , Conclusion Cyber-Physical Systems (CPS)Chaos Engineering as a step beyond FMEA, Chaos Engineering as a Step Beyond FMEA-Chaos Engineering as a Step Beyond FMEA Functional Safety standards
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, Functional Safety Meets Chaos Engineering-FMEA and Chaos Engineering probe effect, Probe Effect-Addressing the Probe Effect rise of, The Rise of Cyber-Physical Systems software in, Software in Cyber-Physical Systems-Software in Cyber-Physical Systems cybersecurity (see Security Chaos Engineering (SCE)) D Dapper, Observability: The Opportunity dark debt, Putting the “Socio” in Sociotechnical Systems data integrity, Data
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operations, Datacenter operations in older systems, Design Patterns Common in Older Systems Failure Mode and Effects Analysis (FMEA), Functional Safety Meets Chaos Engineering-Software in Cyber-Physical Systems failuresas learning in action, If You’re Not Failing, You’re Not Learning detecting with Prometheus, Detecting Failures failure modes, Failure Modes human factors and
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-At/Machines-Are-Better-At Functional SafetyChaos Engineering and, FMEA and Chaos Engineering facets of, Functional Safety Meets Chaos Engineering goals of, The Rise of Cyber-Physical Systems fuzz testing, Data integrity G Game DaysCapital One's approach to, Team Structure design phase of, Collateral ROI determining team roles, Hypothesize evangelizing Chaos Engineering
Autonomous Driving: How the Driverless Revolution Will Change the World
by Andreas Herrmann, Walter Brenner and Rupert Stadler · 25 Mar 2018
efficiency, increasing vehicle automation will also significantly extend the range of electric vehicles [148]. The essence of autonomous driving is the development of vehicles into cyber-physical systems that comprise a combination of mechanical and electronic components. A vehicle’s hardware and software exchange certain data about the infrastructure (the Internet of Things
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dealers, 207 persuasion, 207 208 statements by two early adopters, 205 Cyber attacks, 141 Cyber hacking or failures in algorithms, 354 Cyber security, 141 146 Cyber-physical systems, 9 Daimler, 130 Data, 121 categories in vehicle, 147 creators, 320 322 431 from passengers, 94 95 privacy, 147 148 processing, 91 protection principles, 148
The Truth Machine: The Blockchain and the Future of Everything
by Paul Vigna and Michael J. Casey · 27 Feb 2018 · 348pp · 97,277 words
much more dangerous than one who can eavesdrop on your conversation or track your car’s location.” With the Internet of Things and other such “cyber-physical systems,” Schneier said, “we’ve given the Internet hands and feet: the ability to directly affect the physical world. What used to be attacks against data
Future War: Preparing for the New Global Battlefield
by Robert H. Latiff · 25 Sep 2017 · 158pp · 46,353 words
new features, until the project becomes unworkable, unnecessarily expensive, or even useless upon arrival. The way we’re headed with advanced artificial intelligence, autonomy, and cyber-physical systems seems like more technology seduction. Technology always promises something better, often with an illusion of objectivity. Solving problems seems to require little subjective thought. If
Human Frontiers: The Future of Big Ideas in an Age of Small Thinking
by Michael Bhaskar · 2 Nov 2021
term, as it is a coherent concept. The 4IR is less a historical fact, more a loosely assembled set of conference talking points notionally about ‘cyber-physical systems’, a handy label for a basket of potentially transformative but still nascent technologies that face a host of technical, ethical and social barriers. In the
Stakeholder Capitalism: A Global Economy That Works for Progress, People and Planet
by Klaus Schwab and Peter Vanham · 27 Jan 2021 · 460pp · 107,454 words
era of automation. Back in 2015, I realized we were at the dawn of a new era—one of artificial intelligence, advanced robotics, and integrated cyber-physical systems—and that together they constituted a Fourth Industrial Revolution. The new technologies we were witnessing, including also 3D printing, quantum computing, precision medicine, and others
Hands-On RESTful API Design Patterns and Best Practices
by Harihara Subramanian · 31 Jan 2019 · 422pp · 86,414 words
The Smart Wife: Why Siri, Alexa, and Other Smart Home Devices Need a Feminist Reboot
by Yolande Strengers and Jenny Kennedy · 14 Apr 2020
Stakeholder Capitalism: A Global Economy That Works for Progress, People and Planet
by Klaus Schwab · 7 Jan 2021 · 460pp · 107,454 words
Work: A History of How We Spend Our Time
by James Suzman · 2 Sep 2020 · 909pp · 130,170 words
Inventors at Work: The Minds and Motivation Behind Modern Inventions
by Brett Stern · 14 Oct 2012 · 486pp · 132,784 words