1,846 research outputs found
Cyber-Agricultural Systems for Crop Breeding and Sustainable Production
The Cyber-Agricultural System (CAS) Represents an overarching Framework of Agriculture that Leverages Recent Advances in Ubiquitous Sensing, Artificial Intelligence, Smart Actuators, and Scalable Cyberinfrastructure (CI) in Both Breeding and Production Agriculture. We Discuss the Recent Progress and Perspective of the Three Fundamental Components of CAS – Sensing, Modeling, and Actuation – and the Emerging Concept of Agricultural Digital Twins (DTs). We Also Discuss How Scalable CI is Becoming a Key Enabler of Smart Agriculture. in This Review We Shed Light on the Significance of CAS in Revolutionizing Crop Breeding and Production by Enhancing Efficiency, Productivity, Sustainability, and Resilience to Changing Climate. Finally, We Identify Underexplored and Promising Future Directions for CAS Research and Development
Cyber-Physical Systems for Micro-/Nano-assembly Operations: a Survey
Abstract
Purpose of Review
Latest requirements of the global market force manufacturing systems to a change for a new production paradigm (Industry 4.0). Cyber-Physical Systems (CPS) appear as a solution to be deployed in different manufacturing fields, especially those with high added value and technological complexity, high product variants, and short time to market. In this sense, this paper aims at reviewing the introduction level of CPS technologies in micro/nano-manufacturing and how these technologies could cope with these challenging manufacturing requirements.
Recent Findings
The introduction of CPS is still in its infancy on many industrial applications, but it actually demonstrates its potential to support future manufacturing paradigm. However, only few research works in micro/nano-manufacturing considered CPS frameworks, since the concept barely appeared a decade ago.
Summary
Some contributions have revealed the potential of CPS technologies to improve manufacturing performance which may be scaled to the micro/nano-manufacturing. IoT-based frameworks with VR/AR technologies allow distributed and collaborative systems, or agent-based architectures with advance algorithm implementations that improve the flexibility and performance of micro-/nano-assembly operations. Future research of CPS in micro-/nano-assembly operations should be followed by more studies of its technical deployment showing its implications under other perspectives, i.e. sustainable, economic, and social point of views, to take full advance of all its features
2020 NASA Technology Taxonomy
This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world
GPS Anomaly Detection And Machine Learning Models For Precise Unmanned Aerial Systems
The rapid development and deployment of 5G/6G networks have brought numerous benefits such as faster speeds, enhanced capacity, improved reliability, lower latency, greater network efficiency, and enablement of new applications. Emerging applications of 5G impacting billions of devices and embedded electronics also pose cyber security vulnerabilities. This thesis focuses on the development of Global Positioning Systems (GPS) Based Anomaly Detection and corresponding algorithms for Unmanned Aerial Systems (UAS). Chapter 1 provides an overview of the thesis background and its objectives. Chapter 2 presents an overview of the 5G architectures, their advantages, and potential cyber threat types. Chapter 3 addresses the issue of GPS dropouts by taking the use case of the Dallas-Fort Worth (DFW) airport. By analyzing data from surveillance drones in the (DFW) area, its message frequency, and statistics on time differences between GPS messages were examined. Chapter 4 focuses on modeling and detecting false data injection (FDI) on GPS. Specifically, three scenarios, including Gaussian noise injection, data duplication, data manipulation are modeled. Further, multiple detection schemes that are Clustering-based and reinforcement learning techniques are deployed and detection accuracy were investigated. Chapter 5 shows the results of Chapters 3 and 4. Overall, this research provides a categorization and possible outlier detection to minimize the GPS interference for UAS enhancing the security and reliability of UAS operations
Metaverse: A Vision, Architectural Elements, and Future Directions for Scalable and Realtime Virtual Worlds
With the emergence of Cloud computing, Internet of Things-enabled
Human-Computer Interfaces, Generative Artificial Intelligence, and
high-accurate Machine and Deep-learning recognition and predictive models,
along with the Post Covid-19 proliferation of social networking, and remote
communications, the Metaverse gained a lot of popularity. Metaverse has the
prospective to extend the physical world using virtual and augmented reality so
the users can interact seamlessly with the real and virtual worlds using
avatars and holograms. It has the potential to impact people in the way they
interact on social media, collaborate in their work, perform marketing and
business, teach, learn, and even access personalized healthcare. Several works
in the literature examine Metaverse in terms of hardware wearable devices, and
virtual reality gaming applications. However, the requirements of realizing the
Metaverse in realtime and at a large-scale need yet to be examined for the
technology to be usable. To address this limitation, this paper presents the
temporal evolution of Metaverse definitions and captures its evolving
requirements. Consequently, we provide insights into Metaverse requirements. In
addition to enabling technologies, we lay out architectural elements for
scalable, reliable, and efficient Metaverse systems, and a classification of
existing Metaverse applications along with proposing required future research
directions
Special Session on Industry 4.0
No abstract available
Chapter 3 How is production changing?
The unprecedented Covid-19 crisis revealed the scale and scope of a new type of economy taking shape in front of our very eyes: the digital economy. This book presents a concise theoretical and conceptual framework for a more nuanced analysis of the economic and sociological impacts of the technological disruption that is taking place in the markets of goods and services, labour markets, and the global economy more generally. This interdisciplinary work is a must for researchers and students from economics, business, and other social science majors who seek an overview of the main digital economy concepts and research. Its down-to-earth approach and communicative style will also speak to businesses practitioners who want to understand the ongoing digital disruption of the market rules and emergence of the new digital business models. The book refers to academic insights from economics and sociology while giving numerous empirical examples drawn from basic and applied research and business. It addresses several burning issues: how are digital processes transforming traditional business models? Does intelligent automation threaten our jobs? Are we reaching the end of globalisation as we know it? How can we best prepare ourselves and our children for the digitally transformed world? The book will help the reader gain a better understanding of the mechanisms behind the digital transformation, something that is essential in order to not only reap the plentiful opportunities being created by the digital economy but also to avoid its many pitfalls
Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities
In recent years, ubiquitous semantic Metaverse has been studied to
revolutionize immersive cyber-virtual experiences for augmented reality (AR)
and virtual reality (VR) users, which leverages advanced semantic understanding
and representation to enable seamless, context-aware interactions within
mixed-reality environments. This survey focuses on the intelligence and
spatio-temporal characteristics of four fundamental system components in
ubiquitous semantic Metaverse, i.e., artificial intelligence (AI),
spatio-temporal data representation (STDR), semantic Internet of Things (SIoT),
and semantic-enhanced digital twin (SDT). We thoroughly survey the
representative techniques of the four fundamental system components that enable
intelligent, personalized, and context-aware interactions with typical use
cases of the ubiquitous semantic Metaverse, such as remote education, work and
collaboration, entertainment and socialization, healthcare, and e-commerce
marketing. Furthermore, we outline the opportunities for constructing the
future ubiquitous semantic Metaverse, including scalability and
interoperability, privacy and security, performance measurement and
standardization, as well as ethical considerations and responsible AI.
Addressing those challenges is important for creating a robust, secure, and
ethically sound system environment that offers engaging immersive experiences
for the users and AR/VR applications.Comment: 18 pages, 7 figures, 3 table
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