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mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Industrial artificial intelligence technologies and applications
  name:
    name part: Vermesan, Ovidiu.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: dk
    place:
      place term: Gistrup, Denmark
    publisher: River Publishers
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: The advances in industrial edge artificial intelligence (AI) are transforming the way industrial equipment and machines interact with the real world, with other machines and humans during manufacturing processes. These advances allow Industrial Internet of Things (IIoT) and edge devices to make decisions during the manufacturing processes using sensors and actuators. Digital transformation is reshaping the manufacturing industry, and industrial edge AI aims to combine the potential advantages of edge computing (low latency times, reduced bandwidth, distributed architecture, improved trustworthiness, etc.) with the benefits of AI (intelligent processing, predictive solutions, classification, reasoning, etc.). The industrial environments allow the deployment of highly distributed intelligent industrial applications in remote sites that require reliable connectivity over wireless and cellular connections. Intelligent connectivity combines IIoT, wireless/cellular and AI technologies to support new autonomous industrial applications by enabling AI capabilities at the edge and allowing manufacturing companies to improve operational efficiency and reduce risks and costs for industrial applications. There are several critical issues to consider when introducing AI to industrial IoT applications considering training AI models at the edge, the deployment of the AI-trained inferencing models on the target edge hardware platforms, and the benchmarking of solutions compared to other implementations. Next-generation trustworthy industrial AI systems offer dependability in terms of their design, transparency, explainability, verifiability, and standardised industrial solutionscan be implemented in various applications across different industrial sectors. New AI techniques such as embedded machine learning (ML) and deep learning (DL), capture edge data, employ AI models, and deploy these inhardware target edge devices, from ultra-low-power microcontrollers to embedded devices, gate…
  note: editors; Ovidiu Vermesan, Franz Wotawa, Mario Diaz Nava, Bj̲rn Debaillie.
  note: Dr. Ovidiu Vermesan holds a Ph.D. degree in microelectronics and a Master of International Business (MIB) degree. He is Chief Scientist at SINTEF Digital, Oslo, Norway. His research interests are in smart systems integration, mixed-signal embedded electronics, analogue neural networks, edge artificial intelligence and cognitive communication systems. Dr. Vermesan received the SINTEF's 2003 award for research excellence for his work on the implementation of a biometric sensor system. He is currently working on projects addressing nanoelectronics, integrated sensor/actuator systems, communication, cyber-physical systems (CPSs) and Industrial Internet of Things (IIoT), with applications in green mobility, energy, autonomous systems, and smart cities. He has authored or co-authored over 100 technical articles, conference/workshop papers and holds several patents. He is actively involved in the activities of the European partnership for Key Digital Technologies (KDT). He has coordinated and managed various national, EU and other international projects related to smart sensor systems, integrated electronics, electromobility and intelligent autonomous systems such as E3Car, POLLUX, CASTOR, IoE, MIRANDELA, IoF2020, AUTOPILOT, AutoDrive, ArchitectECA2030, AI4DI, and AI4CSM. Dr. Vermesan actively participates in national, Horizon Europe and other international initiatives by coordinating and managing various projects. He is the coordinator of the IoT European Research Cluster (IERC) and a member of the board of the Alliance for Internet of Things Innovation (AIOTI). He is currently the technical co-coordinator of the Artificial Intelligence for Digitising Industry (AI4DI) project. Dr. Franz Wotawa received ab M.Sc. in Computer Science (1994) and a Ph.D. in 1996 both from the Vienna University of Technology. He is currently a professor of software engineering at the Graz University of Technology. From the founding of the Institute for Software Technology in 2003 to the year 20…
  subject:
    topic: Artificial intelligence
  subject:
    topic: Intelligence artificielle
  subject:
    topic: artificial intelligence
  subject:
    topic: COMPUTERS / Artificial Intelligence
  subject:
    topic: Intel·ligència artificial
  classification: Q335
  classification: 006.3
  identifier: 9781003377382
  identifier: 1003377386
  identifier: 9781000852035
  identifier: 1000852032
  identifier: 1000852059
  identifier: 9781000852059
  identifier: 9781003377382 Taylor & Francis
  identifier: https://www.taylorfrancis.com/books/9781003377382
  record info:
    record content source: SFB
    record creation date: 230906
    record change date: 20240130225821.4
    record identifier: in00004769557
    language of cataloging:
      language term: eng