The Disruptive Power of Machine Learning and IoT in Automation Industry

被引:0
|
作者
Bilgic, Attila M. [1 ]
机构
[1] KROHNE Grp, Ludwig Krohne Str 5, D-47058 Duisburg, Germany
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the past decades the automation industry was evolving at modest pace, mainly driven by innovations in mechanical design and utilizing basic principles from physics or chemistry. What was already known was continuously improved and aspects like requirements for environmental and human protection increased over the years and were more and more formalized leading i.e. to complex procedures for safety designs. The innovations of the IT world which continuously gained speed especially over the last decade were taken over rather reluctantly. But recent trends show a growing push of IT technologies into every field of industrial application, frequently named as industry 4.0 or 4th industrial revolution. We will look at opportunities and threads created by the technological changes, touch preconditions for success and pitfalls for failure. Analyzing the past trends of both IT and industrial automation will allow us for some astonishing predictions for the next decade.
引用
收藏
页码:103 / 103
页数:1
相关论文
共 50 条
  • [31] Machine learning and deep learning approaches in IoT
    Javed A.
    Awais M.
    Shoaib M.
    Khurshid K.S.
    Othman M.
    PeerJ Computer Science, 2023, 9
  • [32] Machine learning and deep learning approaches in IoT
    Javed, Abqa
    Awais, Muhammad
    Shoaib, Muhammad
    Khurshid, Khaldoon S.
    Othman, Mahmoud
    PEERJ COMPUTER SCIENCE, 2023, 9 : 1 - 30
  • [33] Role of Machine Learning in ETL Automation
    Mondal, Kartick Chandra
    Biswas, Neepa
    Saha, Swati
    PROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING (ICDCN 2020), 2020,
  • [34] Machine Learning in Incident Categorization Automation
    Silva, Sara
    Pereira, Ruben
    Ribeiro, Ricardo
    2018 13TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2018,
  • [35] Conveying automation potential with machine learning
    Schönhof, Raoul
    Konstruktion, 2019, 2019 (7-8): : 92 - 93
  • [36] Machine Learning and Automation in Concurrent Engineering
    Vijayakumar, K.
    CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, 2022, 30 (02): : 133 - 134
  • [37] Automation of Society Security Using Deep Learning and IoT
    Gutal, Akanksha
    Bhamare, Tejaswari
    Mayekar, Ankita
    Deshmukh, Prasad
    PROCEEDINGS OF THE 2021 FIFTH INTERNATIONAL CONFERENCE ON I-SMAC (IOT IN SOCIAL, MOBILE, ANALYTICS AND CLOUD) (I-SMAC 2021), 2021, : 96 - 102
  • [38] Blockchain and Machine Learning for Intelligent Automation in Robotic Process Automation
    José G. Jacome-Leon
    Marcelo Zambrano-Vizuete
    Daisy E. Imbaquingo-Esparza
    Miguel Botto-Tobar
    SN Computer Science, 6 (4)
  • [39] Machine learning and data analytics for the IoT
    Adi, Erwin
    Anwar, Adnan
    Baig, Zubair
    Zeadally, Sherali
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (20): : 16205 - 16233
  • [40] Machine Learning Security Allocation in IoT
    Karthika, P.
    Babu, R. Ganesh
    Nedumaran, A.
    PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS), 2019, : 474 - 478