Open AccessAdaptive Cognitive Management and Knowledge Discovery Framework Based on Internet of Things Big Data
Author(s) -
Runxuan Bai,
JianYu Lv,
Chunnan Shang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/4/042080
Subject(s) - big data , computer science , data science , knowledge extraction , cognitive computing , automation , architecture , the internet , world wide web , artificial intelligence , data mining , engineering , cognition , mechanical engineering , art , neuroscience , biology , visual arts
In the future of large-scale industrial automation applications in the Internet of Things big data management and knowledge discovery, the importance of the industrial Internet is increasing day by day. The Internet of Things (IoT), computing intelligence, machine type communication, big data and sensor technology and other diversification. Technology can be combined to improve the efficiency of data management and knowledge discovery for large-scale automated applications. To this end, we need to propose a cognitive-oriented IoT big data framework (COIB-framework) and its implementation architecture, IoT big data hierarchical architecture, data organization and knowledge exploration subsystems to achieve effective data management and knowledge discovery suitable for large-scale industrial automation applications. In this work, we need to propose a cognitive-oriented IoT big data framework (COIB-framework), as well as implementation architecture, IoT big data layered architecture, data organization and knowledge mining subsystems, to meet the needs of large-scale industrial automation applications. Discussion and analysis show that the proposed framework and architecture are based on the intelligent industrial application of IoT big data provides a reasonable solution.