In future IoT big-data management and knowledge discovery for large scale industrial automation application, the importance of industrial internet is increasing day by day. Several diversified technologies such as IoT (Internet of Things), computational intelligence, machine type communication, big-data, and sensor technology can be incorporated together to improve the data management and knowledge discovery efficiency of large scale automation applications. So in this work, we need to propose a Cognitive Oriented IoT Big-data Framework (COIB-framework) along with implementation architecture, IoT big-data layering architecture, and data organization and knowledge exploration subsystem for effective data management and knowledge discovery that is well-suited with the large scale industrial automation applications. The discussion and analysis show that the proposed framework and architectures create a reasonable solution in implementing IoT big-data based smart industrial applications.
The authors in REF describe a cognitive-oriented IoT Big data framework (COIB framework) for the effective data management and knowledge discovery over the IoT Big data layering architecture.
A Cognitive Adopted Framework for IoT Big-Data Management and Knowledge Discovery Prospective
International Journal of Distributed Sensor Networks
Computer Science