دانلود رایگان مقاله انگلیسی بررسی داده های آماری در اینترنت اشیا - MDPI 2018

Abstract:

With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study.

6. Conclusions

Current tendency shows that data semantization in IoT has become an essential part of daily life. It provides possibilities for knowledge interaction and sharing. Ontology modeling stands out a lot in adding semantics with the standardized description formats which give great ability to merge and exchange heterogenous information. The contribution of this survey consists of a general description of data semantization in IoT, including related concepts, general architectures, key techniques, applications and challenges. Techniques involved in data semantization have been introduced, and it is true that ontology modeling has become the most pervasive technique until now. Every entity, context, user and activity can be modeled through ontologies, with strong expressivity, expansibility and reasoning ability. This paper provides a general overview of data semantization, and makes a comparison betweeen different ontology models and automatic tools. Finally, the survey analyzes challenges and open issues including the standardization and generalization, complexity and dynamicity as well as security and privacy. This is a valuable area which will show great influence on future industry