Survey on IoT Data Analytics with Semantic Approaches
Truong Khanh Duy, Josef Küng, Hoàng Hữu Hạnh · 2021
Data generated from the Internet of Things (IoT) devices that are mostly cheap enough for any specific use case. It shows the ability to gather data about the physical environment and to understand real-time context, combining with other heterogeneous data sources such as sensor networks, social media, crowdsource data collections, etc. Data analytics can enable a massive set of new services for IoT applications. The management of data in an ultra-scale network which is continuously expanding leads to concerns in data analytics and management. The researchers have examined the challenge of interoperability of applications and services among IoT applications to address them. The common problems of interoperability come from different levels, from syntactic to semantic. In this paper, we take a broad view of current IoT analytics work where Semantic Web approaches aim to solve the semantic interoperability by exploring recent studies in IoT systems. The paper taxonomized literature based on the interoperability requirement of the IoT system. This study identifies the opportunity resulting from the convergence of the Semantic Web and IoT data analytics.