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TopIntroduction
List of Notations and acronyms:
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IoT: Internet of Things
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GA: Genetic Algorithms
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GSMA: Groupe Speciale Mobile Association
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OWL: Ontology Wed Language
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DL: Description Logic
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DS: Direct Style
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RDF: Resource Description Framework
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RDFS: Resource Description Framework Schema
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RS: RDFS Style
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JVM: Java Virtual Machine
The IoT plays an important role in the new generation of information and communication technology. As more and more devices are connected to the Internet, the data generated by these IoT devices is also increasing. According to the report released by Groupe Speciale Mobile Association (GSMA) in 2019, the total number of global IoT connections reached 9.1 billion in 2018. The total number of global IoT connections is expected to reach 25.2 billion by 2025 (GSMA, 2019). Therefore, the effective use of data has become a research focus in recent years. More and more researchers are introducing Semantic Web technologies into IoT cloud servers to transform IoT data into knowledge. To solve the problem of semantic computing overload, in recent years, many researchers have tried to apply semantic web technology to IoT computing devices to share the computing tasks of servers. For example, semantic ontology is used in smart medical systems to improve the interoperability between medical devices and sensors (Rahmani, 2018); Semantic rules and sensor-based semantic ontology are used in an intelligent medical system to improve the robustness, efficiency, and comprehensibility of medical and health care system(Radhika, 2022) Semantic annotation and inference technologies are used in gateways (Al-Osta, 2019), and an event-driven model is designed to improve the efficiency of data processing. In the gateway system, the researchers realize the annotation and reasoning of sensor data streams and the real-time processing of events. Due to the limited resources of the IoT gateway, to reduce the weight of the annotated sensor data on networks, Urkude et al. (2021) established semantic data management by using semantic reasoner rules to reduce the number of triples from the semantic sensor data employing the unambiguous latent context information of a triple term. Kalatzis et al. (2019) propose a design principle for the specification of interoperability enabling solutions and verify the design principles in the experiment. Semantic annotation technology and the ontology are used in the edge devices of IoT to realize early warning of fire; Ali et al. (2017) design a lightweight ontology, which describes smartphones and sensors from different aspects, including platform, deployment, measurement functions, and attributes, data fusion and context modeling to realize the design of a smartphone sensor body for context-aware applications; the semantic inference technology is used in edge devices and cloud devices to realize stand-alone reasoning, distributed reasoning, mobile reasoning, and their synthetic reasoning (Ai, 2017), etc. There are many advantages to using Semantic Web technologies on IoT devices: 1) Reduce semantic computing tasks in the Cloud; 2) Reduce energy consumption in data transmission; 3) Improve the real-time performance of data processing; 4) Improve data security; 5) Enhance interoperability between IoT devices; 6) Develop more IoT solutions based on Semantic Web technologies, such as local event detection and early warning, fault handling, etc.