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Top1. Introduction
Nowadays, infrastructure systems as smart cities, smart health, smart homes, smart water networks, smart grid, intelligent transportation, became richer and more diverse than we ever thought possible.
The common vision of such systems is usually associated with one single concept, the Internet of Things (IoT) (Atzori, 2010). IoT is a network of physical objects or “things” that contain embedded technology in order to enable these objects to collect data.
IoT allows objects to be sensed and controlled remotely across network infrastructure, creating opportunities for more direct integration between the physical world and computer systems. In other words, the result of the IoT is automation in all fields (Santhi, 2016).
The idea of IoT was developed in parallel to Wireless Sensor Networks (WSNs), therefore, the main technologies that enable IoT are WSNs (Yinbiao, 2014), (Lazarescu, 2017). A WSN is a wireless network consisting of spatially distributed autonomous devices that uses sensors to monitor physical or environmental conditions. The main components of the WSN are: Sensor, Sensor Node, and Sensor Network (Sohraby, 2007).
Applications of the WSNs include monitoring a wide variety of ambient conditions like temperature, humidity, vehicular movement, lightning condition, pressure, soil makeup, noise levels, in military for target field imaging, earth monitoring, disaster management, fire alarm sensors, sensors planted underground for precision agriculture, intrusion detection and criminal hunting (Bakaraniya, 2012), (Kaur, 2016), (Akyildiz, 2010).
A WSN is usually deployed with static sensor nodes to perform monitoring missions in the region of interest, but WSN can also be deployed with mobile sensor nodes to perform monitoring in different locations. WSNs may be homogeneous or heterogeneous. Homogeneous sensors send only one type of information (e.g. the water temperature), while heterogeneous sensors send more than one type of information (e.g. temperature and dissolved oxygen). All these sensors send observational data called sensor data stream to a server. The data describing the WSN itself, its devices and the corresponding site allocation data is called sensor metadata. Sensor data is made available to the web through the Sensor Web. By incorporating technologies of the Semantic Web, Semantic Sensor Web is created. In this way, sensor data stream can be annotated with semantics (for example, with domain knowledge) by providing machine-interpretable descriptions on what the data represents, where it originates from, how it can be related to its surroundings, who is providing it, and what are the quality, technical, and non-technical attributes (Barnaghi, 2012). The real-time integration of sensor data as dynamic data with semantics is defined as real-time semantic annotation, while sensor data that are stored in repository as static data, and then integrated with semantics, is defined as non-real-time semantic annotation. Organizations like Open Geospatial Consortium (OGC)1 and World Wide Web Consortium (W3C)2 have proposed some standards for sensor data, which are described in the next sections.
In this study, a systematic literature review related to the topic of integration of semantics into sensor data for the IoT is presented. The conducted review is focused on the annotation techniques of semantics, main solutions of adding semantic annotations to the sensor data, standards that enable all types of sensor via the Web, existing models of stream data for annotation, and the IoT trend domains that use semantics.
The remainder of this review study is organized as follows. Section 2 provides the problem definition. In section 3, the research methodology is described and research question are defined. The answers to the defined research questions associated with relevant literature, are presented in section 4, while section 5 presents summary of the systematic review. Section 6 is focused around open issues and existing challenges. Finally, conclusions are given in section 7.