## 2 Related Work  
Several studies have focused on the management of WSNs, which are important components of complex environmental monitoring systems. A large number of techniques have been applied to manage specific WSNs. For example, an energy-efficient method was proposed in [3] for an ant-based routing algorithm in Wireless Sensor Networks. In [4], simple and feasible synchronous node sleeping and waking mechanisms for small-scale WSNs were proposed. Sensor nodes were divided into forwarding nodes and listening nodes. A beacon frame containing a sleep command sent from the coordinator can be sent to the listening nodes via the forwarding nodes. In [5], an Energy-Efficient Adaptive Geosource Multicast Routing (EAGER) was proposed for WSNs. It addresses the energy and scalability issues of previous location-based stateless multicast protocols in WSN. A complete hierarchical key management scheme that uses symmetric cryptographic algorithms and low-cost operations for heterogeneous cluster-based WSN was proposed in [6]. The scheme consists of four types of keys for each sensor node: an individual key, a cluster key, a master key, and pairwise keys. However, it is very complicated and time consuming to incorporate and manage different sensor networks. Additionally, we must use different techniques to manage different networks. Most sensor network management models use their own scenarios and management languages. These languages may be quite different, because each network has its own language. Therefore, we require a method that can be applied to a pervasive computing environment. Semantic web technologies have recently been proposed to enable interoperability of sensors and sensing systems. An ontology can be combined with semantic web technology standards to form a semantic sensor web. An ontology is a conceptual model of abstract concepts related to some phenomena in the objective world. The description represented by an ontology is independent of specific environmental conditions. Ontology concepts and their constraints are clearly defined. An ontology is readable and can be processed by a computer. It is based on groups rather than individuals, expresses common knowledge, and reflects a concept set of related areas. We can combine a WSN environment and an ontology to facilitate knowledge sharing, conceptualize the WSN's knowledge, and derive a commonly recognized language. By constructing a WSN ontology, we can integrate different WSN management technologies and apply them to pervasive environments. The Sensor Web Enablement (SWE) [7] initiative of the Open Geospatial Consortium (OGC) defined data encodings and web services for storing and accessing sensor-related data. These standards provide syntactic interoperability. Examples include SensorML and O&M [8; 9; 10]. Some scholars have proposed effective Semantic Sensor Network (SSN) ontologies based on this research. The W3C Semantic Sensor Network Incubator Group (SSN-XG) [1; 11] produced OWL (Web Ontology Language) to describe sensors and observations, _i.e._, a SSN ontology. This SSN ontology can describe sensors in terms of their capabilities, measurement processes, observations, and deployments [1; 11]. The SSN ontology was extended to WSN by [PERSON] _et al._, and was used to optimize the life of a network [2]. It deduces the state of the node based on its energy level. However, the authors did not provide details of the reasoning methods. To effectively manage a WSN, we should consider the objectives and environmental parameters using certain logical rules. Although these ontologies are compatible, specific applications require supplemental rule descriptions and reasoning methods. Semantic Web Rule Language (SWRL) [12] is an expressive Web Ontology Language (OWL)-based rule language [13, 14]. SWRL allows users to write rules that can be expressed in terms of OWL concepts to provide more powerful deductive reasoning capabilities than OWL alone.