General ontology for internet of things (goiot) to achieve semantic interoperability using sensor, observation, sample and actuator (sosa) approach

Internet of Things (IoT) devices are increasing day by day, thus a common vocabulary is required to make sure these devices from a different manufacturer can communicate with each other by themselves known as semantic interoperability. Ontology is required to solve the semantic interoperability problem of the IoT. Ontology provides a base to represent objects in a specific domain. Classes, Instances, and Relationships are the components required to built ontology. Problems with existing IoT ontologies are as follows: (i) Incomplete IoT Concepts; (ii) Most of the Existing IoT ontologies did not includes all critical elements of IoT; (iii) The existing ontologies are not built on the latest ontology language standard recommended by W3C which is Web Ontology Language (OWL); (iv) The IoT ontologies in literature did not follow any Evaluation Measurement such as Reasoner. The objective of this research is to study the existing literature about IoT and Ontology and their relationship. Then to develop and evaluate GoIoT by using Protégé and pallet reasoner respectively. The methodology is divided into three portions which are Analysis, Development and Implementation, and Evaluation and Measurements. In the analysis part, basic concepts of IoT and Ontology are discussed. In Development and Implementation, SOSA is adopted to create a new ontology, namely GoIoT. It talks about the existing reused IoT concept and how new IoT concepts are further integrated. Further, it discusses which language and tools are used to build this ontology. The newly constructed GoIoT is evaluated via semantic reasoner and experts. The reasoner results showed zero error in GoIoT ontology which simply means that no issue is found among ontology components. Five (5) experts have also evaluated ontology in terms of nine (9) evaluation criteria. The mean value of five (5) expert combine is 83.059 % and this value shows that the Ontology developed can be accepted as Ontology that represent General Ontology for IOT

Applications of ontology in the Internet of Things: a systematic analysis

Ontology has been increasingly implemented to facilitate the Internet of Things (IoT) activities, such as tracking and information discovery, storage, information exchange, and object addressing. However, a complete understanding of using ontology in the IoT mechanism remains lacking. The main goal of this research is to recognize the use of ontology in the IoT process and investigate the services of ontology in IoT activities. A systematic literature review (SLR) is conducted using predefined protocols to analyze the literature about the usage of ontologies in IoT. The following conclusions are obtained from the SLR. (1) Primary studies (i.e., selected 115 articles) have addressed the need to use ontologies in IoT for industries and the academe, especially to minimize interoperability and integration of IoT devices. (2) About 31.30% of extant literature discussed ontology development concerning the IoT interoperability issue, while IoT privacy and integration issues are partially discussed in the literature. (3) IoT styles of modeling ontologies are diverse, whereas 35.65% of total studies adopted the OWL style. (4) The 32 articles (i.e., 27.83% of the total studies) reused IoT ontologies to handle diverse IoT methodologies. (5) A total of 45 IoT ontologies are well acknowledged, but the IoT community has widely utilized none. An in-depth analysis of different IoT ontologies suggests that the existing ontologies are beneficial in designing new IoT ontology or achieving three main requirements of the IoT field: interoperability, integration, and privacy. This SLR is finalized by identifying numerous validity threats and future directions

A survey on MAC-based physical layer security over wireless sensor network

Physical layer security for wireless sensor networks (WSNs) is a laborious and highly critical issue in the world. Wireless sensor networks have great importance in civil and military fields or applications. Security of data/information through wireless medium remains a challenge. The data that we transmit wirelessly has increased the speed of transmission rate. In physical layer security, the data transfer between source and destination is not confidential, and thus the user has privacy issues, which is why improving the security of wireless sensor networks is a prime concern. The loss of physical security causes a great threat to a network. We have various techniques to resolve these issues, such as interference, noise, fading in the communications, etc. In this paper we have surveyed the different parameters of a security design model to highlight the vulnerabilities. Further we have discussed the various attacks on different layers of the TCP/IP model along with their mitigation techniques. We also elaborated on the applications of WSNs in healthcare, military information integration, oil and gas. Finally, we have proposed a solution to enhance the security of WSNs by adopting the alpha method and handshake mechanism with encryption and decryption

Applications of ontology in the internet of things: A systematic analysis

Ontology has been increasingly implemented to facilitate the Internet of Things (IoT) activities, such as tracking and information discovery, storage, information exchange, and object addressing. However, a complete understanding of using ontology in the IoT mechanism remains lacking. The main goal of this research is to recognize the use of ontology in the IoT process and investigate the services of ontology in IoT activities. A systematic literature review (SLR) is conducted using predefined protocols to analyze the literature about the usage of ontologies in IoT. The following conclusions are obtained from the SLR. (1) Primary studies (i.e., selected 115 articles) have addressed the need to use ontologies in IoT for industries and the academe, especially to minimize interoperability and integration of IoT devices. (2) About 31.30% of extant literature discussed ontology development concerning the IoT interoperability issue, while IoT privacy and integration issues are partially discussed in the literature. (3) IoT styles of modeling ontologies are diverse, whereas 35.65% of total studies adopted the OWL style. (4) The 32 articles (i.e., 27.83% of the total studies) reused IoT ontologies to handle diverse IoT methodologies. (5) A total of 45 IoT ontologies are well acknowledged, but the IoT community has widely utilized none. An in-depth analysis of different IoT ontologies suggests that the existing ontologies are beneficial in designing new IoT ontology or achieving three main requirements of the IoT field: interoperability, integration, and privacy. This SLR is finalized by identifying numerous validity threats and future directions

A Novel Approach to Explore Edhi Foundation Knowledge for Ontology Construction

The worth of the Edhi Foundation (EF) system depends on how well its structural knowledge can be extracted by EF users and staff to perform daily activities. Ontology has emerged as a semantic tool to represent the knowledge of a particular domain and thus is a good choice for the semantic organization of EF data. However, building an ontology that suits the needs of EF users is a challenging task. This study presents a novel approach that uses the UML class diagram (UCD) to construct an ontology for the EF system. We propose UCD-to-ontology transformation rules, that is, the ontology model that is used for eliciting OWL ontology. We test our approach for the successful interpretation of UCD features to OWL ontology elements and find that the system performs well with an average precision of 97.80%

User interest driven semantic query expansion for effective web search

Retrieving user-relevant content from a large volume of data available on the Web via an input query is a difficult task. A user query may not be able to specify user information needs due to the ambiguous and limited number of query terms. The semantic query expansion (QE) strategy offers a solution to this problem by expanding the query with additional terms, which are semantically similar to the original query. However, this strategy does not consider individual user interest in the generation of expansion terms. In this article, semantic QE is improved by combining the notion of ontology knowledge and user interest. The proposed semantic QE technique involves a computing domain of the input query via ontology, generates expansion terms from the user browsing history, and finally selects expansion terms that represent user preferences on the basis of the semantic similarity between expansion terms and query and user feedback. The experimental evaluation indicates that expanded queries produced by the proposed technique retrieve more personalized contents over Web search than initial user queries. The obtained results achieve 86.4% average precision, which proves a positive impact of incorporating user preferences in semantic QE

Applications of Ontology in the Internet of Things: A Systematic Analysis

Ontology has been increasingly implemented to facilitate the Internet of Things (IoT) activities, such as tracking and information discovery, storage, information exchange, and object addressing. However, a complete understanding of using ontology in the IoT mechanism remains lacking. The main goal of this research is to recognize the use of ontology in the IoT process and investigate the services of ontology in IoT activities. A systematic literature review (SLR) is conducted using predefined protocols to analyze the literature about the usage of ontologies in IoT. The following conclusions are obtained from the SLR. (1) Primary studies (i.e., selected 115 articles) have addressed the need to use ontologies in IoT for industries and the academe, especially to minimize interoperability and integration of IoT devices. (2) About 31.30% of extant literature discussed ontology development concerning the IoT interoperability issue, while IoT privacy and integration issues are partially discussed in the literature. (3) IoT styles of modeling ontologies are diverse, whereas 35.65% of total studies adopted the OWL style. (4) The 32 articles (i.e., 27.83% of the total studies) reused IoT ontologies to handle diverse IoT methodologies. (5) A total of 45 IoT ontologies are well acknowledged, but the IoT community has widely utilized none. An in-depth analysis of different IoT ontologies suggests that the existing ontologies are beneficial in designing new IoT ontology or achieving three main requirements of the IoT field: interoperability, integration, and privacy. This SLR is finalized by identifying numerous validity threats and future directions