WOTS2E: A search engine for a Semantic Web of Things

The Internet of Things (IoT) is being applied for stovepipe solutions, since it presents a semantic description limited to a specific domain. IoT needs to be pushed towards a more open, interoperable and collaborative IoT. The first step has been the Web of Things (WoT). WoT evolves the IoT with a common stack based on web services. But, even when a homogeneous access is reached through web protocols, a common understanding is not yet acquired. For this purpose, the Semantic Web of Things (SWoT) is proposed for the integration of the semantic web on the WoT. This work analyses the SWoT, presenting its different levels to offer an IoT convergence. Specifically, we analyse the trends for capillary networks and for cellular networks with standards such as IPSO, ZigBee, OMA, and the oneM2M initiative. This work also analyses the impact of the semantic-annotations/metadata in the performance of the resources.

Internet of Things (IoT) is considered very widely spread in these days application and technology, which means a huge amount of data will need to be exchanged between devices and applications domains., For example, a weather application needs to communicate with a traffic application. Data between both applications need to be interpreted and to be interoperable in both applications. These applications are based on domain-specific, which means there is no domain interoperability. As a result, some developers and users took the web approach to find an easy solution that can be offered from the web itself, which leads to the Web of Things (WoT). But as with most recommendations in the web community, if data interoperability is needed as part of your implementation, you need to use Semantic Web as an approach that leads to a combined approach called Semantic Web of Things (SWoT). However, not every developer and user are having experience with Semantic Web standards such as RDF, Turtle, RDF/XML, SPARQL, OWL, etc. This paper proposes WOTJD for WoT using JavaScript Object Notation Linked Data (JSON-LD). WOTJD helps IoT users to overcome the main challenges of data interoperability in WOT by helping in (1) Design and integrate WOT applications, (2) IoT data parsing and annotation, and (3) Linking domains with each other (by using domain knowledge expertise), A case study of solving interoperability between smart cars and weather domain through a mobile application is presented, and performance evaluation has been performed, Experimental results show how fast is WOTJD framework against the sensor data size.

Intelligent, autonomous agents are still not available in the Semantic Web at large scale today. Also the fields of Semantic Web and Multi-Agent Systems are not working together very closely although they could profit much from each other. Existing approaches merely use the Web as a transport layer and are not properly aligned to the architectural style of the Web. The Internet of Things, which would be very useful for agents to act upon Things in the real world, on the other side is very fragmented and not easily inter-operable. The Web of Things has emerged as an approach to use the (Semantic) Web as an application layer for Things. It is still unclear however, how agents on the WoT should look like. We propose that the Semantic Web is a suitable integration layer, both for agents and Things. We investigate how a Multi-Agent System in the Semantic Web of Things can be build by utilizing simple reflex agents and the communication paradigm of stigmergy. We map Things and artifacts to Web resources that are managed by a Web server and provide affordances to agents through hypermedia.KeywordsMulti-Agent SystemsWeb of ThingsSimple reflex agentsStigmergyRestHypermedia

This paper reports on the early-stage development of an analytics framework to support the semantic integration of dynamic surveillance data across multiple scales to inform decision making for malaria eradication. We propose using the Semantic Web of Things (SWoT), a combination of Internet of Things (IoT) and semantic web technologies, to support the evolution and integration of dynamic malaria data sources and improve interoperability between different datasets generated through relevant IoT assets (e.g. computers, sensors, persons, and other smart objects and devices).

Falconer is a semantic Web search engine enhanced SIOC (Semantically-Interlinked Online Communities) application, which is designed to demonstrate the ability of accelerating the creation and reuse process of semantic Web data with easy-to-use user interfaces. In this process, semantic Web search engines feed existing semantic data into the SIOC framework, where new semantic data are composed by the community and indexed again by those search engines. Compared to existing social (semantic) Web applications, Falconer inherently conforms to SIOC specification. It provides semantic search engine based user registration suggestion, friends auto-discovery, and semantic annotation for forum post content. Another distinctive feature is that it enables users to subscribe any resource having a URI as the topic they are interested in. The relationships among users, topics, and posts are further visualized for analyzing the topic trends in the community. As all semantic data are formatted in RDF and RDFa, they can be queried with SPARQL query language.

The Semantic Web of Things (SWoT) merges the Internet of Things with knowledge representation and reasoning techniques borrowed from the Semantic Web, in order to improve resource management and discovery. This paper proposes a SWoT framework in Wireless Sensor Networks (WSNs) enabling cooperative discovery of sensors and actuators. A backward-compatible extension of the Constrained Application Protocol (CoAP) makes possible to use semantic matchmaking via non-standard reasoning to better characterize the resource discovery. The framework also integrates nimble data stream mining to detect and annotate high-level events through raw data gathered from the environment. A cooperative environmental monitoring case study in Hybrid Sensor and Vehicular Networks (HSVN) is presented together with experiments on a real testbed to assess feasibility and benefits of proposal.

Smart cities are becoming more and more popular. Currently, there is no unified and interoperable system which could be reused and redeployed in future smart cities. Having an interoperable: (1) system, (2) architecture, (3) workflow to process IoT data, (4) interoperable applications and services, and (5) secure access to data is becoming essential to reduce development cost in smart cities and ensure interoperability among vertical IoT applications (i.e., domain-specific). Firstly, we survey existing work integrating semantic web technologies to Internet of Things, also called 'Semantic Web of Things' and applying it to smart cities. Secondly, we share in this paper, our vision of Semantic Web of Things applied to smart cities and highlight main research challenges. Finally, the main contribution of this work is the semantic engine applied to IoT and smart cities. Moreover, the proposed semantic engine is applied to three use cases: Machine-to-Machine Measurement (M3) framework, FIESTA-IOT EU project and VITAL EU project.

Internet of Things (IoT) is the growing invention in the current development of different domains like industries, e-health, and education, etc. Semantic web of things (SWoT) is an extension of IoT that enhance the communication by behaving intelligently. SWoT comprises 7 layered architecture. The perception layer is an important layer for collecting data from devices and to communicate with its associated layer. The data loss at the perception layer is very common due to inadequate resources, unpredictable link, noise, collision, and unexpected damage. To address this problem, we propose a method based on Compressive Sensing which recovers and estimates sensory data from a low-rank structure. The contribution of this paper is three folds. Firstly, we determine the problem of data acquisition and data loss at semantic sensory nodes in SWoT. Secondly, we introduce a compressive sensing based framework for SWoT that recovers the data accurately using low-rank features. Thirdly, the data estimation method is utilized to reduce the volume of the data. Proposed Compressive Sensing based Data Recoverability and Estimation (CS-RE) method is evaluated and compared with the existing reconstruction methods. The simulation results on real sensory datasets depict that the proposed method significantly outperforms existing methods in terms of error ratio and data recoverability accuracy.

Googling for Health Information

The Generalized World Entities (GWEs) paradigm is a proposal for introducing a semantic/conceptual dimension into the standard IoT procedures and supporting then the creation of a real Semantic Web of Things (SWoT).It is based on a substantial extension of the kind of entities to be considered within a sensor-monitored environment, by modelling in a unified way both physical entities like objects, humans, robots, etc. and higher levels of abstraction structures like situations, events, and behaviors.The unifying element is provided by an extended conceptual representation of the world, ontology based, that is used for modelling the GWEs of both types.NKRL (Narrative Knowledge Representation Language), a high-level tool grounded on two separated but integrated ontologies, an ontology of concepts and an ontology of elementary events, is utilized in this context.

In this demonstration, we present our Semantic Web of Things~(SWoT) prototyping toolkit called SWoTSuite. It is a set of tools supporting an easy and fast prototyping of end-to-end SWoT applications. SWoTSuite facilitates - (i) automation of application development life-cycle, (ii) reducing the amount of time and effort required for developing WoT applications and (iii) an easy integration of semantic web technologies within WoT applications.

The Internet of Things is a vast and growing virtual universe that includes medical devices, automobiles, industrial systems and a variable number of consumer electronics devices. With some 100 billion devices expected to be connected to the Internet by 2025, providing interoperability among the things on the IoT is one of the most fundamental requirements to support tracking, object addressing and discovery as well as information representation, storage, and exchange. Applying semantic techniques to IoT can support Interoperability, effective data access, integration resource discovery reasoning and processing of data knowledge extraction. In this paper, we present an overview of semantic technologies such as Semantic Web of Things (SWoT), Ontologies, Resource Description Framework (RDF), RDF Schema, Web Ontology Language (OWL), SPARQL Protocol And RDF Query Language (SPARQL), Semantic annotation and reasoning widely deployed in IoT.

In our latest work, the problem of semantic interoperability for interconnected and semantically coordinated smart/control entities in a Semantic Web of Things has been explicated and a framework for Semantic Smart Gateways (SSGF) has been proposed. This paper aims to report on a proof-of-concept implementation of the core component of this framework which is the automatic alignment of smart/control entities’ semantic descriptions. More specific, the paper reports on a recent approach towards implementing a configurable, multilingual and synthesis-based ontology alignment tool that has been evaluated by the SEALS and OAEI initiatives.

The World Wide Web is a huge source of hyperlinked information contained in hypertext documents. Search engines use web crawlers to collect these web documents from web for storage and indexing. The prompt growth of the World Wide Web has posed incomparable challenges for the designers of search engines and web crawlers; that help users to retrieve web pages in a reasonable amount of time. In this paper, a review on need and working of a search engine, and role of a web crawler is being presented.

The development of an expert system based search tool needs a superficial structure to satisfy the requirements of current web scale. Search engines and the internet crawler are used to mine the required information from the web and surf the internet in an efficient fashion. Distributed crawler is one of the types of a web crawler, which is a dispersed computation method. In this paper, we design and implement the concept of Efficient Distributed Web Crawler using enhanced bandwidth and hefty algorithms. Mostly Web Crawler doesn’t have any distributed cluster performance system and any implemented algorithm. In this paper, a novel Hefty Algorithm and enhanced bandwidth algorithm are combined for a better-distributed crawling system. The hefty algorithm is implemented to provide strong and efficient surfing results while applying on the drug web search. We also concentrate on the efficiency of the proposed distributed web crawler by implementing Enhanced Bandwidth algorithm.