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 security and privacy issues in IoV

As an up-and-coming branch of the internet of things, internet of vehicles (IoV) is imagined to fill in as a fundamental information detecting and processing platform for astute transportation frameworks. Today, vehicles are progressively being associated with the internet of things which empower them to give pervasive access to data to drivers and travelers while moving. Be that as it may, as the quantity of associated vehicles continues expanding, new prerequisites, (for example, consistent, secure, vigorous, versatile data trade among vehicles, people, and side of the road frameworks) of vehicular systems are developing. Right now, the unique idea of vehicular specially appointed systems is being changed into another idea called the internet of vehicles (IoV). We talk about the issues faced in implementing a secure IoV architecture. We examine the various challenges in implementing security and privacy in IoV by reviewing past papers along with pointing out research gaps and possible future work and putting forth our on inferences relating to each paper

Influence Analysis towards Big Social Data

Large scale social data from online social networks, instant messaging applications, and wearable devices have seen an exponential growth in a number of users and activities recently. The rapid proliferation of social data provides rich information and infinite possibilities for us to understand and analyze the complex inherent mechanism which governs the evolution of the new technology age. Influence, as a natural product of information diffusion (or propagation), which represents the change in an individual’s thoughts, attitudes, and behaviors resulting from interaction with others, is one of the fundamental processes in social worlds. Therefore, influence analysis occupies a very prominent place in social related data analysis, theory, model, and algorithms. In this dissertation, we study the influence analysis under the scenario of big social data. Firstly, we investigate the uncertainty of influence relationship among the social network. A novel sampling scheme is proposed which enables the development of an efficient algorithm to measure uncertainty. Considering the practicality of neighborhood relationship in real social data, a framework is introduced to transform the uncertain networks into deterministic weight networks where the weight on edges can be measured as Jaccard-like index. Secondly, focusing on the dynamic of social data, a practical framework is proposed by only probing partial communities to explore the real changes of a social network data. Our probing framework minimizes the possible difference between the observed topology and the actual network through several representative communities. We also propose an algorithm that takes full advantage of our divide-and-conquer strategy which reduces the computational overhead. Thirdly, if let the number of users who are influenced be the depth of propagation and the area covered by influenced users be the breadth, most of the research results are only focused on the influence depth instead of the influence breadth. Timeliness, acceptance ratio, and breadth are three important factors that significantly affect the result of influence maximization in reality, but they are neglected by researchers in most of time. To fill the gap, a novel algorithm that incorporates time delay for timeliness, opportunistic selection for acceptance ratio, and broad diffusion for influence breadth has been investigated. In our model, the breadth of influence is measured by the number of covered communities, and the tradeoff between depth and breadth of influence could be balanced by a specific parameter. Furthermore, the problem of privacy preserved influence maximization in both physical location network and online social network was addressed. We merge both the sensed location information collected from cyber-physical world and relationship information gathered from online social network into a unified framework with a comprehensive model. Then we propose the resolution for influence maximization problem with an efficient algorithm. At the same time, a privacy-preserving mechanism are proposed to protect the cyber physical location and link information from the application aspect. Last but not least, to address the challenge of large-scale data, we take the lead in designing an efficient influence maximization framework based on two new models which incorporate the dynamism of networks with consideration of time constraint during the influence spreading process in practice. All proposed problems and models of influence analysis have been empirically studied and verified by different, large-scale, real-world social data in this dissertation

Parameter selection and performance comparison of particle swarm optimization in sensor networks localization

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors\u27 memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm

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

IoT and blockchain paradigms for EV charging system

In this research work, we apply the Internet of Things (IoT) paradigm with a decentralized blockchain approach to handle the electric vehicle (EV) charging process in shared spaces, such as condominiums. A mobile app handles the user authentication mechanism to initiate the EV charging process, where a set of sensors are used for measuring energy consumption, and based on a microcontroller, establish data communication with the mobile app. A blockchain handles financial transitions, and this approach can be replicated to other EV charging scenarios, such as public charging systems in a city, where the mobile device provides an authentication mechanism. A user interface was developed to visualize transactions, gather users’ preferences, and handle power charging limitations due to the usage of a shared infrastructure. The developed approach was tested in a shared space with three EVs using a charging infrastructure for a period of 3.5 months.info:eu-repo/semantics/publishedVersio

Experimental Characterization of RGB LED Transceiver in Low-Complexity LED-to-LED Link

This paper proposes a low-complexity and energy-efficient light emitting diode (LED)-to-LED communication system for Internet of Things (IoT) devices with data rates up to 200 kbps over an error-free transmission distance up to 7 cm. The system is based on off-the-shelf red-green-blue (RGB) LEDs, of which the red sub-LED is employed as photodetector in photovoltaic mode while the green sub-LED is the transmitter. The LED photodetector is characterized in the terms of its noise characteristics and its response to the light intensity. The system performance is then analysed in terms of bandwidth, bit error rate (BER) and the signal to noise ratio (SNR). A matched filter is proposed, which optimises the performance and increases the error-free distance

Business impact, risks and controls associated with the internet of things

Thesis (MCom)--Stellenbosch University, 2017.ENGLISH SUMMARY : Modern businesses need to keep up with the ever-evolving state of technology to determine how a change in technology will affect their operations. Adopting Internet of Things to operations will assist businesses in achieving the goals set by management and, through data integration, add additional value to information. With the Internet of Things forming a global communication network, data is gathered in real time by sensor technologies embedded in uniquely identifiable virtual and physical objects. This data gathered are integrated and analysed to extract knowledge, in order to provide services like inventory management, customised customer service and elearning as well as accurate patient records. This integrated information will generate value for businesses by, inter alia, improving the quality of information and business operations. Business may be quick to adopt the Internet of Things into their operations because of the promised benefits, without fully understanding its enabling technologies. It is important that businesses acquire knowledge of the impact that these technologies will have on their operations as well as the risks associated with the use of these technologies before they deploy the Internet of Things in their business environment. The purpose of this study was to identify the business impact, risks and controls associated with the Internet of Things and its enabling technologies. Through the understanding of the enabling technologies of Internet of Things, the possible uses and impact on business operations can be identified. With the help of a control framework, the understanding gained on the technologies were used to identify the risks associated with them. The study concludes by formulating internal controls to address the identified risks. It was found that the core technologies (smart objects, wireless networks and semantic technologies) adopt humanlike characteristics and convert most manual business operations into autonomous operations, leading to increased business productivity, market differentiation, cost reduction and higher-quality information. The identified risks centred on data integrity, privacy and confidentiality, authenticity, unauthorised access, network availability and semantic technology vulnerabilities. A multi-layered approach of technical and non-technical internal controls were formulated to mitigate the identified risks to an acceptable level. The findings will assist information technology specialists and executive management of industries to identify the risks associated with the implementation of Internet of Things in operations, mitigate the risks to an acceptable level through controls as well as assist them to determine the possible uses and its impact on operations.AFRIKAANSE OPSOMMING : Moderne ondernemings moet tred hou met die voortdurende ontwikkeling van tegnologie om te bepaal hoe ʼn verandering in tegnologie hulle bedrywighede sal beïnvloed. Inkorporering van Internet van Dinge in bedrywighede sal besighede help om die doelwitte wat deur bestuur gestel is te bereik en, deur data integrasie, additionele waarde te voeg tot inligting. Met Internet van Dinge wat ʼn globale kommunikasienetwerk vorm, word data in regte tyd versamel deur ensortegnologieë wat ingebed is in unieke identifiseerbare virtuele en fisiese voorwerpe. Hierdie versamelde data word geïntegreer en ontleed om kennis te onttrek om sodoende dienste te lewer, soos voorraadbestuur, pasgemaakte kliëntediens en e-leer sowel as akkurate pasiënt rekords. Hierdie geïntegreerde inligting sal waarde genereer vir ondernemings deur, inter alia, die gehalte van inligting en sakebedrywighede te verbeter. Ondernemings mag vinnig Internet van Dinge in hulle bedrywighede inkorporeer as gevolg van die beloofde voordele, sonder om die instaatstellende tegnologieë ten volle te verstaan. Dit is belangrik dat ondernemings kennis inwin oor die impak wat hierdie tegnologieë sal hê op hulle bedrywighede sowel as die risiko’s wat geassosieer word met die gebruik van hierdie tegnologieë voordat Internet van Dinge in hulle sakeomgewings ontplooi word. Die doel van hierdie studie was om die besigheidsimpak, risko’s en kontroles wat geassosieer word met Internet van Dinge en die instaatstellende tegnologieë te identifiseer. Deur die instaatstellende tegnologieë van Internet van Dinge te verstaan, kan die moontlike gebruike en impak daarvan op sakebedrywighede geïdentifiseer word. Met behulp van ʼn kontroleraamwerk, is die begrip van die tegnologieë gebruik om die risiko’s wat geassosieer word met hulle te identifiseer. Die studie sluit af met die formulering van interne kontroles om die geïdentifiseerde risko’s aan te spreek. Daar is gevind dat die kerrntegnologiekomponente (slim voorwerpe, draadlose netwerke en semantiese tegnologieë) menslike eienskappe aanneem en die meeste handsakebedrywighede omskakel na outonome bedrywighede, wat lei tot verhoogte sakeproduktiwiteit, markdifferensiasie, kostebesparing en hoërgehalte-inligting. Die geïdentifiseerde risiko’s is toegespits op data integriteit, -privaatheid en - vertroulikheid, egtheid, ongemagtigde toegang, netwerkbeskikbaarheid en semantiese tegnologiekwesbaarhede. ʼn Multilaagbenadering van tegniese en nie-tegniese interne kontroles is geformuleer, om sodoende die geïdentifiseerde risiko’s tot ʼn aanvaarbare vlak te versag. Die bevindinge sal inligtingstegnologie-spesialiste en uitvoerende bestuur van industrieë help om die risiko’s verbonde aan implementering van Internet van Dinge te identifiseer, risko’s te versag tot ʼn aanvaarbare vlak met kontroles sowel as hulle te help om moontlike gebruike en hulle impak op bedrywighede vas te stel