IoT-Lite: A Lightweight Semantic Model for the Internet of Things

Bermúdez-Edo, María; Elsaleh, Tarek; Barnaghi, Payam; Taylor, Kerry

doi:10.1109/uic-atc-scalcom-cbdcom-iop-smartworld.2016.0035

Cited by 152 publications

(77 citation statements)

References 10 publications

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“…In the same context, authors in [8] tried to examine how the IoT methods can be demonstrated utilizing web ontologies that enable them to straightforwardly convey the strategy usage. On the other hand, authors in [9] propose an IoT-Lite ontology, by launching of the semantic sensor organize (SSN) ontology to depict key IoT ideas permitting interoperability and revelation of tactile information in heterogeneous IoT stages by a lightweight semantics. In addition to that, authors In [10] established a more concluded method for collecting sensor information by using SASML (Sensors Annotation and Semantic Mapping Language) to annotate the corresponding relationship between the SSN ontology and its sensor data in the mapping file using the RDF Mapping Data Sensor (SDRM) algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Semantic Architecture for Modelling and Reasoning IoT Data Resources based on SPARK

Salama¹,

Masoud²,

Al-Feel³

2020

IJACSA

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Electronic Internet-of-Things is one of the foremost valuable techniques today. Through it, everything everywhere the globe became connected and intelligent, eliminating the wants to human-to-human interaction to perform tasks. This by changing all of those objects like humans, machines, devices and something around to be simply an internet Protocol (IP) to be expressed within the network environment through completely different sensors and actuators devices which might facilitate the interaction between all of them. These different types of sensors generate a large volume of various information and data. This type of sensor information created it generally useless because of the heterogeneity and lack of interoperability of it that represents it in unstructured form. So, investing from semantic internet techniques might handle these main challenges that face the IoT applications. Hence, the main contribution behind this research aims to boost the performance and quality of sensors information retrieved from IoT resources and applications by using semantic web technologies to resolve the matter of heterogeneity and interoperability and then convert the unstructured sensor data to structured form to realize the next level of investing of sensors employed in IoT applications. Also, the aim through this research to improve the performance of the tremendous amount of information that represents the demonstrated IoT information utilizing Big Data techniques such as Spark and its query language that's named SPARK-SQL as a streaming inquiry language for a colossal amount of information. The proposed architecture demonstrated that utilizing the semantic techniques to model the streaming sensors data improve the value of information and permit us to gather unused information. Moreover, the improvement by using SPARK leads to extend the performance of utilizing this sensor information in terms of the time retrieval of running queries, particularly when running the same queries utilizing the conventional SPARQL inquiry language.

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Section: Literature Reviewmentioning

confidence: 99%

Semantic Architecture for Modelling and Reasoning IoT Data Resources based on SPARK

Salama¹,

Masoud²,

Al-Feel³

2020

IJACSA

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“…A few other research projects on the IoT semantic framework are: (i) the Open-IoT project relies on a blueprint cloud-based IoT architecture, which leverages the W3C SSN ontology for modeling sensors [13]. (ii) The IoT-Lite ontology [14] is an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability, discovery of sensory data in heterogeneous IoT platforms by lightweight semantics. This project was deployed to address the concern that semantic techniques increase the complexity and the processing time.…”

Section: Related Workmentioning

confidence: 99%

Internet of Things Infrastructure for Security and Safety in Public Places

et al. 2019

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We present the technologies and the theoretical background of an intelligent interconnected infrastructure for public security and safety. The innovation of the framework lies in the intelligent combination of devices and human information towards human and situational awareness, so as to provide a protection and security environment for citizens. The framework is currently being used to support visitors in public spaces and events, by creating the appropriate infrastructure to address a set of urgent situations, such as health-related problems and missing children in overcrowded environments, supporting smart links between humans and entities on the basis of goals, and adapting device operation to comply with human objectives, profiles, and privacy. State-of-the-art technologies in the domain of IoT data collection and analytics are combined with localization techniques, ontologies, reasoning mechanisms, and data aggregation in order to acquire a better understanding of the ongoing situation and inform the necessary people and devices to act accordingly. Finally, we present the first results of people localization and the platforms’ ontology and representation framework.

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“…In this way, after applying the action, the algorithm calls shop2mt with these possibilities (lines [18][19][20]. If w is a method, we perform the task decomposition (lines [23][24][25][26][27][28][29][30][31][32][33][34][35][36]. If more than one decomposition is applied, a new thread is generated for each of the possibilities (lines 27-32).…”

Section: The Automatic Service Composermentioning

confidence: 99%

Interoperability in semantic Web of Things: Design issues and solutions

Silva

Pérez-Alcázar

Kofuji

2019

Int J Communication

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Summary The significant improvement in processing power, communication, energy consumption, and the size of computational devices has led to the emergence of the Internet of Things (IoT). IoT projects raise many challenges, such as the interoperability between IoT applications because of the high number of sensors, actuators, services, protocols, and data associated with these systems. Semantics solves this problem by using annotations that define the role of each IoT element and reduces the ambiguity of information exchanged between the devices. This work presents SWoTPAD, a semantic framework that helps in the development of IoT projects. The framework is designer oriented and provides a semantic language that is more user‐friendly than OWL‐S and WSML and allows the IoT designer to specify devices, services, environment, and requests. Following this, it makes use of these specifications and maps them for RESTful services. Additionally, it generates an automatic service composition engine that is able to combine services needed to handle complex user requests. We validated this approach with two case studies. The former concerns a residential security system and the latter, the cloud application deployment. The average time required for service discovery and automatic service composition corresponds to 72.9% of the service execution time in the case study 1 and 64.4% in the case study 2.

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IoT-Lite: A Lightweight Semantic Model for the Internet of Things

Cited by 152 publications

References 10 publications

Semantic Architecture for Modelling and Reasoning IoT Data Resources based on SPARK

Semantic Architecture for Modelling and Reasoning IoT Data Resources based on SPARK

Internet of Things Infrastructure for Security and Safety in Public Places

Interoperability in semantic Web of Things: Design issues and solutions

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