IoTCrawler: Browsing the Internet of Things

Skarmeta, Antonio F.; Santa, José; Martı́nez, Juan Antonio; Parreira, Josiane Xavier; Barnaghi, Payam; Enshaeifar, Shirin; Beliatis, Michail J.; Presser, Mirko; Iggena, Thorben; Fischer, Marten; Tönjes, Ralf; Strohbach, Martin; Sforzin, Alessandro; Truong, Hien Thi Thu

doi:10.1109/giots.2018.8534528

Cited by 16 publications

(13 citation statements)

References 15 publications

(16 reference statements)

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“…The IoTCrawler framework provides a crawler and search engine for discovering sources of multi-domain IoT data streams. The crawler extracts metadata from the data sources and pushes the metadata through an Adaptation Layer that semantically annotates the metadata as instances of IotStream, and is stored in an RDF metadata repository [44]. Metadata captured here include identification for the discovered IotStream and the sosa:Sensor generating it, and the the qu:QuantityKind being measured and the qu:Unit used for measuring.…”

Section: Crawling and Search Engines For Iot Data Streamsmentioning

confidence: 99%

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services

Elsaleh

Enshaeifar

Rezvani

et al. 2020

Sensors

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With the proliferation of sensors and IoT technologies, stream data are increasingly stored and analysed, but rarely combined, due to the heterogeneity of sources and technologies. Semantics are increasingly used to share sensory data, but not so much for annotating stream data. Semantic models for stream annotation are scarce, as generally, semantics are heavy to process and not ideal for Internet of Things (IoT) environments, where the data are frequently updated. We present a light model to semantically annotate streams, IoT-Stream. It takes advantage of common knowledge sharing of the semantics, but keeping the inferences and queries simple. Furthermore, we present a system architecture to demonstrate the adoption the semantic model, and provide examples of instantiation of the system for different use cases. The system architecture is based on commonly used architectures in the field of IoT, such as web services, microservices and middleware. Our system approach includes the semantic annotations that take place in the pipeline of IoT services and sensory data analytics. It includes modules needed to annotate, consume, and query data annotated with IoT-Stream. In addition to this, we present tools that could be used in conjunction to the IoT-Stream model and facilitate the use of semantics in IoT.

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Section: Crawling and Search Engines For Iot Data Streamsmentioning

confidence: 99%

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services

Elsaleh

Enshaeifar

Rezvani

et al. 2020

Sensors

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“…The authors of [ 41 ] focus on the integration and interoperability across different platforms, through dynamic and reconfigurable solutions for discovery and integration of data and services and also considering a privacy-aware and secure solution for crawling, indexing, and searching in distributed IoT systems. The proposal presents solutions for the environment of Industry 4.0 among others.…”

Section: Related Workmentioning

confidence: 99%

FASTEN IIoT: An Open Real-Time Platform for Vertical, Horizontal and End-To-End Integration

Costa

Nassar

Gusmeroli

et al. 2020

Sensors

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The Industry 4.0 paradigm, since its initial conception in Germany in 2011, has extended its scope and adoption to a broader set of technologies. It is being considered as the most vital mechanism in the production systems lifecycle. It is the key element in the digital transformation of manufacturing industry all over the world. This scenario imposes a set of major unprecedented challenges which require to be overcome. In order to enable integration in horizontal, vertical, and end-to-end formats, one of the most critical aspects of this digital transformation process consists of effectively coupling digital integrated service/products business models with additive manufacturing processes. This integration is based upon advanced AI-based tools for decentralized decision-making and for secure and trusted data sharing in the global value. This paper presents the FASTEN IIoT Platform, which targets to provide a flexible, configurable, and open solution. The platform acts as an interface between the shop floor and the industry 4.0 advanced applications and solutions. Examples of these efforts comprise management, forecasting, optimization, and simulation, by harmonizing the heterogeneous characteristics of the data sources involved while meeting real-time requirements.

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“…Several research papers, derived by the work done in various EU funded projects, exist in the literature mainly focusing on crucial aspects of the IoT domain, such as the interoperability in different IoT environments [15] and for heterogeneous testbeds [16], privacy [17] in terms of authorisation and sensitive information handling, cloudification [18] and smart applications towards an open IoT ecosystem [19]. Nevertheless, there are numerous open issues for further discussion, with the most prominent one being the security in IoT.…”

Section: Emerging Advancementsmentioning

confidence: 99%

From Internet of Threats to Internet of Things: A Cyber Security Architecture for Smart Homes

Augusto-Gonzalez¹,

Collen

Evangelatos

et al. 2019

2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

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The H2020 European research project GHOST-SafeGuarding Home IoT Environments with Personalised Realtime Risk Control-aims to deploy a highly effective security framework for IoT smart home residents through a novel reference architecture for user-centric cyber security in smart homes providing an unobtrusive and user-comprehensible solution. The aforementioned security framework leads to a transparent cyber security environment by increasing the effectiveness of the existing cyber security services and enhancing system's self-defence through disruptive software-enabled network security solutions. In this paper, GHOST security framework for IoT-based smart homes is presented. It is aiming to address the security challenges posed by several types of attacks, such as network, device and software. The effective design of the overall multilayered architecture is analysed, with particular emphasis given to the integration aspects through dynamic and re-configurable solutions and the features provided by each one of the architectural layers. Additionally, real-life trials and the associated use cases are described showcasing the competences and potential of the proposed framework.

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IoTCrawler: Browsing the Internet of Things

Cited by 16 publications

References 15 publications

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams and Its Use with Data Analytics and Event Detection Services

FASTEN IIoT: An Open Real-Time Platform for Vertical, Horizontal and End-To-End Integration

From Internet of Threats to Internet of Things: A Cyber Security Architecture for Smart Homes

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