Toward a standardized common M2M service layer platform: Introduction to oneM2M

Chen

et al. 2017

IJGI

Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

Section: Resultsmentioning

confidence: 99%

A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

Chen

et al. 2017

IJGI

“…In order to support different applications for business purposes, a configurable information service platform is proposed in [20]. By combining ontology and RESTful service, the platform provides an information support base for data integration and intelligent interaction toward product lifecycle management.…”

Section: Communication Level Techniquesmentioning

confidence: 99%

IoT-Based Techniques for Online M2M-Interactive Itemized Data Registration and Offline Information Traceability in a Digital Manufacturing System

Meng

Gray

2017

IEEE Trans. Ind. Inf.

Abstract-The integration of Internet of Things (IoT) technologies in the industry benefits digital manufacturing applications by allowing ubiquitous interaction and collaborative automation between machines. Online data collection and data interaction are critical for real-time decision making and machine collaborations. However, due to the specificity of digital manufacturing applications, the technical gap between IoT techniques and practical machine operation could hinder the efficient data interactions, collaborations between machines, and the effectiveness as well as accuracy of itemised data collection. This investigation therefore identifies some major technical problems and challenges that current IoT-based digital manufacturing is facing, and proposes a method to bridge the technical gap for itemised product management. The highlights of this investigation are: (1) a data-oriented system architecture toward flexible data interaction between machines, (2) a customised Machine-toMachine (M2M) protocol for machine discovery, presence, and messaging, (3) flexible data structure and data presentation for interoperability, and (4) versatile information tracing approaches for product management. The proposed solutions have been implemented in PicknPack digital food manufacturing line, and achieved ubiquitous data interaction, online data collection, and versatile product information tracing methods have shown the feasibility and significance of the presented methods.

“…The primary applicable standardization activity from the European Telecommunications Standards Institute (ETSI) M2M Working Group has identified the need for a semantic resource descriptions in [40]. The successor, oneM2M (http://onem2m.org) [41], already has established the OneM2M Working Group 5 Management, Abstraction and Semantics (MAS). With the recent establishment of the World Wide Web Consortium (W3C) Web of Things (WoT) [42] Working Group, semantic vocabularies will be developed to describe data and interaction models.…”

Section: Semantic Models For Grids Clouds and Iotmentioning

confidence: 99%

Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures

Willner

Giatili

Grosso

et al. 2017

Data

A standardized descriptive ontology supports efficient querying and manipulation of data from heterogeneous sources across boundaries of distributed infrastructures, particularly in federated environments. In this article, we present the Open-Multinet (OMN) set of ontologies, which were designed specifically for this purpose as well as to support management of life-cycles of infrastructure resources. We present their initial application in Future Internet testbeds, their use for representing and requesting available resources, and our experimental performance evaluation of the ontologies in terms of querying and translation times. Our results highlight the value and applicability of Semantic Web technologies in managing resources of federated cyber-infrastructures.