A Review of Semantic Sensor Technologies in Internet of Things Architectures

Honti, Gergely Marcell; Abonyi, János

doi:10.1155/2019/6473160

Cited by 33 publications

(27 citation statements)

References 168 publications

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“…The semantic representation (Honti and Abonyi, 2019 ) allows the modeling and administration of semantic knowledge from different IoRT devices and platforms.…”

Section: Iort Platformsmentioning

confidence: 99%

“…The semantic representation(Honti and Abonyi, 2019) allows the modeling and administration of semantic knowledge from different IoRT devices and platforms.• The security and policy framework implements the federated identity management for authentication, authorization policies, the access control mechanisms, and facilitates the exchange and coordination among several IoRT platforms. • The networking framework enables connectivity within and among IoRT and IoT/IIoT platforms, ensuring the instruments for self-management (i.e., monitoring, configuration, healing, optimization, and protection) through cognitive algorithms.…”

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confidence: 99%

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Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and "things" have evolved significantly. "Things" now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of "intelligent things" (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.

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“…The semantic representation (Honti and Abonyi, 2019 ) allows the modeling and administration of semantic knowledge from different IoRT devices and platforms.…”

Section: Iort Platformsmentioning

confidence: 99%

mentioning

confidence: 99%

Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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“…Li et al [49] review standardized Web of Things ontologies and identify their coverage of different levels of abstraction. Honti and Abonyi [50] present sensor ontologies according to the semantic needs of the layers of IoT solutions based on an IoT standard. Bajaj et al [51] survey existing IoT ontologies based on the fundamental ontological concepts required for an IoT-based application.…”

Section: Contribution Of This Reviewmentioning

confidence: 99%

“…Gyrard et al identify more than 200 ontologies relevant to IoT applications [147], but it is unclear how many of these can be directly related to building applications. For interested readers, other reviews provide more information about these schemas [48][49][50][51][52]. In addition to the smart home schemas described in Section 3.2.2, Connected Home over IP (CHIP) is a recent project supported by several IoT/smart home vendors and coordinated by the Zigbee Alliance.…”

Section: The Landscape Of Metadata Schemas For Building Energy Applicmentioning

confidence: 99%

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

et al. 2021

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Digital and intelligent buildings are critical to realizing efficient building energy operations and a smart grid. With the increasing digitalization of processes throughout the life cycle of buildings, data exchanged between stakeholders and between building systems have grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent and hinders the development of energy-oriented applications that can be reused across buildings, limiting the scalability of innovative solutions. Addressing this challenge, our review paper systematically reviews metadata schemas and ontologies that are at the foundation of semantic interoperability necessary to move toward improved building energy operations. The review finds 40 schemas that span different phases of the building life cycle, most of which cover commercial building operations and, in particular, control and monitoring systems. The paper’s deeper review and analysis of five popular schemas identify several gaps in their ability to fully facilitate the work of a building modeler attempting to support three use cases: energy audits, automated fault detection and diagnosis, and optimal control. Our findings demonstrate that building modelers focused on energy use cases will find it difficult, labor intensive, and costly to create, sustain, and use semantic models with existing ontologies. This underscores the significant work still to be done to enable interoperable, usable, and maintainable building models. We make three recommendations for future work by the building modeling and energy communities: a centralized repository with a search engine for relevant schemas, the development of more use cases, and better harmonization and standardization of schemas in collaboration with industry to facilitate their adoption by stakeholders addressing varied energy-focused use cases.

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“…Due to the aforementioned reasons, it is necessary to use methods that can save this knowledge and reuse it to solve various problems. Semantics plays a significant role in knowledge organization, and it can support the enrichment of measurements and gaining knowledge [2] Ontology is one of the methods that use semantics. Ontology is a collection of terms in a domain, and these terms are linked to visual properties, relationships, and associations.…”

Section: Introductionmentioning

confidence: 99%

An Improved Route‐Finding Algorithm Using Ubiquitous Ontology‐Based Experiences Modeling

et al. 2019

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Every day, people are hired in different organizations and old and retiring employees are eliminated from enterprise systems. Eliminating these individuals from organizations leads to the loss of their spatial experiences. In addition, since new employees lack relevant experience, they need a long time to develop the correct skills for the company and may even cause damage to the organization during this learning process. Therefore, storing the spatial experience of individuals is a critical issue. Due to the intelligence of ubiquitous Geospatial Information System (GIS), any experience from any user can be received and stored. In the future, based on these experiences, an appropriate service to each user may be provided as needed. This paper aims to propose an ontology-based model to store spatial experiences in the field of ubiquitous GIS route finding. For this purpose, first ontology is designed for route finding, and then according to this ontology, an ontology-based route-finding algorithm is developed for ubiquitous GIS. Finally, this algorithm is implemented for Tehran, Iran, and its results are compared with the shortest path algorithm (Dijkstra’s algorithm) in terms of the route length and travel time for peak traffic time. The results show that while the route length obtained from the ontology-based algorithm is more than Dijkstra’s algorithm, the travel time is lower, and on some routes the difference in travel time saved reaches 35 minutes.

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A Review of Semantic Sensor Technologies in Internet of Things Architectures

Cited by 33 publications

References 168 publications

Internet of Robotic Things Intelligent Connectivity and Platforms

Internet of Robotic Things Intelligent Connectivity and Platforms

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

An Improved Route‐Finding Algorithm Using Ubiquitous Ontology‐Based Experiences Modeling

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