Describing human-object interaction in Intelligent Space

Niitsuma, Mihoko; Yokoi, K.; Hashimoto, Hideki

doi:10.1109/hsi.2009.5091012

Cited by 10 publications

(6 citation statements)

References 13 publications

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“…4W1H [10,11] is a popular approach that is being used to describe the basics of an event/situation. To define the comprehensive list of concepts for an IoT ontology, we rely on the use of 4W1H methodology.…”

Section: Identifying Core Conceptsmentioning

confidence: 99%

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A study of existing Ontologies in the IoT-domain

Bajaj,

Agarwal,

Singh

et al. 2017

Preprint

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Several domains have adopted the increasing use of IoT-based devices to collect sensor data for generating abstractions and perceptions of the real world. This sensor data is multi-modal and heterogeneous in nature. This heterogeneity induces interoperability issues while developing cross-domain applications, thereby restricting the possibility of reusing sensor data to develop new applications. As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data. Several ontologies have been proposed to handle different aspects of IoT-based sensor data collection, ranging from discovering the IoT sensors for data collection to applying reasoning on the collected sensor data for drawing inferences. In this paper, we survey these existing semantic ontologies to provide an overview of the recent developments in this field. We highlight the fundamental ontological concepts (e.g., sensor-capabilities and context-awareness) required for an IoT-based application, and survey the existing ontologies which include these concepts. Based on our study, we also identify the shortcomings of currently available ontologies, which serves as a stepping stone to state the need for a common unified ontology for the IoT domain.

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Section: Identifying Core Conceptsmentioning

confidence: 99%

“…[9]. We identify these questions using the 4W1H methodology [10,11]. The answers to the competency questions will help us identify the core concepts for a unified IoT ontology.…”

Section: Introductionmentioning

confidence: 99%

A study of existing Ontologies in the IoT-domain

Bajaj,

Agarwal,

Singh

et al. 2017

Preprint

View full text Add to dashboard Cite

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“…Such information is vast, and considering the cost it is not realistic to describe beforehand the use history information on a large number of objects that exist in the space. Therefore, it is necessary that the object's information is written automatically without human intention when the object is used by the user [8].…”

Section: W1hmentioning

confidence: 99%

Using conditional random fields to validate observations in a 4W1H paradigm

Palafox

Jeni

Hashimoto

2011

2011 4th International Conference on Human System Interactions, HSI 2011

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Detecting human activity has been one of the main focuses in intelligent spaces. This is achieved by using a large number of sensors attached both to the humans and the environment. Yet, these systems are prone to failure due to the parallel sensing when miss firings occur. We propose a method to test and prevent the miss firings using conditional random fields, since they provide us with a tool that allows us to confirm whether the expected output or activity is likely to happen in the space or not, given the inputs of the system, which are provided by the 4W1H paradigm, that allows us to segment every piece of information in the space into 5 simple variables (Who, When, What, Where and How).A 80 978-1-4244-9640-2/11/$26.00 ©2011 IEEE

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“…Semantics includes ontologies, contexts, and structured metadata. As ontologies can describe knowledge that is problem relevant [12][13][14] by answering a 4W1H question (what, where, when, who, and how) [15,16], ontological modelling provides a flexible framework of knowledge management (Ontohub https://ontohub.org and DAML http://www.daml.org/ list about 5536 and 282 ontologies, respectively. ).…”

Section: Introductionmentioning

confidence: 99%

A Review of Semantic Sensor Technologies in Internet of Things Architectures

Honti

Abonyi

2019

Complexity

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Intelligent sensors should be seamlessly, securely, and trustworthy interconnected to enable automated high-level smart applications. Semantic metadata can provide contextual information to support the accessibility of these features, making it easier for machines and humans to process the sensory data and achieve interoperability. The unique overview of sensor ontologies according to the semantic needs of the layers of IoT solutions can serve a guideline of engineers and researchers interested in the development of intelligent sensor-based solutions. The explored trends show that ontologies will play an even more essential role in interlinked IoT systems as interoperability and the generation of controlled linkable data sources should be based on semantically enriched sensory data.

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Describing human-object interaction in Intelligent Space

Cited by 10 publications

References 13 publications

A study of existing Ontologies in the IoT-domain

A study of existing Ontologies in the IoT-domain

Using conditional random fields to validate observations in a 4W1H paradigm

A Review of Semantic Sensor Technologies in Internet of Things Architectures

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