Cognitive Management for the Internet of Things: A Framework for Enabling Autonomous Applications

Foteinos, Vassilis; Kelaidonis, Dimitrios; Poulios, George; Vlacheas, Panagiotis; Stavroulaki, Vera; Demestichas, Panagiotis

doi:10.1109/mvt.2013.2281657

Cited by 56 publications

(30 citation statements)

References 10 publications

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“…Furthermore, IoT-based systems implementing real-world applications continuously evolve and generate unforeseen requirements [9], which requires the coordination of the management processes as well as interacting with humans to learn from his intelligence and provide more accurate analytics. Recently, a new era of IoT called "Cognitive IoT" [10] has been enunciated. It aims at integrating cognitive technologies into IoT-based systems to ensure the smart management through enabling the cooperation and interaction between IoT and human.…”

Section: Nevertheless the Integration Of Iot Poses New Challenges Fomentioning

confidence: 99%

A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare

Mezghani

Expósito

Drira

2017

IEEE Trans. Emerg. Top. Comput. Intell.

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Due to its abilities to capture real-time data concerning the physical world, the Internet of Things (IoT) phenomenon is fast gaining momentum in different applicative domains. Its benefits are not limited to connecting things, but lean on how the collected data is transformed into insights and interact with domain experts for better decisions. Nonetheless, a set of challenges including the complexity of IoT-based systems and the management of the ensuing big and heterogeneous data and as well as the system scalability; need to be addressed for the development of flexible smart IoT-based systems that drive the business decision-making. Consequently, inspired from the human nervous system and cognitive abilities, we have proposed a set of autonomic cognitive design patterns that alleviate the design complexity of smart IoT-based systems, while taking into consideration big data and scalability management. The ultimate goal of these patterns is providing generic and reusable solutions for elaborating flexible smart IoTbased systems able to perceive the collected data and provide decisions. These patterns are articulated within a model-driven methodology that we have proposed to incrementally refine the system functional and nonfunctional requirements. Following the proposed methodology, we have combined and instantiated a set of patterns for developing a flexible cognitive monitoring system to manage patients' health based on heterogeneous wearable devices. We have highlighted the gained flexibility and demonstrated the ability of our system to integrate and process heterogeneous 2 large scale data streams. Finally, we have evaluated the system performance in terms of response time and scalability management.

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Section: Nevertheless the Integration Of Iot Poses New Challenges Fomentioning

confidence: 99%

A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare

Mezghani

Expósito

Drira

2017

IEEE Trans. Emerg. Top. Comput. Intell.

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“…Cognitive functionalities can select most relevant VOs of an application dynamically. Abstraction of technological heterogeneity derived from vast amount of heterogeneous objects and the development of a cognitive management framework comprising the VO/ CVO have been discussed by iCore project in Foteinos et al, 7 Sasidharan et al, 8 and Kelaidonis et al 9 Ubiquitous service provisioning can be ensured by composing VO/CVO and service policies. To compose a service, the composition architecture, methodology, and algorithm have been discussed in Ara et al 10 and Kim et al 11,12 In a previous work, 13 objectives of the Do-itYourself Smart Experiences (DiYSE Smart Experiences), such as creating awareness, setting up and controlling applications by user own self, and interactive and following experiences in the IoT, have been discussed.…”

Section: Related Workmentioning

confidence: 99%

Knowledge-based open Internet of Things service provisioning architecture on beacon-enabled Web of Objects

Kibria

Chong

2016

International Journal of Distributed Sensor Networks

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Web of Objects uses a semantic ontology to create and provide knowledge-based Internet of Things services in terms of virtual objects and composite virtual objects. The objects are created through virtualization with the use of semantic ontology to form the virtual objects, where multiple virtual objects are combined to form the composite virtual objects to offer the services. Beacon-enabled Web of Objects is the extension of the existing web that allows the beacon to broadcast the uniform resource identifier of the real-world object to the nearer mobile devices. Based on the user selection and request, the service is handled and offered by the Web of Objects platform; thus, an architecture on the beacon-enabled Web of Objects has been proposed in this article. To offer the knowledge-based services, a knowledge creation model has been presented. To realize the knowledge-based service features on the proposed architecture, a use case scenario has been presented and a conceptual semantic ontology model has been designed. Finally, to assess the features, a prototype has been implemented and demonstrated on the use case scenario.

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“…Using this deluge of data to build information and knowledge for decision making is a significant business challenge. Machine assistance through machine learning techniques are enhancing this ability [7], generating new information to feed and help decision making [8] but ultimately the human decision maker plays a central role. The human eye is the most data intensive and efficient sense in the human body [9] playing a role facilitating memorization in many cases.…”

Section: Introductionmentioning

confidence: 99%

SiMoNa: A Proof-of-concept Domain-Specific Modeling Language for IoT Infographics

Morais¹,

Sadok²,

Kelner³

et al. 2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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The Internet of Things (IoT) is a prominent concept in academic and technology business discourse in recent times reflecting a wider trend to connect physical objects to the Internet and to each other. This idea of connecting things started in the beginning of the 2008 through RFID. But after the open hardware initiatives (as Arduino), it gained more visibility and access to experiments with sensors in the environment. The IoT is already generating an unprecedented volume of data in greater varieties and higher velocities. Making sense of such data is an emerging and significant challenge. Infographics are visual representations that provide a visual space for end users to compare and analyze data, information, and knowledge in a more efficient form than traditional forms. The nature of IoT requires a continuum modification in how end users see information to achieve such efficiency gains. Conceptualizing and implementing infographics in an IoT system can thus require significant planning and development for both data scientists, graphic designers and developers resulting in both costs in terms of time and effort. To address this problem, this paper presents SiMoNa, a domain-specific modeling language (DSML) to create, connect, interact, and build interactive infographic presentations for IoT systems efficiently based on the model-driven development (MDD) paradigm. The language and approach are validated using real-world use cases.

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Cognitive Management for the Internet of Things: A Framework for Enabling Autonomous Applications

Cited by 56 publications

References 10 publications

A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare

A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare

Knowledge-based open Internet of Things service provisioning architecture on beacon-enabled Web of Objects

SiMoNa: A Proof-of-concept Domain-Specific Modeling Language for IoT Infographics

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