Utilizing Next Generation Emerging Technologies for Enabling Collective Computational Intelligence in Disaster Management

Bessis, Nik; Assimakopoulou, Eleana; Aydın, Mehmet Emin; Xhafa, Fatos

doi:10.1007/978-3-642-20344-2_19

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…The maximum data generated through online (Web 2.0) is of flat text format; this can be easily consumable by human beings (Bessis, 2011), meaning that it is easily understandable. However, it is very difficult for the machines to process and understand.…”

Section: Challenges On Current Webmentioning

confidence: 99%

“…Semantic Web is the answer for many questions that are raised out of the Web 2.0. The newest concepts include (Bessis, 2011), the blend of deductive databases, expert systems, knowledge based systems along with Semantic Web and its associated applications are much needed to cover the issues mentioned above. The Web 3.0 has the facility of reducing the repeated information and dummy information.…”

Section: Need Of Semantic Webmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Approach for Semantic Web Application in Online Education Based on Steganography

Gurunath

Samanta

2021

International Journal of Web-Based Learning and Teaching Technologies

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Semantic Web technology is not new as most of us contemplate; it has evolved over the years. Linked Data web terminology is the name set recently to the Semantic Web. Semantic Web is a continuation of Web 2.0 and it is to replace existing technologies. It is built on Natural Language processing and provides solutions to most of the prevailing issues. Web 3.0 is the version of Semantic Web caters to the information needs of half of the population on earth. This paper links two important current concerns, the security of information and enforced online education due to COVID-19 with Semantic Web. The Steganography requirement for the Semantic web is discussed elaborately, even though encryption is applied which is inadequate in providing protection. Web 2.0 issues concerning online education and semantic Web solutions have been discussed. An extensive literature survey has been conducted related to the architecture of Web 3.0, detailed history of online education, and Security architecture. Finally, Semantic Web is here to stay and data hiding along with encryption makes it robust.

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Section: Challenges On Current Webmentioning

confidence: 99%

Section: Need Of Semantic Webmentioning

confidence: 99%

A Novel Approach for Semantic Web Application in Online Education Based on Steganography

Gurunath

Samanta

2021

International Journal of Web-Based Learning and Teaching Technologies

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“…Over recent years, some collective computational intelligence technologies and tools have emerged in response to the demands for analyzing big data. Among them, the CEP technology is essential for analyzing the complexity of 3 Uniform (0.5, 0.67) 41 5 3 Uniform (0.5, 0.68) 67 6 3 Uniform (0.5, 0.69) 88 7 3 Uniform (0.5, 0.7) 91 8 3 Uniform (0.5, 0.71) 99 9 3 Uniform (0.5, 0.72) 100 multicriteria that could generate an alert [21], extracting meaningful events. However, the implementation of event pattern conditions can become a handicap for users who are experts on the domain but not in the involved technology.…”

Section: Related Workmentioning

confidence: 99%

Facilitating the Quantitative Analysis of Complex Events through a Computational Intelligence Model-Driven Tool

D́ıaz

Macià

Valero

et al. 2019

Scientific Programming

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Complex event processing (CEP) is a computational intelligence technology capable of analyzing big data streams for event pattern recognition in real time. In particular, this technology is vastly useful for analyzing multicriteria conditions in a pattern, which will trigger alerts (complex events) upon their fulfillment. However, one of the main challenges to be faced by CEP is how to define the quantitative analysis to be performed in response to the produced complex events. In this paper, we propose the use of the MEdit4CEP-CPN model-driven tool as a solution for conducting such quantitative analysis of events of interest for an application domain, without requiring knowledge of any scientific programming language for implementing the pattern conditions. Precisely, MEdit4CEP-CPN facilitates domain experts to graphically model event patterns, transform them into a Prioritized Colored Petri Net (PCPN) model, modify its initial marking depending on the application scenario, and make the quantitative analysis through the simulation and monitor capabilities provided by CPN tools.

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“…Technologies related to Intelligent Transportation Systems (ITS), with advanced traveller information systems (ATIS), travel advisories, variable message signs (VMS) and others, attempt to relieve congestion and decrease travel time by assisting drivers on selecting routes, departure times, and even mode of travel. Also, such technologies rely on a large extent on collective and computational intelligencewhich is why CAPIM was selected as an ideal candidate [24].…”

Section: Case Study: An Intelligent Transportation Systemmentioning

confidence: 99%

Intelligent services for Big Data science

Dobre

Xhafa

2014

Future Generation Computer Systems

246

103

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Cities are areas where big data is having a real impact. Town planners and administration bodies just need the right tools at their fingertips to consume all the data points that a town or city generate and then be able to turn that into actions that improve peoples lives. In this case big data is definitely a phenomenon that has a direct impact on the quality of life for those of us that choose to live in a town or city. Smart Cities of tomorrow will rely not only on sensors within the city infrastructure, but also on a large number of devices that will willingly sense and integrate their data into technological platforms used for introspection into the habits and situations of individuals and city-large communities. Predictions say that cities will generate over 4.1 terabytes per day per square kilometer of urbanized land area by 2016. Handling efficiently such amounts of data already is already a challenge. In this paper we present our solutions designed to support next-generation Big Data applications. We first present CAPIM, a platform designed to automate the process of collecting and aggregating context information on a large scale. It integrates services designed to collect context data (location, users profile and characteristics, as well as the environment). We next present a concrete implementation of an Intelligent Transportation System designed on top of CAPIM. The application is designed to assist users and city officials better understand traffic problems in large cities. Finally, we present a solution to handle efficient storage of context data on a large scale. The combination of these services provide support for intelligent Smart City applications, for

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Utilizing Next Generation Emerging Technologies for Enabling Collective Computational Intelligence in Disaster Management

Cited by 7 publications

References 29 publications

A Novel Approach for Semantic Web Application in Online Education Based on Steganography

A Novel Approach for Semantic Web Application in Online Education Based on Steganography

Facilitating the Quantitative Analysis of Complex Events through a Computational Intelligence Model-Driven Tool

Intelligent services for Big Data science

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