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Abstract
The rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like water and energy. So, an efficient management of resources is strongly required. What is more, a global warming and carbon emissions are considered as some critical factors for living conditions in many cities, too. A vision of a smart city is related to a better protection of a natural environment and a more efficient use of it. Moreover, citizens expect an efficient and sustainable transportation in livable city. To present some solutions on above issues, this paper outlines the methodology of using social media to provide necessary knowledge by citizenship training systems. In particular, some selected e-learning applications have been characterized. They are related to pedagogical agents in e-learning. In addition, some advanced meta-heuristics have been proposed with particular emphasis on genetic programming, artificial neural networks, neuro-evolution algorithms, support vector machines, and some collective intelligence algorithms. Finally, cloud services are discussed regarding a smart city management and training.
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Authors (4)
-
Jerzy Balicki dr hab. inż.
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Honorata Balicka
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Keywords
Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- The 10th Jubilee Scientific Conference – InfoGlob 2018 strony 1 - 11
- Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Balicki J., Balicka H., Dryja P., TYSZKA M.: Social media for e-learning of citizens in smart city// The 10th Jubilee Scientific Conference – InfoGlob 2018/ ed. Rogula-Kopiec P. : , 2018, s.1-11
- DOI:
- Digital Object Identifier (open in new tab) 10.1051/shsconf/20185701002
- Verified by:
- Gdańsk University of Technology
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