English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The idea of modern urban systems and smart cities requires monitoring andcareful analysis of different signals. Such signals can originate fromdifferent sources and one of the most promising is the BTS, i.e. basetransceiver station, an element of mobile carrier networks. This paper presentsthe fundamental problems of elicitation, classification and understanding ofsuch signals so as to develop context-aware and pro-active systems in urbanareas. These systems are characterized by the omnipresence of computing whichis strongly focused on providing on-line support to users/inhabitants of smartcities. A method of analyzing selected elements of mobile phone datasetsthrough understanding inhabitants' behavioral fingerprints to obtain smartscenarios for public transport is proposed. Some scenarios are outlined. Amulti-agent system is proposed. A formalism based on graphs that allowsreasoning about inhabitant behaviors is also proposed.

Towards a better understanding and behavior recognition of inhabitants in smart cities. A public transport case