Authors:
Carlos Oberdan Rolim
1
;
Anubis Graciela de Moraes Rossetto
1
;
Valderi R. Q. Leithardt
2
;
Guilherme A. Borges
1
;
Tatiana F. M. dos Santos
3
;
Adriano M. Souza
3
and
Claudio Geyer
1
Affiliations:
1
Federal University of Rio Grande do Sul (UFRGS), Brazil
;
2
UFRGS, Brazil
;
3
Federal University of Santa Maria (UFSM), Brazil
Keyword(s):
Urban Sensing, Smart Cities, Opportunistic Networks, Machine Learning, Prediction, Situation Awareness.
Related
Ontology
Subjects/Areas/Topics:
Enterprise Information Systems
;
Software Agents and Internet Computing
;
Telecommunications
;
Ubiquitous Computing
;
Wireless and Mobile Computing
;
Wireless and Mobile Technologies
;
Wireless Information Networks and Systems
Abstract:
Social urban sensing is a new paradigm which exploits human-carried or vehicle-mounted sensors to ubiquitously
collect data for large-scale urban sensing. A challenge of such scenario is how to transmit sensed
data in situations where the networking infrastructure is intermittent or unavailable. In this context, this paper
outlines the early stages of our research which is concerned with a novel engine that uses Opportunistic
Networks paradigm to underlie the data transmission of social urban sensing applications. It applies Situation
awareness, Neural Networks and Fuzzy Logic for routing and decision-making process. As we know, this is
the first paper to use such approaches in Smart Cities area with focus on social sensing application. As well as
being original, the preliminary results from our simulations signals the way that further research can be carried
out in this area.