Di Chiappari, Alain
(2016)
A Collaborative Mobile Crowdsensing System for Smart Cities.
[Laurea magistrale], Università di Bologna, Corso di Studio in
Informatica [LM-DM270]
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Abstract
Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.
Abstract
Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Di Chiappari, Alain
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Curriculum C: Sistemi e reti
Ordinamento Cds
DM270
Parole chiave
Mobile Crowdsensing,Smart City,Internet of Things,CoAP,Android,Environmental Monitoring,Geofencing
Data di discussione della Tesi
12 Ottobre 2016
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Di Chiappari, Alain
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Curriculum C: Sistemi e reti
Ordinamento Cds
DM270
Parole chiave
Mobile Crowdsensing,Smart City,Internet of Things,CoAP,Android,Environmental Monitoring,Geofencing
Data di discussione della Tesi
12 Ottobre 2016
URI
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