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Crowdsourcing with Smartphones Chatzimilioudis et al 2012 (Opportunistic,…
Crowdsourcing with Smartphones
Chatzimilioudis et al 2012
extension of web-based applications
users without conventional workstation/real-time location
Gigwalk
Jana
new applications
real-time information
1.Waze
VTrack
Ear-Phone
PotHole
Participatory
requires human skill
typically web-based
active user involvement
incentives more likely required
Opportunistic
data generated from sensors
passive user involvement/automatic
typically location based
high transparency
SmartTrace
asks a crowd of smartphone users to help identify mobility patterns or a given trajectory's popularity
ride sharing
large-scale transit planning
habitat monitoring
Crowdcast
continuously provides geographical nearest neighbour
sends out SOS and emergency dispatch
natural disaster warnings
SmartP2P
data sharing over a crowd of mobile users participating in a smartphone social network by using the crowd's location data to maximize the search process
places of interest
share interests
no need for central authority involvement
Classical crowdsourcing
centralized
ships data generated from the crowd to a server and generates an answer
uses up phone's battery power
perceived delays from the user
degrades network health
requires personal information to be disclosed to central authority
Examples: Facebook, Twitter, YouTube
decentralized
queries sent to smartphone where computations are performed locally
can also deplete battery power and create perceived user delays
Location dependent-crowdsourcing
Cellular-only
transmits WIFI signal or cell tower over the internet
10'-100's of meters
least accurate ( 3G connection)
most expensive ( 3G connection)
WiFi-only
transmits WIFI signal or cell tower over the internet
10-100's of meters
least energy consumed
GPS-only
a few meters
no need for internet
most energy consumed
most accurate