Paper Info
Title
Crowdsourcing from the True crowd: Device, vehicle, road-surface and driving independent road profiling from smartphone sensors.
Abstract
Existing smartphone-based systems for detection of road surface events such as speed-breakers, potholes, broken road patches, etc. have been developed primarily for the use in four-wheeler vehicles such as cars with perfect driving maneuvers over a road with occasional irregularities. However, our experiments on a 673 km road trail in a suburban city of India, where an overall road condition is poor, show that such event detection accuracy drops to less than 80% for speed-breakers and less than 70% for potholes, when the crowdsourcing data is collected from different vehicles such as two-wheeler (bike or scooty), three-wheeler (auto-rickshaw) or four-wheeler (car) or with different smartphones kept at different positions (in-pocket, in-dashboard, vehicle-mounted).
Year
DOI
Venue
2020
10.1016/j.pmcj.2019.101103
Pervasive and Mobile Computing
Keywords
Field
DocType
Smartphone,Crowdsourcing,Road profiling,Urban computing
Decision tree,Android (operating system),Computer science,Crowdsourcing,Profiling (computer programming),Real-time computing,Road surface,Thresholding,Cluster analysis,Classifier (linguistics),Distributed computing
Journal
Volume
ISSN
Citations 
61
1574-1192
1
PageRank 
References 
Authors
0.37
0
7
Name
Order
Citations
PageRank
Munshi Yusuf Alam110.37
Akash Nandi210.37
Abhay Kumar310.37
Sujoy Saha44713.03
Saha Mousumi531.81
Subrata Nandi67121.37
Sandip Chakraborty72416.46