On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
A dynamic method for dominant point detection
Graphical Models
A two-dimensional interpolation function for irregularly-spaced data
ACM '68 Proceedings of the 1968 23rd ACM national conference
Understanding Link Quality in 802.11 Mobile Ad Hoc Networks
IEEE Internet Computing
Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Connectivity Maps: Measurements and Applications
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 09
Accuracy characterization for metropolitan-scale Wi-Fi localization
Proceedings of the 3rd international conference on Mobile systems, applications, and services
A measurement study of vehicular internet access using in situ Wi-Fi networks
Proceedings of the 12th annual international conference on Mobile computing and networking
MobiSteer: using steerable beam directional antenna for vehicular network access
Proceedings of the 5th international conference on Mobile systems, applications and services
Self-management in chaotic wireless deployments
Wireless Networks
Understanding wifi-based connectivity from moving vehicles
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
A sensor platform for sentient transportation research
EuroSSC'06 Proceedings of the First European conference on Smart Sensing and Context
IEEE Transactions on Wireless Communications
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Wireless connectivity for vehicles is a fast-growing market, with a plethora of different network technologies already in use. Surveys of the numbers of IEEE 802.11b/g access points in cities point to hundreds to thousands of networks within each square kilometre, with coverage areas that are not easily predicted due to the complexities of the urban environment. In order to take advantage of the diversity in wireless networks available, we need data concerning their coverage. Methods of generating such coverage maps that are accurate, space-efficient and easy to query are not a well addressed area. In this paper, we present and evaluate, using a large corpus of real-world data, novel algorithms for processing large quantities of signal strength values into coverage maps that satisfy such requirements.