The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
LOCALE: Collaborative Localization Estimation for Sparse Mobile Sensor Networks
Abstract
Mobile devices, by their nature, are very personal devices. As the field of mobile application matures, applications are beginning to include location and other context aware services. In addition, current research is trending to more peer-to-peer capable systems. They will often be very sparse for all or part of their operation because of mobility. While some of these devices localizes with fixed location beacons or per-node GPS, these methods are not always possible due to many constraints. This chapter focuses on a robust statistical method in mobile networks to both determine the location of the device and provide an estimation of the accuracy. This method is provides seamless operation despite the local density of a mobile network, providing the application with a meaningful measure of location with accuracy. While this chapter only focuses on localization, the methods discussed here can be applied to provide other estimation based in-system measurements.
Related Content
|
Subrata Tikadar, Kaushik Paul, Abhishek Mukhopadhyay.
© 2026.
26 pages.
|
|
Devanshi Shrivastava, Debanshi Chakraborty, Manjusha Pandey, Siddharth Swarup Rautray.
© 2026.
32 pages.
|
|
Harshita Gupta, Suman Suman Majumder.
© 2026.
12 pages.
|
|
Subhajit Ghosh.
© 2026.
38 pages.
|
|
Sanjib Kundu, Sourav Kayal.
© 2026.
40 pages.
|
|
Sudip Chatterjee, Pronaya Bhattacharya, Subrata Tikadar.
© 2026.
14 pages.
|
|
Chandan Kumar Singh.
© 2026.
40 pages.
|
|
|