NDLI: RTS Assisted Mobile Localization: Mitigating Jigsaw Puzzle Problem of Fingerprint Space with Extra Mile

Content Provider	IEEE Xplore Digital Library
Author	Chao Song Jie Wu Li Lu Ming Liu
Copyright Year	2015
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China (Chao Song; Li Lu; Ming Liu) \|\| Dept. of Comput. & Inf. Sci., Temple Univ., Temple, TX, USA (Jie Wu)
Abstract	With the development of Location Based Services (LBSs), both academic researchers and industries have paid more attention to GPS-less mobile localization on mobile phones. The majority of the existing localization approaches have utilized signal-fingerprint as a metric for location determinations. However, one of the most challenging issues is the problem of uncertain fingerprints for building the fingerprint map, termed as the jigsaw puzzle problem. In this paper, for more accurate fingerprints of the mobile localization, we investigate the changes of Received Signal Strength Indication (RSSI) from the connected cell-towers over time along the mobile users' trajectories, termed as RSSI Time Series (RTS). Thus, we propose an RTS Assisted Localization System (RALS), which is a GPS-less outdoor mobile localization system. For localization, an RTS map is built on the back-end server, which consists of RTS harvested from the mobile phones, by the way of crowd sensing. The jigsaw puzzle problem slows down the map construction solely by the regular unintentional users with short-distance trajectories, and affects its efficiency. To speed up the map construction, we propose employing a few advanced intentional users with additional long-distance trajectories, at a higher cost than the regular user, this is called extra mile. Our extensional experiments verify the effectiveness of our localization system.
Sponsorship	IEEE Comput. Soc.
Starting Page	434
Ending Page	442
File Size	636747
Page Count	9
File Format	PDF
e-ISBN	9781467391016
DOI	10.1109/MASS.2015.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	outdoor mobile localization Roads Time series analysis Buildings Mobile communication Mobile handsets Trajectory RSSI time series Servers crowdsensing jigsaw puzzle problem
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

K-Means Fingerprint Clustering for Low-Complexity Floor Estimation in Indoor Mobile Localization

Indoor localization of objects based on RSSI and MEMS sensors

Pattern Recognition Comparative Analysis Applied to Fingerprint Indoor Mobile Sensors Localization

Remote Cloud or Local Crowd: Communicating and Sharing the Crowdsensing Data

Database Correlation for GSM Location in Outdoor & Indoor Environments

Context-Aware Recruitment Scheme for Opportunistic Mobile Crowdsensing

Sahyog: A middleware for mobile collaborative applications

A three-dimensional positioning system based on RSSI for the wireless sensor network

On-demand fingerprint selection for 802.11-based positioning systems

RTS Assisted Mobile Localization: Mitigating Jigsaw Puzzle Problem of Fingerprint Space with Extra Mile

Similar Documents

K-Means Fingerprint Clustering for Low-Complexity Floor Estimation in Indoor Mobile Localization

Indoor localization of objects based on RSSI and MEMS sensors

Pattern Recognition Comparative Analysis Applied to Fingerprint Indoor Mobile Sensors Localization

Remote Cloud or Local Crowd: Communicating and Sharing the Crowdsensing Data

Database Correlation for GSM Location in Outdoor & Indoor Environments

Context-Aware Recruitment Scheme for Opportunistic Mobile Crowdsensing

Sahyog: A middleware for mobile collaborative applications

A three-dimensional positioning system based on RSSI for the wireless sensor network

On-demand fingerprint selection for 802.11-based positioning systems

RTS Assisted Mobile Localization: Mitigating Jigsaw Puzzle Problem of Fingerprint Space with Extra Mile