Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Pralav Dessai

dblp:133/3835 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Wireless sensing and localization · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › localization algorithms
calibration-free localization
0.212013
FreeLoc: Calibration-free crowdsourced indoor localization · INFOCOM 2013
Wireless sensing and localization › localization algorithms
crowdsourced localization
0.212013
FreeLoc: Calibration-free crowdsourced indoor localization · INFOCOM 2013
Wireless sensing and localization
device heterogeneity
0.212013
FreeLoc: Calibration-free crowdsourced indoor localization · INFOCOM 2013
Wireless sensing and localization
indoor localization
0.212013
FreeLoc: Calibration-free crowdsourced indoor localization · INFOCOM 2013
Wireless sensing and localization › indoor localization
wifi fingerprinting
0.212013
FreeLoc: Calibration-free crowdsourced indoor localization · INFOCOM 2013

Methods — techniques the papers use, named apart from their topics

RSS fingerprinting · 0.2
YearPublicationVenuePosition
2013 FreeLoc: Calibration-free crowdsourced indoor localization
abstract
Many indoor localization techniques that rely on RF signals from wireless Access Points have been proposed in the last decade. In recent years, research on crowdsourced (also known as “Organic”) Wi-Fi fingerprint positioning systems has been attracting much attention. This participatory approach introduces new challenges that no previously proposed techniques have taken into account. This paper proposes “FreeLoc”, an efficient localization method addressing three major technical issues posed in crowdsourcing based systems. Our novel solution facilitates 1) extracting accurate fingerprint values from short RSS measurement times 2) calibration-free positioning across different devices and 3) maintaining a single fingerprint for each location in a radio map, irrespective of any number of uploaded data sets for a given location. Through experiments using four different smartphones, we evaluate our new indoor positioning method. The experimental results confirm that the proposed scheme provides consistent localization accuracy in an environment where the device heterogeneity and the multiple surveyor problems exist.
Sungwon Yang, Pralav Dessai, Mansi Verma, Mario Gerla
INFOCOM2