NDLI: Mobile sensing of pedestrian flocks in indoor environments using WiFi signals

Content Provider	IEEE Xplore Digital Library
Author	Kjaergaard, M.B. Wirz, M. Roggen, D. Troster, G.
Copyright Year	2012
Description	Author affiliation: Wearable Computing Laboratory, ETH Zurich, Switzerland (Kjaergaard, M.B.; Wirz, M.; Roggen, D.; Troster, G.)
Abstract	In Pervasive Computing research, substantial work has been directed towards radio-based sensing of human movement patterns. This research has, however, mainly been focused on movements of individuals. This paper addresses the joint identification of the movement indoors of multiple persons forming a cohesive whole - specifically flocks - with clustering approaches operating on three different feature sets derived from WiFi signals which are comparatively analysed. Automatic detection of flocks has several important applications, including social and psychological sensing and emergency research studies. We use a dataset comprising 16 subjects forming one to four flocks walking in a building on single and multiple floors. For the detection of flocks we achieved an average F-measure accuracy of up to 85 percent. We report on the advantages and drawbacks of the three different types of feature sets considering their suitability for use “in the wild” or in well-defined environments.
Starting Page	95
Ending Page	102
File Size	941266
Page Count	8
File Format	PDF
ISBN	9781467302562
e-ISBN	9781467302586
e-ISBN	9781467302579
DOI	10.1109/PerCom.2012.6199854
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-19
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Accuracy IEEE 802.11 Standards Sensors Feature extraction Legged locomotion Buildings signal strength-based methods pattern recognition crowd behavior sensing mobile sensing
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

Time-lag method for detecting following and leadership behavior of pedestrians from mobile sensing data

WiFi-assisted human activity recognition

Detecting pedestrian flocks by fusion of multi-modal sensors in mobile phones

Indoor localization on mobile phone platforms using embedded inertial sensors

An Experimental Study on the Behavior of Received Signal Strength in Indoor Environment

Opportunistic crowd sensing in WiFi-enabled indoor areas

HiMLoc: Indoor smartphone localization via activity aware Pedestrian Dead Reckoning with selective crowdsourced WiFi fingerprinting

Indoor location based on independent sensors and WIFI

Smart Phone Based Indoor Pedestrian Localization System

Mobile sensing of pedestrian flocks in indoor environments using WiFi signals

Similar Documents

Time-lag method for detecting following and leadership behavior of pedestrians from mobile sensing data

WiFi-assisted human activity recognition

Detecting pedestrian flocks by fusion of multi-modal sensors in mobile phones

Indoor localization on mobile phone platforms using embedded inertial sensors

An Experimental Study on the Behavior of Received Signal Strength in Indoor Environment

Opportunistic crowd sensing in WiFi-enabled indoor areas

HiMLoc: Indoor smartphone localization via activity aware Pedestrian Dead Reckoning with selective crowdsourced WiFi fingerprinting

Indoor location based on independent sensors and WIFI

Smart Phone Based Indoor Pedestrian Localization System

Mobile sensing of pedestrian flocks in indoor environments using WiFi signals