東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Multi sensor system for pedestrian t...

Marron Monteserin, Juan Jose.

Linked to FindBook

Google Book

Amazon

博客來

Multi sensor system for pedestrian tracking and activity recognition in indoor environments.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multi sensor system for pedestrian tracking and activity recognition in indoor environments./
Author:	Marron Monteserin, Juan Jose.
Description:	95 p.
Notes:	Source: Masters Abstracts International, Volume: 52-06.
Contained By:	Masters Abstracts International52-06(E).
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1553867
ISBN:	9781303819698

Multi sensor system for pedestrian tracking and activity recognition in indoor environments.
Marron Monteserin, Juan Jose.

Multi sensor system for pedestrian tracking and activity recognition in indoor environments. - 95 p.

Source: Masters Abstracts International, Volume: 52-06.

Thesis (M.S.C.S.)--University of South Florida, 2014.

This item must not be sold to any third party vendors.

The widespread use of mobile devices and the rise of Global Navigation Satellite Systems (GNSS) have allowed mobile tracking applications to become very popular and valuable in outdoor environments. However, tracking pedestrians in indoor environments with Global Positioning System (GPS)-based schemes is still very challenging given the lack of enough signals to locate the user. Along with indoor tracking, the ability to recognize pedestrian behavior and activities can lead to considerable growth in location-based applications including pervasive healthcare, leisure and guide services (such as, museum, airports, stores, etc.), and emergency services, among the most important ones. This thesis presents a system for pedestrian tracking and activity recognition in indoor environments using exclusively common off-the-shelf sensors embedded in smartphones (accelerometer, gyroscope, magnetometer and barometer). The proposed system combines the knowledge found in biomechanical patterns of the human body while accomplishing basic activities, such as walking or climbing stairs up and down, along with identifiable signatures that certain indoor locations (such as turns or elevators) introduce on sensing data. The system was implemented and tested on Android-based mobile phones with a fixed phone position. The system provides accurate step detection and count with an error of 3% in flat floor motion traces and 3.33% in stairs. The detection of user changes of direction and altitude are performed with 98.88% and 96.66% accuracy, respectively. In addition, the activity recognition module has an accuracy of 95%. The combination of modules leads to a total tracking error of 90.81% in common human motion indoor displacements.

ISBN: 9781303819698Subjects--Topical Terms:

626642
Computer Science.

Multi sensor system for pedestrian tracking and activity recognition in indoor environments.
LDR:02784nmm a2200289 4500 001 2057300
005 20150610074907.5
008 170521s2014 ||||||||||||||||| ||eng d
020 $a 9781303819698
035 $a (MiAaPQ)AAI1553867
035 $a AAI1553867
040 $a MiAaPQ $c MiAaPQ
100 1 $a Marron Monteserin, Juan Jose. $3 3171125
245 1 0 $a Multi sensor system for pedestrian tracking and activity recognition in indoor environments.
300 $a 95 p.
500 $a Source: Masters Abstracts International, Volume: 52-06.
500 $a Adviser: Miguel A. Labrador.
502 $a Thesis (M.S.C.S.)--University of South Florida, 2014.
506 $a This item must not be sold to any third party vendors.
520 $a The widespread use of mobile devices and the rise of Global Navigation Satellite Systems (GNSS) have allowed mobile tracking applications to become very popular and valuable in outdoor environments. However, tracking pedestrians in indoor environments with Global Positioning System (GPS)-based schemes is still very challenging given the lack of enough signals to locate the user. Along with indoor tracking, the ability to recognize pedestrian behavior and activities can lead to considerable growth in location-based applications including pervasive healthcare, leisure and guide services (such as, museum, airports, stores, etc.), and emergency services, among the most important ones. This thesis presents a system for pedestrian tracking and activity recognition in indoor environments using exclusively common off-the-shelf sensors embedded in smartphones (accelerometer, gyroscope, magnetometer and barometer). The proposed system combines the knowledge found in biomechanical patterns of the human body while accomplishing basic activities, such as walking or climbing stairs up and down, along with identifiable signatures that certain indoor locations (such as turns or elevators) introduce on sensing data. The system was implemented and tested on Android-based mobile phones with a fixed phone position. The system provides accurate step detection and count with an error of 3% in flat floor motion traces and 3.33% in stairs. The detection of user changes of direction and altitude are performed with 98.88% and 96.66% accuracy, respectively. In addition, the activity recognition module has an accuracy of 95%. The combination of modules leads to a total tracking error of 90.81% in common human motion indoor displacements.
590 $a School code: 0206.
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, General. $3 1020744
690 $a 0984
690 $a 0537
710 2 $a University of South Florida. $b Computer Science and Engineering. $3 1682850
773 0 $t Masters Abstracts International $g 52-06(E).
790 $a 0206
791 $a M.S.C.S.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1553867