메뉴 건너뛰기




Volumn , Issue , 2008, Pages 25-28

Determining transportation mode on mobile phones

Author keywords

[No Author keywords available]

Indexed keywords

ACCELEROMETER SENSOR; ACCURACY LEVEL; APPLICATION REQUIREMENTS; CLASSIFICATION SYSTEM; CONTEXTUAL INFORMATION; DATA SETS; FIRST-ORDER HIDDEN MARKOV MODELS; GPS RECEIVERS; IMAGERS; PERSONAL MONITORING; PROTOTYPE CLASSIFICATION; TARGET APPLICATION; TRANSPORTATION MODE; TRAVEL PATTERNS;

EID: 70349101313     PISSN: 15504816     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISWC.2008.4911579     Document Type: Conference Paper
Times cited : (96)

References (17)
  • 1
    • 59249102131 scopus 로고    scopus 로고
    • Seeing our signals: Combining location traces andweb based models for personal discovery
    • E. Agapie et. al. Seeing Our Signals: Combining Location Traces andWeb Based Models for Personal Discovery. HotMobile, 2008.
    • (2008) HotMobile
    • Agapie, E.1
  • 3
    • 33750288403 scopus 로고    scopus 로고
    • Mobility detection using everyday GSM traces
    • T. Sohn et. al. Mobility Detection Using Everyday GSM Traces. Ubiquitous Computing, pages 212-224, 2006.
    • (2006) Ubiquitous Computing , pp. 212-224
    • Sohn, T.1
  • 4
    • 70450228889 scopus 로고    scopus 로고
    • Mobile context inference using low-cost sensors
    • E. Welbourne, et. al. Mobile context inference using low-cost sensors. LOCA, 2005.
    • (2005) LOCA
    • Welbourne, E.1
  • 5
    • 77954405064 scopus 로고    scopus 로고
    • Parsimonious mobility classification using GSM and WiFi traces
    • M. Mun, et. al. Parsimonious Mobility Classification using GSM and WiFi Traces. Hot-EmNets, 2008.
    • (2008) Hot-EmNets
    • Mun, M.1
  • 6
    • 70349122861 scopus 로고    scopus 로고
    • Practical activity recognition using GSM data
    • I.A.H. Muller. Practical Activity Recognition using GSM Data. ISWC, 2006.
    • (2006) ISWC
    • Muller, I.A.H.1
  • 7
    • 4644220755 scopus 로고    scopus 로고
    • Activity recognition from user- Annotated acceleration data
    • L. Bao and S.S. Intille. Activity Recognition from User- Annotated Acceleration Data. Pervasive, 2004.
    • (2004) Pervasive
    • Bao, L.1    Intille, S.S.2
  • 8
    • 0042707813 scopus 로고    scopus 로고
    • Validity of 10 pedometers for measuring steps, distance, and energy cost
    • S.E. Crouter et. al. Validity of 10 Pedometers for Measuring Steps, Distance, and Energy Cost. MSSE, 2003.
    • (2003) MSSE
    • Crouter, S.E.1
  • 9
    • 33751063964 scopus 로고    scopus 로고
    • Multi-sensor activity context detection for wearable computing
    • N. Kern et. al. Multi-sensor Activity Context Detection for Wearable Computing. EUSAI, 2003.
    • (2003) EUSAI
    • Kern, N.1
  • 10
    • 0034506339 scopus 로고    scopus 로고
    • Context awareness by analysing accelerometer data
    • C. Randell and H. Muller. Context awareness by analysing accelerometer data. ISWC, 2000.
    • (2000) ISWC
    • Randell, C.1    Muller, H.2
  • 11
    • 33745823819 scopus 로고    scopus 로고
    • A Practical approach to recognizing physical activities
    • J. Lester et. al. A Practical Approach to Recognizing Physical Activities. Pervasive, 2006.
    • (2006) Pervasive
    • Lester, J.1
  • 12
    • 84880762436 scopus 로고    scopus 로고
    • A hybrid discriminative/generative approach for modeling human activities
    • J. Lester et. al. A hybrid discriminative/generative approach for modeling human activities. IJCAI, 2005.
    • (2005) IJCAI
    • Lester, J.1
  • 13
    • 70349157476 scopus 로고    scopus 로고
    • Nokia n95
    • Nokia. Nokia n95. http://www.nseries.com, 2007.
    • (2007) Nokia
  • 17
    • 33845294797 scopus 로고    scopus 로고
    • Trading off prediction accuracy and power consumption for context-aware wearable computing
    • A. Krause, et. al. Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing. ISWC, 2005.
    • (2005) ISWC
    • Krause, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.