SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Understanding the Lifestyle of Older Population: Mobile Crowdsensing Approach
1 references·6 citing·24 second hop
Understanding the Lifestyle of Older Population: Mobile Crowdsensing Approach (2018)Understanding the Lifestyle of Older Popu…On Combining Crowdsourcing, Sensing and Open Data for an Accessible Smart City (2014)On Combining Crowdsourcing, S…Clustering and Analysis of GPS Trajectory Data Using Distance-Based Features (2022)Clustering and Analysis of GP…WiFi Fingerprint Clustering for Urban Mobility Analysis (2021)WiFi Fingerprint Clustering f…Trip Purposes Mining From Mobile Signaling Data (2021)Trip Purposes Mining From Mob…The Study of Urban Residential’s Public Space Activeness Using Space-Centric Approach (2021)The Study of Urban Residentia…Uber Movement Data: A Proxy for Average One-way Commuting Times by Car (2020)Uber Movement Data: A Proxy f…Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data (2020)Multiple-Perspective Clusteri…The credibility of volunteered geographic information (2008)Are Crowdsourced Datasets Suitable for Specialized Routing Services? Case Study of OpenStreetMap for Routing of People with Limited Mobility (2017)The Role of Social Factors in the Accessibility of Urban Areas for People with Motor Disabilities (2018)Mapping with Stakeholders: An Overview of Public Participatory GIS and VGI in Transport Decision-Making (2019)Understanding mobility based on GPS data (2008)GIS based destination accessibility via public transit and walking in Auckland, New Zealand (2011)Transport accessibility and social inequities: a tool for identification of mobility needs and evaluation of transport investments (2012)Discovering Intra-Urban Population Movement Pattern Using Taxis’ Origin and Destination Data and Modeling the Parameters Affecting Population Distribution (2021)Understanding individual human mobility patterns (2008)Urban computing with taxicabs (2011)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Participatory Bluetooth Scans Serving as Urban Crowd Probes (2014)Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment (2015)Understanding Crowd Behaviors in a Social Event by Passive WiFi Sensing and Data Mining (2020)Bus travel feature inference with small samples based on multi-clustering topic model over Internet of Things (2024)Exploring human movements in Singapore (2013)Estimating human trajectories and hotspots through mobile phone data (2014)Extracting point of interest and classifying environment for low sampling crowd sensing smartphone sensor data (2017)The Gravity Model (2011)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Spatial–Temporal Convolutional Model for Urban Crowd Density Prediction Based on Mobile-Phone Signaling Data (2021)TrajSGAN: A Semantic-Guiding Adversarial Network for Urban Trajectory Generation (2023)A hybrid method for intercity transport mode identification based on mobility features and sequential relations mined from cellular signaling data (2024)Returners and explorers dichotomy in human mobility (2015)
this work references cited by second hop

References

  • 2014On Combining Crowdsourcing, Sensing and Open Data for an Accessible Smart City95 cited

Cited by

  • 2021Trip Purposes Mining From Mobile Signaling Data40 cited
  • 2020Uber Movement Data: A Proxy for Average One-way Commuting Times by Car14 cited
  • 2021WiFi Fingerprint Clustering for Urban Mobility Analysis11 cited
  • 2020Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data10 cited
  • 2021The Study of Urban Residential’s Public Space Activeness Using Space-Centric Approach10 cited
  • 2022Clustering and Analysis of GPS Trajectory Data Using Distance-Based Features5 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work