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DeepMatch2: A comprehensive deep learning-based approach for in-vehicle presence detection
5 references·0 citing·22 second hop
DeepMatch2: A comprehensive deep learning-based approach for in-vehicle presence detection (2021)DeepMatch2: A comprehensive deep learning…Smartphone Data Classification Technique for Detecting the Usage of Public or Private Transportation Modes (2020)Smartphone Data Classificatio…HybridBaro: Mining Driving Routes Using Barometer Sensor of Smartphone (2017)HybridBaro: Mining Driving Ro…RideSense: Towards ticketless transportation (2016)RideSense: Towards ticketless…From Pressure to Path (2015)From Pressure to PathWireless detection of end-to-end passenger trips on public transport buses (2010)Wireless detection of end-to-…Deriving origin–destination data from a mobile phone network (2007)Estimating a Rail Passenger Trip Origin‐Destination Matrix Using Automatic Data Collection Systems (2007)Understanding individual human mobility patterns (2008)Use of Mobile Device Wireless Signals to Determine Transit Route-Level Passenger Origin–Destination Flows: Methodology and Empirical Evaluation (2016)Data analysis of transit systems using low-cost IoT technology (2017)PortoLivingLab: An IoT-Based Sensing Platform for Smart Cities (2018)Tracking unmodified smartphones using wi-fi monitors (2012)Enabling energy-efficient driving route detection using built-in smartphone barometer sensor (2016)Survey of Automated Fare Collection Solutions in Public Transportation (2022)Towards sustainable transport: wireless detection of passenger trips on public transport buses (2008)Towards proximity-based passenger sensing on public transport buses (2013)Urban sensing: Using smartphones for transportation mode classification (2014)Towards Frictionless Public Transit: A Brief Review of Automatic Fare Collection (2024)Automatically characterizing places with opportunistic crowdsensing using smartphones (2012)Mining users' significant driving routes with low-power sensors (2014)Towards Smart Mobility: Journey Reconstruction for Frictionless Public Transit using GPS and GTFS Data (2023)Concurrent mobile (cellular) phone use and driving performance: task demand characteristics and compensatory processes (2000)Analysis of Financial Time Series (2002)A GPS/GIS method for travel mode detection in New York City (2011)Comparative analysis of models and performance indicators for optimal service facility location (2020)Transportation Mode Detection Using Crowdsourced Smartphone Data (2021)Transportation Mode Detection by Using Smartphones and Smartwatches with Machine Learning (2022)
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References

  • 2015From Pressure to Path58 cited
  • 2010Wireless detection of end-to-end passenger trips on public transport buses39 cited
  • 2020Smartphone Data Classification Technique for Detecting the Usage of Public or Private Transportation Modes33 cited
  • 2017HybridBaro: Mining Driving Routes Using Barometer Sensor of Smartphone25 cited
  • 2016RideSense: Towards ticketless transportation5 cited

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