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Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity
3 references·6 citing·32 second hop
Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity (2019)Classifying Passenger and Non-passenger S…Public transport occupancy estimation using WLAN probing (2016)Public transport occupancy es…Feasibility of Analyzing Wi-Fi Activity to Estimate Transit Passenger Population (2016)Feasibility of Analyzing Wi-F…Measuring Bus Passenger Load by Monitoring Wi-Fi Transmissions from Mobile Devices (2014)Measuring Bus Passenger Load …A Machine Learning Approach to Estimate Public Transport Ridership Using Wi-Fi Data (2024)A Machine Learning Approach t…The potential of Wi-Fi data to estimate bus passenger mobility (2023)The potential of Wi-Fi data t…Bayesian Estimation of Passenger Boardings at Bus Stops Using Wi-Fi Probe Requests (2023)Bayesian Estimation of Passen…Utilizing Wi-Fi Sensing and an Optimized Radius Algorithm to Count Passengers with Transfers to Enhance Bus Transit O-D Matrix (2022)Utilizing Wi-Fi Sensing and a…UAI-FI: using artificial intelligence for automatic passenger counting through Wi-Fi and GPS data (2022)UAI-FI: using artificial inte…The practicability of predicting the number of bus passengers by monitoring wi-fi signal from mobile devices with the polynomial regression (2019)The practicability of predict…Reality mining: sensing complex social systems (2005)Mobility Detection Using Everyday GSM Traces (2006)Location-Aware Tools for Improving Public Transit Usability (2009)WiFi Scanner Technologies for Obtaining Travel Data about Circulator Bus Passengers: Case Study in Obuse, Nagano Prefecture, Japan (2018)A Field Study of Internet of Things-Based Solutions for Automatic Passenger Counting (2021)Multi-stage deep learning approaches to predict boarding behaviour of bus passengers (2021)Participatory bluetooth sensing: A method for acquiring spatio-temporal data about participant mobility and interactions at large scale events (2013)The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA (2021)Trends in Toronto’s Subway Ridership Recovery: An Exploratory Analysis of Wi-Fi Records (2024)Deriving origin–destination data from a mobile phone network (2007)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Crowd Density Estimation for Public Transport Vehicles (2014)Bus OD matrix reconstruction based on clustering Wi-Fi probe data (2021)A low-cost automatic people-counting system at bus stops using Wi-Fi probe requests and deep learning (2024)A prediction model of passenger demand using AVL and APC data from a bus fleet (2015)Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground (2010)Travel Time and Transfer Analysis Using Transit Smart Card Data (2010)Towards equitable transit: examining transit accessibility and social need in Toronto, Canada, 1996–2006 (2013)How talkative is your mobile device? (2015)Estimation of Origin and Destination Information from Bluetooth and Wi-Fi Sensing for Transit (2016)iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System (2020)Application of Spatial Data and Analysis for Bus Transportation Optimization and Planning: A State-of-the-Art Review (2026)Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)A survey of results on mobile phone datasets analysis (2015)Impact of COVID-19 on the travel and tourism industry (2020)Exploring The Role Of Artificial Intelligence In Enhancing Tourism Education And Training (2025)Urban Transit : Operations, Planning and Economics (2005)Urban Transit: Operations, Planning and Economics (2006)A review of urban computing for mobile phone traces (2013)Portfolio optimization with return prediction using deep learning and machine learning (2020)Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets (2023)Exploring the effects of the built environment on activity duration among older adults: A case study of metro systems in Dalian, China (2025)
this work references cited by second hop

References

  • 2014Measuring Bus Passenger Load by Monitoring Wi-Fi Transmissions from Mobile Devices40 cited
  • 2016Public transport occupancy estimation using WLAN probing38 cited
  • 2016Feasibility of Analyzing Wi-Fi Activity to Estimate Transit Passenger Population17 cited

Cited by

  • 2023The potential of Wi-Fi data to estimate bus passenger mobility15 cited
  • 2022Utilizing Wi-Fi Sensing and an Optimized Radius Algorithm to Count Passengers with Transfers to Enhance Bus Transit O-D Matrix9 cited
  • 2024A Machine Learning Approach to Estimate Public Transport Ridership Using Wi-Fi Data8 cited
  • 2019The practicability of predicting the number of bus passengers by monitoring wi-fi signal from mobile devices with the polynomial regression4 cited
  • 2022UAI-FI: using artificial intelligence for automatic passenger counting through Wi-Fi and GPS data4 cited
  • 2023Bayesian Estimation of Passenger Boardings at Bus Stops Using Wi-Fi Probe Requests4 cited

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