Assessment of Applicability of Wi-Fi Analytics in Studies of Urban Public Transport Passenger Flow (Moscow Case Study)

The advantages and disadvantages of existing tools for calculating passenger flow are shown using the example of the city of Moscow.
The objective of the research was to assess possibilities of using Wi-Fi data as a tool for analysing passenger flow. The authors used two types of Wi-Fi scanners and a tool they developed to analyse the collected data. The primary results of the study demonstrate the possibility of practical application of Wi-Fi data to analyse passenger flow.
The described empirical studies, particularly data received from the portable Wi-Fi scanner, have shown that more than 20% of mobile devices in urban public transport and metro are used with Wi-Fi enabled, which is clearly not enough to get results necessary for comprehensive and detailed analysis of passenger flows. Nevertheless, the accumulating data allow to get possibility to forecast general passenger flow.
A portable Wi-Fi scanner does not provide an opportunity to extensively capture a large area of the surveyed territory in real time (stops of urban public transport, locations where passengers enter the metro, etc.). Stationary Wi-Fi scanners could increase the amount of data and, accordingly, significantly adjust the results obtained. This enhancement could also be achieved through expansion of adoption of the tool of studying passenger flow to urban railways, i.e., in case of Moscow, to Moscow Central Circle and Moscow Central Diameters, as those routes provide Wi-Fi access at stations and in coaches.
Data collected from Wi-Fi scanners can be an additional tool to other data sources, such as validation, automatic systems of passenger flow monitoring, and data obtained from cellular operators. For this reason, the further research in the field of Wi-Fi analytics along with development of technology in the field of existing data sources of passenger flow monitoring may result in better calculation of passenger flow.

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