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Resource Machine Learning for monitoring via WiFi the number of passengers on public vehicles


As part of a project on sustainable mobility involving the city of Ferrara, U-Hopper collaborated with Dedagroup Public Services to tackle the problem related to the automatic passenger counting on public transport vehicles.


For public transport operators and mobility agencies, the number of passengers on board represents a valuable piece of information in order to accurately plan the frequency of the trips and to choose the most suitable type of vehicle to be used.
However, this information is difficult to retrieve. Various solutions are already on the market (for instance based on video cameras or weight sensors), but they all present significant shortcomings in terms of cost and reliability of the estimates (as well as privacy issues).


To cope with this problem, U-Hopper has designed a system, which is easy to deploy, requires a limited investment and is based on a combination of WiFi and advanced Machine Learning techniques...

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Case StudyAnalyticsMachine learningPublic Administration

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