  Recent advances in Internet of Things (IoT) and the rising of the Internet of
Behavior (IoB) have made it possible to develop real-time improved traveler
assistance tools for mobile phones, assisted by cloud-based machine learning,
and using fog computing in between IoT and the Cloud. Within the
Horizon2020-funded mF2C project an Android app has been developed exploiting
the proximity marketing concept and covers the essential path through the
airport onto the flight, from the least busy security queue through to the time
to walk to gate, gate changes, and other obstacles. It gives chance to
travelers to discover the facilities of the airport, aided by a recommender
system using machine learning, that can make recommendations and offer voucher
according with the traveler's preferences or on similarities to other
travelers. The system provides obvious benefits to the airport planners, not
only people tracking in the shops area, but also aggregated and anonymized
view, like heat maps that can highlight bottlenecks in the infrastructure, or
suggest situations that require intervention, such as emergencies. With the
emerging of the COVID pandemic the tool could be adapted to help in the social
distancing to guarantee safety. The use of the fog-to-cloud platform and the
fulfilling of all centricity and privacy requirements of the IoB give evidence
of the impact of the solution in a smart city environment.
