Crowd Monitoring in Smart Destinations Based on GDPR-Ready Opportunistic RF Scanning and Classification of WiFi Devices to Identify and Classify Visitors’ Origins

Crowd monitoring was an essential measure to deal with over-tourism problems in urban destinations the pre-COVID era. It will play a crucial role pandemic scenario when restarting tourism and making safer. Notably, Destination Management Organisation (DMO) of smart destination needs deploy technological layer for crowd that allows data gathering order count visitors distinguish them from residents. The correct identification versus residents by DMO, while privacy rights (e.g., Regulation EU 2016/679, also known as GDPR) are ensured, is ongoing problem has not been fully solved. In this paper, we describe novel approach processing (i) massive scanning WiFi access points find SSIDs (Service Set Identifier), well (ii) exposed Preferred Network List (PNL) containing which WiFi-enabled mobile devices likely connect. These enable us provide number at given point interest destination. A pilot study conducted city Alcoi (Spain), comparing our provided manually filled surveys Tourist Info office, average accuracy 83%, thus showing feasibility policy enrich information system