A smart city run-time planner for multi-site congestion management

The twenty most visited museums in Italy (over the total number of 4.976) attract one third of the entire visitors population. This results into a small number of very famous overcrowded museums (with an average waiting time of two hours) and a myriad of still beautiful but empty museums. In order to reduce the queuing time outside one of those famous museums, we have been asked to produce a mobile application that, based on statistical models, can return a timed reservation to the tourist, so to avoid to spend waiting time in a physical queue. Based on this pre-conditions, this paper presents a smart city run-time planner approach and app that, by taking in input some minimum information (location, congestion, and scheduled timed reservation), recommends near-by museums to visit while waiting the scheduled visit to the busy one. The mobile app has been designed to work in the absence of internet connection. The approach and its implementation is presented, as well as some initial conceptual applications to an explanatory example.