Location-Based Crowdsensing Technologies for Planning of Public Transport and other Smart City Solutions

Abstract

Our research deals with creating a suitable and sufficiently reliable methodology to use for evaluating the movement of passengers in public transport or pedestrians. The goal is to design crowds ensing-based methods that provide a quick alternative to large-scale evaluations. It is the settings, the number of installed elements, parameters, and possibly other attributes enabling an increase in quality and reliability in real city conditions. The methodology must comply with GDPR. We also deal with the possibility of evaluating the behavior of people in case of restrictions due to disease spreading (nowadays, for example, COVID19). Our goal is to find methods using wireless technology and their generally little-described features for evaluating the movement of people. The usability of these technologies extends to some branches of logistics or organizations of larger cultural or sporting events.