The European Researchers’ Night (ERN) is a science event open to the public, promoted by the European Commission since 2005, with the aim of celebrating science and bringing it closer to citizens. Framed in the Marie Sklodowska-Curie Actions, the ERN takes place simultaneously in more than 30 countries and 300 cities throughout Europe, on the last Friday of September. ERN’2019, dedicated to the theme “Science in the City”, occurred on the night of September 27 and its central spot in Lisbon was the National Museum of Natural History and Science that, according to ERN’2019 organizers, received 4750 visitors [see teaser and program].
ISTAR-IUL presence was guaranteed by an indoor demonstration of people detection techniques, based on the electromagnetic activity of their mobile devices, developed in the scope of the “Prevent Crowding” research project, coordinated by Fernando Brito e Abreu, researcher at ISTAR-IUL and founder of the Software Systems Engineering group. Its main objective is providing a smart solution for mitigating the pressure felt both by residents and visitors, due to tourism overcrowding in historic neighborhoods, by means of an alternative routing recommendation system for tourists, that mitigates overcrowding trough their dispersion, while promoting the visitation of sustainable points of interest. This project is a partnership with other public and private organizations: CML, JFSMM, GEOTA, APECATE, ISPA and APPA and is being developed in collaboration with two other ISCTE-IUL research centers: IT–IUL and CIES-IUL.
At ISTAR-IUL’s stand in ERN’2019, that was intensively visited all night long, from 6PM to midnight [see photos here], we showed how several of our research threads (Software Defined Radio, Edge Computing, Digital Fabrication, Building Information Models and Gamification) can be combined. It was therefore a good showcase of ISTAR-IUL as a reference research unit in the application of multidisciplinary and trans-disciplinary digital and computing approaches and services to identified problems. It is worth mentioning that the same techniques can be used for applications in outdoor scenarios such as urban waste management, civil protection and emergency management, and indoor ones, such as crowd management for sports venues or understanding museum visitors’ behavior (as shown in the ERN’2019). Our solution distinguishes from other crowding detection approaches by combining trace data from heterogeneous wireless technologies, collected in real-time with off-the-shelf equipment and open source hardware and software.