TrialsNet

The use case will aim to improve the protection of people in crowded public spaces. The information provided by the use case will help the authorities to better plan public events and to efficiently react in case abnormal situations occur. Two scenarios will be followed for implementation: i) crowd characterisation in terms of people counting, density, and dynamics of large numbers of persons (flow directions, spread, speed) during outdoor public events and ii) detecting special situations during normal traffic scenarios (e.g., presence of various objects such as cars, trucks, motorcycles, etc. in restricted access areas).

 Several cameras will be installed on poles already available on the premises, along with Wi-Fi Access Points (APs). Video streams and information related to the number of Wi-Fi-enabled devices present in the region under study will be sent (through the 5G communication infrastructure put in place by ORO) to a server located in the 5G Lab facility within the “Gheorghe Asachi” Technical University of Iasi. Specific (AI-oriented) algorithms will run on the server side, aiming at reliably estimating the number, density, and dynamics of large crowds, along with the identification of special events of interest (e.g., cars entering restricted access areas or people falling on the street). Analytics results provided by the algorithms will be transmitted to the relevant stakeholders and made visible through appropriate interfaces.