Two Aspects of Managing of the Crowds: physical and virtual

About 80% of the world data come from geo-components, and they can be processed under machine learning. It means that data circulated can be localised. Though being of greater importance in search and rescue of people, for example, the team of scientists and researchers Marina Tavira, Josip Peros and Ivan Reciting from the University of Split, Faculty of Civil Engineering, Architecture and Geodesy at the regular CRISPRO webinar hold on 21.10.2021. The scientists added that GIS-based crisis management could take advantage of social network data validation. They are sourcing the system with data from the crowds and managing it by introducing the Virtual Support teams, widely promoted by the unique NGO VOST Europe presented by the “maker” and developer Jorge Gomes, ahead of the international network.

He added that crowdsourcing had been used, with success in several instances. While many groups continue the purely conceptual discussion about the pros and cons of using crowdsourcing in DRR and crowd management, VOST Europe focuses on the cases of successful data gathering to help decision-makers and citizens (African natural disaster case). Social network information crowding can also enable the direct involvement of citizens in the research and investigation processes. For example, they can be asked to share the photos they have taken at a particular place and time concerning a criminal or disaster-related accident. Furthermore, it can foster the citizens’ participation and make them accountable for the environment and communities. As a result, citizens can feel important and helpful, and it can be considered a “democratic” model for illustrating public engagement in disasters or emergencies.

Volunteered geographical information or VGI and remote sensing technologies are basic for modern data aggregation and rapid filtration through machine learning and big data processing. It is extremely important in the interventions referring to the life and health of persons worldwide. Remote sensing data and volunteered geographical information from non-experts collecting and sharing data can be acknowledged as an essential complementary tool of the traditional situational awareness technologies. It refers to the professional capacities of the rescue and searches intervention teams who challenge the physical obstacles in the area affected by the disaster or public disorder incident/riot/unrest. Social-network-based data aggregation can support rescue and emergency planning, especially in the remote or lesser density populated regions such as the Arctic and Barents see areas, outlined Mr Hannu Rantannen, a security expert of the project. “Improving maritime safety in the Arctic Ocean through Ai and Virtual Control Room”. The Barents Rescue Event is an excellent platform for testing and validating technological solutions, and the upcoming one in the fall of 2023 in Bodo Norway, added Hannu Rantanen.

Another physical aspect of the crowd management interventions refers to the CBRN incidents in public spaces, shopping malls, airports or religious places, added Mr Timo Hellenberg, a security expert.
Geo-referencing and geo-positions shall also move from planning and monitoring to intervention support tools for the first responders. It can be useful for disseminating information through the traditional communication channels used during specific interventions.

Rapid processing and data aggregation can also influence the scenarios at the very moment of the reactions. The most popular forms of public crowd management scenarios were presented by Leonard Leso, a Security Analyst with a long 44 years career in the Carabinieri Corps, the military and police force of Italy. He raised attention to the essentials of crowd management: defining the antagonists and lessons learnt, planning for the public order operations, mobile teams setting, training and procedures for public order that can also be enabled by the alert information as an entry point and gets to any rescue situations. Furthermore, spacial recaptured evaluated images involving citizens and extracting reliable data could support the field interventions.

The teams’ preparation is driven by particular national and regional scenarios of potential risks outlined by Jari Honkanen from the Ministry of Interior of Finland. Further, he referred to the leading principles of the Finnish civil protection driven by the comprehensive approach, integrated preparation for peace-time and war-related emergencies, making all actors responsible for carrying out their functions in all security situations, and stressing the pragmatic public/private cooperation, also supported by the military authorities. The territory of Finland is divided into risk classes. The regression model determines four risk levels, and it is based on the number of inhabitants and buildings. The regression model has been calculated according to real house fires and any prognosis for risk level in a square 1 km x 1 km. While the National Risk Assessment outlines 20 scenarios, the sub-national risk assessments are drafted cross-sectorally to represent the region’s municipalities, authorities, businesses, and working groups. The representatives of the National Rescue Platform do provide insights into their communities and reference groups extensively.