Page 30 - Smart public health emergency management and ICT implementations - A U4SSC deliverable on city platforms

iii. Phase 3: Safety simulation – the disaster-affected area is estimated by multidimensional data
analysis to mitigate the damage from disaster.
iv. Phase 4: Safety management determines the countermeasure activities (e.g., alert signalling)
when a disaster has occurred to mitigate transportation damage.

Figure 4: IoT-based transportation safety management 60

Similar synergies can be considered to exist between the SSC, the SSC platform and all the local
operational sub-systems that are based on utilities (e.g., water, energy, waste etc.) or on typical
services (e.g., health, training etc.) that are affected during a crisis. Accordingly, the following
Figure 6 depicts how an SSC architecture can follow these four phases during a disaster. The local
physical environment and infrastructure are being sensed by the local IoT layer, which triggers
the safety management phases (2, 3 and 4) with the support of the medical and safety teams (soft
infrastructure), enabling information to flow across the entire SSC ecosystem. Phase 1 could include
artificial intelligence (AI) applications to support early warnings for known or unknown hazards.
The existence of IoT and AI influences (Figure 5), which are being transformed to the SSCs (Figure
6 and Figure 7), taking into account the involvement of local stakeholders. More specifically, SSCs
host control centres in most cases, which consist of a local dashboard that monitors IoT collected
and processed data . Pandemic-related graphs can be depicted on this dashboard, while the local
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IoT can communicate with the rest of the information systems that belong to the national public
health system. However, although this architecture is focused on generic safety management in
SSCs, similar processes were not observed during the first wave of the Covid-19 pandemic in
aspiring SSCs.

20 U4SSC: Smart public health emergency management and ICT implementations