Table 1 Challenges in multi-agency response (own table, based on discussions held with stakeholders listed in subsection Identifying stakeholder needs).
From: Towards a digital twin for supporting multi-agency incident management in a smart city
Area | Challenge | Description |
|---|---|---|
Processes | Redundancies in communication | Communication between key responders runs through multiple control centres, hindering efficiency in responding to incidents |
Inefficiencies in information collection | Key responders at a scene cannot see and do not know when other responders will arrive. They obtain this information from the control centre, making it difficult to create a real-time operational picture for all responders | |
Missing joint overview across agencies | Key responders do not have a common view of resources allocated to the incident, making it difficult to assign incident-relevant information across agencies | |
People | Silo working cross agencies | Silo work occurs internally and externally, as different processes and procedures are in place. Due to competing goals, these different processes do not always seem to be compatible right away |
Data | Lack of sharing information | Relevant incident data is not always shared with other agencies, making it challenging to act proactively |
Lack of real-time information | Real-time data, e.g. traffic, weather and flooding information, is not available. First responders on their way to an incident do not know if another road traffic accident has occurred on their route, which may hinder a timely response | |
Data | Heterogeneous data landscape | Multi agencies have various different system providers, making it difficult to ensure interoperability externally with other agencies |
Technology | Lack of third-party software extensions | Existing software is often proprietary, making it challenging to link further third-party software extensions that could be useful for multi-agency response collaboration |
Analysis | Lack of real-time analytics | Data analysis is mainly a historical data evaluation of past events and involves little or no real-time data or does not take predictive analysis into account |