TY - GEN
T1 - An Artificial Intelligence and simulation approach to climate-conflict-migration driven security issues
AU - David, Walter
AU - King-Okoye, Michelle
AU - Mugambwa, Irene
AU - Garmendia-Doval, Beatriz
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - This research aims to present a novel approach, leveraging Artificial Intelligence (AI), and Modelling & Simulation (M&S) technologies to plan and respond to present and future threats to safeguard people, including displaced and marginalized communities, and reduce risks to humanitarian workers. In the framework of the United Nations Humanitarian Networks and Partnerships Weeks (HNPW) conference, Authors have discussed the requirements for smarter responses in addressing climate change, conflict, and migration issues. M&S is used since many years for military Staff training; the convergence of AI and M&S makes such systems affordable also to humanitarian organizations. We have examined how real time big data analysis, intelligence and AI supported testing of contingency plans can be implemented to address operating environments challenges. The Medical Intelligence Platform (MIP) from Expert.ai and the Synergy simulation system from MASA Group have been tested on a North-East Nigeria scenario. The automatic transfer of actionable intelligence would enable real-time situational awareness and decision-making. Predictive analytics, reliable early detection and warning can help in anticipating emergencies before they spread, improving the efficiency of humanitarian responses and operations. AI systems can help to decide and act faster and better by providing outcomes feedback. A digital transformation in the humanitarian sector with the exploitation of data analytics and AI will improve resource allocation and support the shift from reacting to crises to anticipatory action, by acting ahead of predicted hazards to prevent or reduce humanitarian impacts before they fully unfold
AB - This research aims to present a novel approach, leveraging Artificial Intelligence (AI), and Modelling & Simulation (M&S) technologies to plan and respond to present and future threats to safeguard people, including displaced and marginalized communities, and reduce risks to humanitarian workers. In the framework of the United Nations Humanitarian Networks and Partnerships Weeks (HNPW) conference, Authors have discussed the requirements for smarter responses in addressing climate change, conflict, and migration issues. M&S is used since many years for military Staff training; the convergence of AI and M&S makes such systems affordable also to humanitarian organizations. We have examined how real time big data analysis, intelligence and AI supported testing of contingency plans can be implemented to address operating environments challenges. The Medical Intelligence Platform (MIP) from Expert.ai and the Synergy simulation system from MASA Group have been tested on a North-East Nigeria scenario. The automatic transfer of actionable intelligence would enable real-time situational awareness and decision-making. Predictive analytics, reliable early detection and warning can help in anticipating emergencies before they spread, improving the efficiency of humanitarian responses and operations. AI systems can help to decide and act faster and better by providing outcomes feedback. A digital transformation in the humanitarian sector with the exploitation of data analytics and AI will improve resource allocation and support the shift from reacting to crises to anticipatory action, by acting ahead of predicted hazards to prevent or reduce humanitarian impacts before they fully unfold
U2 - 10.1007/978-3-031-26754-3_13
DO - 10.1007/978-3-031-26754-3_13
M3 - Conference contribution
SN - 9783031267536
T3 - Lecture Notes in Networks and Systems
SP - 149
EP - 159
BT - Environmental Protection and Disaster Risks
A2 - Dobrinkova, Nina
A2 - Nikolov, Orlin
PB - Springer
ER -