Development of simulation scenarios to evaluate the effectiveness of smart city systems during military conflicts – title of paper
Shortly (3-4 sentences): Importance of simulations: An explanation of why simulations are important for investigating crisis situations and making informed decisions.
1. Basic elements of simulation scenarios. Description of smart city systems: Selection of the key technologies and systems to be included in the simulations (e.g. IoT, AI, communication networks) and Key Performance Indicators (KPIs): Defining performance evaluation metrics (e.g. time to response, accuracy of warnings, number of lives saved).
2. Simulation scenarios
Scenario 1: Attack on critical infrastructure
Description: Simulation of an attack on important infrastructure objects such as power plants, water supply systems, transport networks.
Objectives: Evaluation of the effectiveness of early warning systems and coordination of emergency teams.
Key indicators: Time to detect the attack, response time of emergency teams, minimization of damage.
Scenario 2: Mass evacuation
Description: Simulation of a mass evacuation of a population as a result of an immediate threat (eg bombing, chemical attack).
Objectives: Evaluation of the effectiveness of communication networks and transport systems for rapid and safe evacuation.
Key indicators: Evacuation time, capacity of transport vehicles, safety of evacuees.
Scenario 3: Cyber attack on information systems
Description: Simulation of a cyber attack targeting the city’s information systems (eg hacking of traffic management networks or energy supply).
Objectives: Assess the resilience and cyber security of urban systems.
Key indicators: Time to detect the cyber attack, effectiveness of protective measures, restoration of normal operation.
Scenario 4: Humanitarian crisis and resource allocation
Description: A simulation of a humanitarian crisis where there is an urgent need to distribute resources such as food, water, medicine.
Objectives: Evaluation of the effectiveness of logistics and resource allocation systems.
Key indicators: Time of delivery of resources, accuracy of distribution, meeting the needs of the population.
3. Methodology of simulations
Selection of a simulation platform: Explanation of the selection of a software platform for running the simulations (eg MATLAB, AnyLogic, Simulink).
Data and Modeling: Description of the required data and modeling process of urban systems and crisis situations.
Validation of simulations: A methodology for validating and testing the accuracy of simulations.
5. Analysis of results
Data processing: Methods for analyzing simulation results and data visualization.
Scenario Comparison: Comparison of the performance of intelligent systems in different simulation scenarios.
Key Findings: Summary of key findings and recommendations for improvements.
6. Conclusion
Summary of Key Findings: A brief summary of the main findings from the simulations conducted.
Practical recommendations: Recommendations for applying the results in practice in real conditions.
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Development of simulation scenarios to evaluate the effectiveness of smart city
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