Vehicular Cloud Computing for Population Evacuation Optimization

Idoudi, Hassan; Ameli, Mostafa; Phu, Cyril Nguyen Van; Zargayouna, Mahdi; Rachedi, Abderrezak

doi:10.1109/aiccsa56895.2022.10017964

Cited by 3 publications

(2 citation statements)

References 38 publications

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“…AI and Machine Learning algorithms excel in their ability to sift through historical data, identifying patterns and trends that might not be immediately apparent to human planners. This capability is crucial in predicting potential challenges in future evacuations, allowing for proactive rather than reactive planning (Idoudi et al, 2023;Alrehaili, 2021;Hosamo et al, 2023). By understanding past events, AI can forecast scenarios that might occur under similar conditions, thereby preparing evacuation teams to handle a wide range of situations effectively.…”

Section: Ai and Machine Learningmentioning

confidence: 99%

Review of advanced emergency evacuation procedures in hospital buildings: comprehensive analysis and insights

Wu,

Nie,

Zeng

et al. 2024

Front. Built Environ.

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This research paper explores the integration of novel technologies in hospital emergency evacuations, particularly in Operating Rooms (ORs) and Emergency Departments (EDs). It examines the application of advanced tools like simulation modeling, Building Information Modeling (BIM), Digital Twin technology, sensor data, and Artificial Intelligence (AI) to improve evacuation strategies in the building. The study extends to in-depth case studies for assessing the practicality of existing protocols, while also highlighting the critical importance of staff training and preparedness. Additionally, it addresses the ethical and psychological impacts of emergencies on patients and healthcare staff, underscoring the need for technology to be complemented with human-centered care. The paper concludes by emphasizing the ongoing necessity for innovative research in enhancing safety and operational resilience in healthcare emergency management.

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Section: Ai and Machine Learningmentioning

confidence: 99%

Review of advanced emergency evacuation procedures in hospital buildings: comprehensive analysis and insights

Wu,

Nie,

Zeng

et al. 2024

Front. Built Environ.

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show abstract

“…However, this work did not consider telecommunication networks. Idoudi et al (2022b) proposed to use telecommunication networks for the DPE problem with a centralized configuration for a synthetic test case. While the results show the effectiveness of using telecommunication, the evolution of the risk was assumed to be static, and only one VANET architecture was considered.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart dynamic evacuation planning and online management using vehicular communication system

Idoudi,

Ameli,

Nguyen Van Phu

et al. 2023

Computer aided Civil Eng

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During disasters, swiftly and efficiently evacuating populations in hazardous situations is crucial to minimize losses. This study proposes a novel framework to address dynamic population evacuation (DPE) problems, which includes planning and online evacuation management phases facilitated by vehicular communication. In the planning phase, a shelter allocation problem (SAP) is solved dynamically for destination choice and a dynamic traffic assignment (DTA) for path choice toward the chosen destinations to obtain an initial evacuation plan. The initial plan is then enhanced by employing a vehicular ad hoc network (VANET) within the vehicular edge computing (VEC) architecture. This enhancement enables communication among evacuees, allowing them to revise their vehicle's route choice and planned destination. These revisions take into account the changing risk and traffic conditions. The proposed online DPE framework is applied to the real evacuation scenario of Mill Valley City, CA. The proposed model is evaluated with different VANET architectures, including vehicular cloud computing (VCC) and VEC. The results show that the VEC framework outperforms other configurations and improves the evacuation process compared to the scenario with an initial plan by more than 30% in network clearance time. Additionally, a performance analysis is carried out for evacuation scenarios with different penetration rates of connected vehicles in VANET.

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Streamlining Disaster Response: A Benchmark Study on Population Evacuation Planning with Telecommunication Network

Idoudi,

Ameli,

Van Phu

et al. 2023

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)

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Vehicular Cloud Computing for Population Evacuation Optimization

Cited by 3 publications

References 38 publications

Review of advanced emergency evacuation procedures in hospital buildings: comprehensive analysis and insights

Review of advanced emergency evacuation procedures in hospital buildings: comprehensive analysis and insights

Smart dynamic evacuation planning and online management using vehicular communication system

Streamlining Disaster Response: A Benchmark Study on Population Evacuation Planning with Telecommunication Network

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