A model-driven framework for developing multi-agent systems in emergency response environments

HoseinDoost, Samaneh; Adamzadeh, Tahereh; Zamani, Bahman; Fatemi, Afsaneh

doi:10.1007/s10270-017-0627-4

Cited by 14 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For instance, fire emergencies such as fire in a building or urban fire emergencies, and day-to-day emergencies that can be traffic accidents, and industrial accidents. Natural and human-made disasters [10][11][12][13][14]17,36,42,63,64,72,73,80,81,83,84,[89][90][91][92]98,99] The articles where the authors contemplate both types of disasters. It means that the presented solutions in these articles work in both types of disasters.…”

Section: Disasters Descriptionmentioning

confidence: 99%

“…Lwin et al [64], Puspita et al [75], Gokaraju et al [76], Fontes et al [80], and Peng et al [83] designed GISs that can help to improve the efficiency and decision-making of emergency response in various scenarios. Preinerstorfer et al [63], Ahmed et al [71], Valecha et al [97], HoseinDoost et al [98], and Agrawal et al [99] developed ISs for emergency response in various scenarios, mainly focusing on land SAR. Ghasemi et al [81], Mouradian et al [88], and Ejaz et al [91] focused on IoT applications and their characteristics for disaster management.…”

Section: Disasters Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

The Use of Decision Support in Search and Rescue: A Systematic Literature Review

Nasar

Torres

Gundersen

et al. 2023

IJGI

View full text Add to dashboard Cite

Whenever natural and human-made disasters strike, the proper response of the concerned authorities often relies on search and rescue services. Search and rescue services are complex multidisciplinary processes that involve several degrees of interdependent assignments. To handle such complexity, decision support systems are used for decision-making and execution of plans within search and rescue operations. Advances in data management solutions and artificial intelligence technologies have provided better opportunities to make more efficient and effective decisions that can lead to improved search and rescue operations. This paper provides findings from a bibliometric mapping and a systematic literature review performed to: (1) identify existing search and rescue processes that use decision support systems, data management solutions, and artificial intelligence technologies; (2) do a comprehensive analysis of existing solutions in terms of their research contributions to the investigated domain; and (3) investigate the potential for knowledge transfer between application areas. The main findings of this review are that non-conventional data management solutions are commonly used in land rescue operations and that geographical information systems have been integrated with various machine learning approaches for land rescue. However, there is a gap in the existing research on search and rescue decision support at sea, which can motivate future studies within this specific application area.

show abstract

Section: Disasters Descriptionmentioning

confidence: 99%

Section: Disasters Descriptionmentioning

confidence: 99%

The Use of Decision Support in Search and Rescue: A Systematic Literature Review

Nasar

Torres

Gundersen

et al. 2023

IJGI

View full text Add to dashboard Cite

show abstract

“…Taga et al [23] have proposed an evacuation support system using an ad hoc mobile network that enables information sharing when communication infrastructure is not available. HoseinDoost et al [24] have described a model-driven framework for developing multiagent systems in emergency response environments, which contains three steps of domain-specific modeling language, a transformation program and a platform for executing the generated code.…”

Section: A Evacuation Guidancementioning

confidence: 99%

Large-Scale Evacuation Shelter Selection Method Through Iterations of Pedestrian Simulations With Dynamic Congestion Reproduction

et al. 2022

View full text Add to dashboard Cite

It is necessary to optimize evacuation guidance to shelters in short evacuation time. The state-of-theart method based on an idea of combinatorial optimization problems related to evacuees' locations and the capacities of nearby shelters has been developed, while it cannot mitigate the effect of congestion on roads/streets after evacuation starts. In this study, to cover this problem, we develop a new method that utilizes simulations for estimating the effect of congestion on roads/streets during evacuation and reassigning shelters to evacuees based on the simulation results. By iterating this step, our method derives the congestion-aware solutions for shelter selection that can realize more smooth evacuation. To evaluate our method, we conducted multi-agent simulations assuming a disaster situation in a sightseeing spot. Specifically, we examined a hypothetical case scenario involving the evacuation of 30,000 visitors from the Gion Festival. We compared the proposed method with conventional methods, such as the nearest shelter selection method and our previous method. We found that our proposed method reduced average and total evacuation time and congestion on roads compared to the conventional methods including the nearest shelter selection method and our previous method that only employs combinatorial optimization without estimating congestion. From this result, our idea of simulation-based congestion estimation has an impact of easing congestion during evacuation and preventing overcapacity of shelters at the same time. It shows the possibilities of help in developing congestion-aware evacuation strategies in emergency situations of crowded areas like huge cities or sightseeing spots.

show abstract

“…MAS tabanlı geliştirilmiş modellerin çoğu, birden fazla farklı aracı platformunda uygulanmasına izin vermemektedir [98]. Platform çeşitliliğini arttırmak için, MAS, alana özgü modelleme dillerinin (DSML: domain-specific modeling languages) sözdiziminde ve meta modellerde bulunan dikey dönüşümleri kullanır [99]. Tezel ve Kardas [100]'a göre bunun nedeni, MAS DSML'lerin Platformdan Bağımsız Meta modellerinde (PIMM) bulunan yatay dönüşümlerin inşası yoluyla benzer bir aracı platformda çalıştırılabilen farklı bir MAS DSML'inin model durumlarını etkinleştirmeleridir.…”

Section: Platformların Iş Birliği (Platform Interoperability)unclassified

IoT uygulamalarında çok etmenli sistemlerin (MAS) birlikte çalışabilirliğinin rolü: Akıllı üretim sistemlerindeki son gelişmeler üzerine bir araştırma

Uslu

2022

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

View full text Add to dashboard Cite

Çok Etmenli Sistemler (MAS), Nesnelerin İnterneti (IoT) uygulamaları içerisinde, akıllı nesnelerin etmenler (agent) olarak tasarlanması aracılığı ile birden çok akıllı cihazdan bilgilerin algılamasını, toplamasını, paylaşmasını, pekiştirilmesini ve revize edilmesini mümkün kılmaktadır. Çok etmenli sistemler ve ilgili araçlar, sistemlerin optimizasyonunda kullanılan paradigmalar için önemli değişikliklere katkıda bulunmakla birlikte, MAS hakkındaki mevcut literatür, IoT cihazlarının gelişmiş işbirliğini açıklayan modern dağıtılmış hesaplama yöntemlerini açıklamak için yeterli düzeyde değildir. Bu araştırma, IoT içerisinde yer alan akıllı cihazların, MAS teknolojisi ile birlikte çalışabilirliği hakkında kapsamlı bir araştırma sunmaktadır. Bu kapsamda, önce etmen tabanlı sistemler ve IoT teknolojisi hakkında genel bir bilgilendirilme sunularak, çok etmenli sistemler içerisinde birlikte çalışabilirliğin önemi ve üretim sistemleri özelinde çoklu etmen teknolojisinin, sensör verilerini yakalamadan karar vermeye kadar çeşitli amaçlarla nasıl kullanılabileceğini açıklanmıştır. Çok etmenli sistemlerde birlikte çalışabilirlik için geliştirilen ve üreticiden bağımsız olarak birbirini anlayabilen iki ana dil hakkında bilgilendirme sunulmuştur. MAS'in IoT tabanlı kablosuz sensör ağında (WSN'ler) veri toplama ve entegrasyonu açıklanmıştır. Akıllı üretim sistemlerinin tasarımında, MAS'in geliştirmeye açık alanları ve gelecekteki trendlerinde IoT uygulamasını ele almak, bu makalenin bir diğer katkısı olarak sunulmuştur. Araştırmanın, IoT ve MAS üzeride çalışan araştırmacılar, tasarımcılar ve yöneticiler için bir yol gösterici olması beklenmektedir.

show abstract

A model-driven framework for developing multi-agent systems in emergency response environments

Cited by 14 publications

References 21 publications

The Use of Decision Support in Search and Rescue: A Systematic Literature Review

The Use of Decision Support in Search and Rescue: A Systematic Literature Review

Large-Scale Evacuation Shelter Selection Method Through Iterations of Pedestrian Simulations With Dynamic Congestion Reproduction

IoT uygulamalarında çok etmenli sistemlerin (MAS) birlikte çalışabilirliğinin rolü: Akıllı üretim sistemlerindeki son gelişmeler üzerine bir araştırma

Contact Info

Product

Resources

About