An Architecture for Fog Computing Enabled Emergency Response and Disaster Management System (ERDMS)

Dar, Bilal Khalid; Shah, M. Ali; Shahid, Huniya; Fizzah, Fizzah; Amjad, Zunaira

doi:10.23919/iconac.2018.8749064

Cited by 9 publications

(9 citation statements)

References 21 publications

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“…Natural disasters [7,39,40,59,60,69,71,[75][76][77][78]82,87,88,96] The articles where the category encompasses disasters caused by nature. e.g., floods, hurricanes, earthquakes, avalanches, and bushfires.…”

Section: Disasters Descriptionmentioning

confidence: 99%

“…e.g., floods, hurricanes, earthquakes, avalanches, and bushfires. Human-made disasters [15,38,46,61,62,[65][66][67]69,70,74,85,86,[93][94][95]97] The articles in which the category of disaster involves the calamities caused by mankind. 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.…”

Section: Disasters Descriptionmentioning

confidence: 99%

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

Nasar

Torres

Gundersen

et al. 2023

IJGI

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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.

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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

“…Moreover, the newest IoT networks appear as a new architecture to coordinate natural disasters. In the works [17,18], the authors propose a new system based on an IoT-dedicated network architecture. All these works will help first responder performances in front of disaster management, but the network required is vulnerable versus a natural disaster as it can be destroyed.…”

Section: Current Research On Disaster Recoverymentioning

confidence: 99%

Heterogeneous wireless IoT architecture for natural disaster monitorization

Porte

Briones

Maso

et al. 2020

J Wireless Com Network

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A heterogeneous sensor network offers an extremely effective means of communicating with the international community, first responders, and humanitarian assistance agencies as long as affected populations have access to the Internet during disasters. When communication networks fail in an emergency situation, a challenge emerges when emergency services try to communicate with each other. In such situations, field data can be collected from nearby sensors deploying a wireless sensor network and a delay-tolerant network over the region to monitor. When data has to be sent to the operations center without any telecommunication infrastructure available, HF, satellite, and high-altitude platforms are the unique options, being HF with Near Vertical Incidence Skywave the most cost-effective and easy-to-install solution. Sensed data in disaster situations could serve a wide range of interests and needs (scientific, technical, and operational information for decision-makers). The proposed monitorization architecture addresses the communication with the public during emergencies using movable and deployable resource unit technologies for sensing, exchanging, and distributing information for humanitarian organizations. The challenge is to show how sensed data and information management contribute to a more effective and timely response to improve the quality of life of the affected populations. Our proposal was tested under real emergency conditions in Europe and Antarctica.

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“…It also overcomes a data center failure bears with it. Dar et al (2018a) has presented an automated accident detection and response system which makes use of fog computing to decrease response time. System evaluation by iFogSim toolkit is introduced in (Dar et al, 2019;2018b).…”

Section: A Fog Computingmentioning

confidence: 99%

IoT-Fog based Smart-Building Security System Design and Performance Evaluation

Medhat

Elshafey

Ali

2020

Journal of Computer Science

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This paper aims to develop a smart building-security system utilizing fog technology. Fog computing is an innovative solution to reduce latency and network congestion, in which the cloud is extended to the edge of the network. The proposed system can detect an intruder, fire and water leakage. It is implemented using Raspberry Pi, Arduino, Pi-camera and different sensors. The sensors are installed on Arduino and Pi-camera is mounted on Raspberry Pi. The Raspberry Pi is used as a fog node to fit the time-sensitive nature of the system. The performance was evaluated through the iFogSim toolkit. Fog reduces 33.26 and 46.8% average latency and sensor delay as compared to the cloud. Also, the value of the network usage decreases by 71% in the case of fog-based even with increased network load. Finally, the iFogSim was evaluated by measuring the simulation time, which gave acceptable results of about 8.5 sec.

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An Architecture for Fog Computing Enabled Emergency Response and Disaster Management System (ERDMS)

Cited by 9 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

Heterogeneous wireless IoT architecture for natural disaster monitorization

IoT-Fog based Smart-Building Security System Design and Performance Evaluation

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