A smart disaster management system for future cities

Alazawi, Zubaida; Alani, Omar; Abdljabar, Mohmmad B.; Altowaijri, Saleh M.; Mehmood, Rashid

doi:10.1145/2633661.2633670

Cited by 79 publications

(36 citation statements)

References 8 publications

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“…Alazawi et al discussed the importance of building frameworks for smart city-based disaster management context. Other notable studies in this domain have also proposed a framework for implementing intelligent transportation systems including vehicular ad hoc networks (VANETs) and cloud computing technologies [10], and smartphonebased mobile disaster management system for optimal geographical routing for volunteers and resources under limitations of time [34]. However, to the best of the author's knowledge, quantitative studies utilizing machine learning to investigate the potential of the visual content of the captured big data in smart cities effective disaster search and response were lacking.…”

Section: Disaster Management In Smart Citiesmentioning

confidence: 99%

“…This combined with the adoption of advanced data analytics will aid effective decision making in disaster situations. However, the limited amount of studies in this domain such as those by Asimakopoulou and Bessis [6] or Alazawi et al [10] highlight the lack of focus on utilizing the capabilities of data analytics, holistically, for disaster management as a 'smart service' in a smart city. In response to this gap in the extant literature, our current study attempts to examine the effectiveness of a specialized ML technique for disaster management in smart cities.…”

Section: Introductionmentioning

confidence: 99%

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Application of Image Analytics for Disaster Response in Smart Cities

Chaudhuri¹,

Bose²

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Post-disaster, city planners need to effectively plan response activities and assign rescue teams to specific disaster zones quickly. We address the problem of lack of accurate information of the disaster zones and existence of human survivors in debris using image analytics from smart city data. Innovative usage of smart city infrastructure is proposed as a potential solution to this issue. We collected images from earthquake-hit smart urban environments and implemented a CNN model for classification of these images to identify human body parts out of the debris. TensorFlow backend (using Keras) was utilized for this classification. We were able to achieve 83.2% accuracy from our model. The novel application of image data from smart city infrastructure and the resultant findings from our model has significant implications for effective disaster response operations, especially in smart cities.

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Section: Disaster Management In Smart Citiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of Image Analytics for Disaster Response in Smart Cities

Chaudhuri¹,

Bose²

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…With the intent of presenting the role of today's technologies in this field in (Alazawi et al, 2014) it is stated that this type of systems is growing at fast pace. In contrast to (Benkhelifa et al, 2014), this work focuses on Vehicular Ad hoc Networks (VANETs), sensors, social networks and Car-to-X, where X can either be infrastructures or other cars.…”

Section: Related Workmentioning

confidence: 99%

“…This may create problems for collaborative ventures between city governments and businesses, and even with other public sector agencies, as well as with voluntary and community organisations. According to (Alazawi et al, 2014) a smart city depends on the provision of information, communication technologies and services to the population via web based services. However, the concept of smart city can, many times, be mistaken.…”

Section: Introductionmentioning

confidence: 99%

Smart Cities - An Architectural Approach

Duarte

Oliveira

Bernardino

2015

Proceedings of the 17th International Conference on Enterprise Information Systems

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Smart cities are usually defined as modern cities with smooth information processes, facilitation mechanisms for creativity and innovativeness, and smart and sustainable solutions promoted through service platforms. With the objective of improving citizen's quality of life and quickly and efficiently make informed decisions, authorities try to monitor all information of city systems. Smart cities provide the integration of all systems in the city via a centralized command centre, which provides a holistic view of it. As smart cities emerge, old systems already in place are trying to evolve to become smarter, although these systems have many specific needs that need to be attended. With the intent to suit the needs of specific systems the focus of this work is to gather viable information that leads to analyse and, present solutions to address their current shortcomings. In order to understand the most scalable, adaptable and interoperable architecture for the problem, existing architectures will be analysed as well as the algorithms that make them work. To this end, we propose a new architecture to smart cities.

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“…A few technologies and platforms, which are well positioned candidates to serve as the next generation disaster recovery systems may include [13,14,15]:…”

mentioning

confidence: 99%

A mobile health network disaster management system

Adibi

2015

2015 Seventh International Conference on Ubiquitous and Future Networks

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A common occurrence in almost all full-scale natural disasters is the rapid destruction of the telecommunication infrastructure as the inevitable unfolds, which tends to halt the necessary communications between the humanitarian operators and the people in need. In such scenarios, the deployment of wireless networks would provide fast and temporary remedies, however these networks normally do not provide services to the end-users and ordinary people, instead they provide connectivity between groups of end-users administered by a local service provider. From a range of services provided to the end-users by the humanitarian operators, healthcare is by far the top priority. This is considered through the utilization of smartphones in a Mobile Health (mHealth) perspective, which is an emerging concept for monitoring and tracking end-user health conditions. This article considers an mHealth system used in a tsunami-stricken disaster scenario, including a discussion on the most recent advances of Device to Device (D2D) and LTE-Direct technologies.The future of wireless and cellular disaster recovery systems is expected to rely heavily on direct Device-to-Device (D to D) communication, eliminating the need of the functioning telecommunication infrastructure. Reference [11] has identified the following 7 key technology goals for future public disaster recovery systems: LTE-based communication systems, resource sharing mechanisms, hierarchical dispatch-chain, unified voice/data/video communication channels, integrated security, privacy, and reliability, scalability and system reconfiguration, and real-time low-latency communication responses. These goals will be coupled with Wireless Body Area Network (WBAN)

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A smart disaster management system for future cities

Cited by 79 publications

References 8 publications

Application of Image Analytics for Disaster Response in Smart Cities

Application of Image Analytics for Disaster Response in Smart Cities

Smart Cities - An Architectural Approach

A mobile health network disaster management system

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