2020
DOI: 10.1007/978-3-030-43795-4_12
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Internet of Things (IoT) and Cloud Computing Enabled Disaster Management

Abstract: Disaster management demands a near real-time information dissemination so that the emergency services can be provided to the right people at the right time. Recent advances in information and communication technologies enable collection of real-time information from various sources. For example, sensors deployed in the fields collect data about the environment. Similarly, social networks like Twitter and Facebook can help to collect data from people in the disaster zone. On one hand, inadequate situation aware… Show more

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Cited by 6 publications
(3 citation statements)
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References 52 publications
(55 reference statements)
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“…• Smart sensor-based real time fire detection: Gathering and monitoring of smart sensors providing real time data as mentioned in Table [1] and sending out the report of the state to a server as soon as there is a detection of fire [10].…”
Section: Internet Of Things Based Real-time Remote Systemmentioning
confidence: 99%
“…• Smart sensor-based real time fire detection: Gathering and monitoring of smart sensors providing real time data as mentioned in Table [1] and sending out the report of the state to a server as soon as there is a detection of fire [10].…”
Section: Internet Of Things Based Real-time Remote Systemmentioning
confidence: 99%
“…In order to capture live data from vehicles in real-world environment the devices which are used in laboratory must be modified to transfer live data to cloud via wireless communication. Technological advancement and emergence of the IoT has provided substantial advantages to address similar challenges in capturing and processing live and heterogeneous data from multiple sensors in several real-world applications such as precision agriculture, smart cities, healthcare, environmental monitoring and so forth [ 13 , 14 , 15 , 16 , 17 , 18 ].…”
Section: Introductionmentioning
confidence: 99%
“…In smart cities' environments, different data sources (e.g., Internet of things, IoT, devices, points of interest, POIs, and geographical information systems) can be used to support different objectives (e.g., improving life quality, providing suggestions to city users and operators, and assisting decision makers by means of predictions, simulations, and plans) [3]. One of the major challenges in this context is dealing with the data ingestion process [1, [4][5][6][7], addressing the import and pre-processing of complex multi-dimensional data (historical and real-time data with their metadata, which can be considered as static and real-time data, respectively). Acquired and derived data are stored to be further accessed and exploited for data analytics, dashboards, and visual analytics views [8].…”
Section: Introductionmentioning
confidence: 99%