Evidence map›Paper›PMID 35665301›Full record

ArticleComputational intelligence and neuroscience2022

Cloud-Based IoE Enabled an Urban Flooding Surveillance System.

R Dhaya, Tariq Ahamed Ahanger, G R Asha, Emad A Ahmed, Vikas Tripathi, R Kanthavel, Henry Kwame Atiglah

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

R DhayaDepartment of Computer Science, College of Arts and Science-Sarat Abidha, King Khalid University, Abha, Saudi Arabia.ORCID https://orcid.org/0000-0002-3599-7272
Tariq Ahamed AhangerCollege of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.ORCID https://orcid.org/0000-0002-4525-0738
G R AshaDepartment of Computer Science & Engineering, B.M.S. College of Engineering, Bangalore, Bull Temple Rd, Basavanagudi, Bengaluru, Karnataka-560019, India.
Emad A AhmedDepartment of Computer Science, Faculty of Computers and Information, South Valley University, Qena, Egypt.
Vikas TripathiDepartment of Computer Science & Engineering, Graphic Era Deemed to Be University, Dehradun, Uttarakhand, India.ORCID https://orcid.org/0000-0002-2254-3044
R KanthavelDepartment of Computer Engineering, College of Computer Science, King Khalid University, Abha, Saudi Arabia.ORCID https://orcid.org/0000-0001-5537-2571
Henry Kwame AtiglahDepartment of Electrical & Electronics Engineering, Tamale Technical University, Tamale, Ghana.ORCID https://orcid.org/0000-0001-7879-1779

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A flood is defined as a surplus of water or sludge on parched soil, and a flood has originated through the runoff of water inside the water route from the various water sources like canals, etc. Intense rainfall, deforestation, urbanization, deprived water and sewerage administration, and lack of concentration toward the environment of the hydrological scheme have been the causes of urban flooding. In addition, there is a deficiency in flood assessment due to the impediment in getting data on floods to the control room from the flood-affected area. To diminish the possessions due to flooding, there ought to be an immediate move of captured statistics as of the hectic region en route to the observation room with no further wait for a completely fledged technique in the wireless settings data from the Internet of Things (IoT). The Internet of Everything (IoE) is a concept that extends the Internet of Things. In view of the fact that the wireless nodes are changeable in their environment, those effects lead to unsteadiness and uncertainty in information distribution. Therefore, there is a requirement for flood-predictable region data that may be exaggerated between the source and the control room. In the past, there were a lot of techniques set up and put into practice intended for keeping an eye on the flood spots. However, one of the biggest challenges is to have data sharing without delay and loss of data among source and destination nodes. In addition to that, the video quality also needs to be taken into consideration at the same time in receipt, as it is a tough task to determine and preplan the flood happenings completely from the normal disaster that makes scientific complicatedness more than the information being received in a wireless ad-hoc environment using IoT-based sensors. Considering all the abovementioned reasons, the proposed work comprises of three folded goals, namely, the design of a mobile ad-hoc flooding environment, the development of an urban flood high definition video surveillance system using IoT-based sensors, and experimental work on simulation.

Indexed as

FloodsRainCloud ComputingInternetWaterWater

Identifiers

PMID35665301
PMCPMC9159849

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.