Evidence map›Paper›PMID 36003113›Full record

ArticleFrontiers in psychology2022

Situation aware intelligent reasoning during disaster situation in smart cities.

Kiran Saleem, Salwa Muhammad Akhtar, Makia Nazir, Ahmad S Almadhor, Yousaf Bin Zikria, Rana Zeeshan Ahmad, Sung Won Kim

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kiran SaleemDepartment of Software Engineering, University of Lahore, Lahore, Pakistan.
Salwa Muhammad AkhtarDepartment of Software Engineering, University of Lahore, Lahore, Pakistan.
Makia NazirDepartment of Software Engineering, University of Lahore, Lahore, Pakistan.
Ahmad S AlmadhorCollege of Computer and Information Sciences, Jouf University, Sakakah, Saudi Arabia.
Yousaf Bin ZikriaDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan, South Korea.
Rana Zeeshan AhmadInformation Technology Department, University of Sialkot, Sialkot, Pakistan.
Sung Won KimDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigating prior methodologies, it has come to our knowledge that in smart cities, a disaster management system needs an autonomous reasoning mechanism to efficiently enhance the situation awareness of disaster sites and reduce its after-effects. Disasters are unavoidable events that occur at anytime and anywhere. Timely response to hazardous situations can save countless lives. Therefore, this paper introduces a multi-agent system (MAS) with a situation-awareness method utilizing NB-IoT, cyan industrial Internet of things (IIOT), and edge intelligence to have efficient energy, optimistic planning, range flexibility, and handle the situation promptly. We introduce the belief-desire-intention (BDI) reasoning mechanism in a MAS to enhance the ability to have disaster information when an event occurs and perform an intelligent reasoning mechanism to act efficiently in a dynamic environment. Moreover, we illustrate the framework using a case study to determine the working of the proposed system. We develop ontology and a prototype model to demonstrate the scalability of our proposed system.

Indexed as

BDI mechanismdisaster management systemedge intelligenceintelligent decision support systemmulti-agent systemsituation-awarenesssmart cities

Identifiers

PMID36003113
PMCPMC9394515

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.