Interconnectedness of Complex Systems of Internet of Things through Social Network Analysis for Disaster Management

Zelenkauskaite, Asta; Bessis, Nik; Sotiriadis, Stelios; Asimakopoulou, Eleana

doi:10.1109/incos.2012.25

Cited by 56 publications

(28 citation statements)

References 21 publications

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“…Such works focus mainly on the study of the collected images. GIS data are too broad and need smart device architecture [8]. GIS information is too growing.…”

Section: Statistical Data Analysismentioning

confidence: 99%

Role of IoT devices in Flood Monitoring System using Social Networking Sites

Goyal*,

Ghanshala,

Sharma

2020

IJITEE

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Each country has a natural disaster, but catastrophe losses can't be avoided. The loss of human life, damage to the environment, infrastructure degradation, etc. Which in turn affects the country's development facing the disaster's wrath? In this analysis, we discuss the various methods available in the literature to reduce the losses in flood-related natural disasters. There are four major steps in the prevention of disaster losses, including preparedness, response, recovery and mitigation. Existing methods that address the above steps and all the current methods have certain limitations and are therefore not all sufficient to minimize losses due to flooding. In order to overcome all the deficiencies in the exit method, we propose an IoT devices based algorithm to get the number of victims and survivors due to flood and reduce the flood losses model using social networking sites.

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“…Such works focus mainly on the study of the collected images. GIS data are too broad and need smart device architecture [8]. GIS information is too growing.…”

Section: Statistical Data Analysismentioning

confidence: 99%

Role of IoT devices in Flood Monitoring System using Social Networking Sites

Goyal*,

Ghanshala,

Sharma

2020

IJITEE

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“…even though it is not absolutely viable to keep away from the incidence of a catastrophe, the effect can honestly be minimized through creating proper techniques of focus of probable catastrophe and its consequences by using growing a system that channels this statistics to the involved government [6]. IoT will play an important role throughout this channeling and transmission of knowledge through the inexperienced use of existing technology [7].Catastrophe management is improbably significant to alive within the case of a catastrophe and can be described as the employer and control of assets and duties for handling with all humanitarian parts of emergencies specifically, awareness, reaction, and healing an honest thanks to reduce the impact of a sudden catastrophe.…”

Section: Need For Disaster Managementmentioning

confidence: 99%

IoT- save the community project

Deepa¹,

Agarwal²,

Uprety³

et al. 2018

IJET

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IoT offers elaborate structures that combine multiple disperse additives towards their synergetic use. The machine suggested within this paper is an answer to track the environment conditions at a selected location while allowing the facts to be seen everywhere around the globe for the propagation of statistics in absence of any current infrastructure. Importance is given on how sensing and communique applications of IoT be utilized successfully in case of catastrophe control. The hardware of the module used for this motive is calculated and elaborated in a detailed way.

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“…In particular, such networks can provide the ability to extract intelligence from a data-set, which leads to a better and more comprehensive understanding of the information related to it. In fact, understanding and assessing the interconnection among data provide useful modelling frameworks which can be applied to risk and decision analysis [25].…”

Section: A Measuring Co-occurrence-based Influencementioning

confidence: 99%

An influence assessment method based on co-occurrence for topologically reduced big data sets

Trovati

Bessis

2015

Soft Comput

Self Cite

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Abstract-The extraction of meaningful, accurate, and relevant information is at the core of Big Data research. Furthermore, the ability to obtain an insight is essential in any decision making process, even though the diverse and complex nature of big datasets raises a multitude of challenges.In this paper, we propose a novel method to address the automated assessment of influence among concepts in big data sets. This is carried out by investigating their mutual cooccurrence, which is determined via topologically reducing the corresponding network. The main motivation is to provide a toolbox to classify and analyse influence properties, which can be used to investigate their dynamical and statistical behaviour, which would potentially lead to a better understanding and prediction of the properties of the system(s) they model.An evaluation was carried out on two real-world data-sets, which were analysed to test the capabilities of our system. The results show the potential of our approach, indicating both accuracy and efficiency.

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Interconnectedness of Complex Systems of Internet of Things through Social Network Analysis for Disaster Management

Cited by 56 publications

References 21 publications

Role of IoT devices in Flood Monitoring System using Social Networking Sites

Role of IoT devices in Flood Monitoring System using Social Networking Sites

IoT- save the community project

An influence assessment method based on co-occurrence for topologically reduced big data sets

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