IoTs (Internet of Things) and DfPL (Device-free Passive Localisation) in a disaster management scenario

Deak, Gabriel; Curran, Kevin; Condell, Joan; Asimakopoulou, Eleana; Bessis, Nik

doi:10.1016/j.simpat.2013.03.005

Cited by 38 publications

(22 citation statements)

References 34 publications

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“…Open MTC [8] is the first platform using IoT for forest fire disaster management. Many IoT based post disaster management were proposed in [9], [10] with advances in hardware, communications technology in contrast to the existing WSN based solutions. IoT as a technology evolved to cater many changing needs and make human life smart.…”

Section: Literature Surveymentioning

confidence: 99%

Data Offloading for Effective Rescue Operations During Fire Disaster Management

Kavitha,

Lalitha,

Latha

et al. 2019

IJEAT

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Disasters such as fire, earthquake and tsunami, etc. often result in precious loss of life as well as pose great economic challenge to developing countries like India. Of late, fires in moving vehicles such as trains and buses have become very common in India leading to loss of life and property. As we cannot predict or control the disaster, we can at least make efforts in minimising loss and some effective rescue operations post disaster. It is very important to perform post disaster analysis of the event to have better rescue operations and also to analyse the reason behind the occurrence of such disaster if possible. So that if it is man-made disaster preventive measures could be prescribed in future. Many Wireless Sensor Networks were proposed in the past for disaster management. But, fire leaves the network disconnected and important data is left unused in the damaged network. So, we propose Internet of Things (IoT) which is a promising technology that can be used to solve some of the problems mentioned above. To date, the application of IoT in post-disaster management is still an unexplored problem. In this paper, we propose data offloading mechanism for effective rescue operations post disaster from damaged network. The network is partially damaged in case of disaster and using fog computing we retrieve data and transfer to cloud for better data analytics. We propose a data flow framework built for effective post-disaster management.

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Section: Literature Surveymentioning

confidence: 99%

Data Offloading for Effective Rescue Operations During Fire Disaster Management

Kavitha,

Lalitha,

Latha

et al. 2019

IJEAT

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“…Deak et al [ 10 ] propose the use of IoT DfPL (Device-free Passive Location), since this enables the users to be located in an environment without the need to have any type of device for disaster management. In their work, the IoT DfPL consists of a WSN DfPL that collects the data.…”

Section: Related Workmentioning

confidence: 99%

How to Improve Fault Tolerance in Disaster Predictions: A Case Study about Flash Floods Using IoT, ML and Real Data

Furquim

Filho

Jalali

et al. 2018

Sensors

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The rise in the number and intensity of natural disasters is a serious problem that affects the whole world. The consequences of these disasters are significantly worse when they occur in urban districts because of the casualties and extent of the damage to goods and property that is caused. Until now feasible methods of dealing with this have included the use of wireless sensor networks (WSNs) for data collection and machine-learning (ML) techniques for forecasting natural disasters. However, there have recently been some promising new innovations in technology which have supplemented the task of monitoring the environment and carrying out the forecasting. One of these schemes involves adopting IP-based (Internet Protocol) sensor networks, by using emerging patterns for IoT. In light of this, in this study, an attempt has been made to set out and describe the results achieved by SENDI (System for dEtecting and forecasting Natural Disasters based on IoT). SENDI is a fault-tolerant system based on IoT, ML and WSN for the detection and forecasting of natural disasters and the issuing of alerts. The system was modeled by means of ns-3 and data collected by a real-world WSN installed in the town of São Carlos - Brazil, which carries out the data collection from rivers in the region. The fault-tolerance is embedded in the system by anticipating the risk of communication breakdowns and the destruction of the nodes during disasters. It operates by adding intelligence to the nodes to carry out the data distribution and forecasting, even in extreme situations. A case study is also included for flash flood forecasting and this makes use of the ns-3 SENDI model and data collected by WSN.

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“…Researchers in [19] and [20] in their work highlighted that the IoT-enabled devices that are used to collect the data can offer a minimal device-to-device communication services if the conventional communication infrastructure is out of service during disaster. Researchers in [21] deployed a DfPL (Device free Passive Localisation) WSN in IoT scenario for disaster management which aiming to build upon technology in order to deliver a robust field-trial ready human detection system for disaster situations Dlodlo had done a study about the potential of using the technologies in making an impact to sustainable environmental monitoring in South Africa [22]. The IoT technologies highlighted covers the area of environmental quality and protection, natural resource management, oceans and coasts management, climate change mitigation and adaptation, biodiversity, conservation and environmental awareness areas.…”

Section: Iot In Disaster Managementmentioning

confidence: 99%