Emergency Evacuation using Wireless Sensor Networks

Itaya, S.; Hasegawa, Jun; Kondo, Yoshihisa; Davis, Peter; Suzuki, Ritsuro; Obana, Sadao

doi:10.1109/lcn.2007.48

Cited by 86 publications

(61 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The dynamic snapshot betweenness is shown in Fig. 4 for the nodes (5,5) and (9,4). Note that the node (5,5) is central to the grid therefore it is being used by shortest paths for most of the times outside the peak time intervals.…”

Section: Experiments 2: Variation Of Dynamic Indicesmentioning

confidence: 99%

See 1 more Smart Citation

Snapshot Centrality Indices in Dynamic FIFO Networks

2011

View full text Add to dashboard Cite

The article introduces the concept of snapshot dynamic indices as centrality measures to analyse how the importance of nodes changes over time in dynamic networks. In particular, the dynamic stress-snapshot and dynamic betweenness snapshot are investigated. We present theoretical results on dynamic shortest paths in firstin first-out dynamic networks, and then introduce some algorithms for computing these indices in the discrete-time case. Finally, we present some experimental results exploring the algorithms' efficiency and illustrating the variation of the dynamic betweenness snapshot index for some sample dynamic networks.

show abstract

Section: Experiments 2: Variation Of Dynamic Indicesmentioning

confidence: 99%

“…In this way the navigation costs of the arcs should increase for a few seconds to reflect the hazard and then they become infinity. This model is introduced by Barnes et al [4] and then generalised by Tabirca et al [22]. Since Fig.…”

Section: Case 3 Variation Of Dynamic Indices For Hazardmentioning

confidence: 99%

Snapshot Centrality Indices in Dynamic FIFO Networks

2011

View full text Add to dashboard Cite

show abstract

“…al. [9] presented a distributed algorithm to direct evacuees to an exit through arbitrarily complex building layouts in emergency situations. They fmd the safest paths for evacuees by taking into account predictions of the relative movements of hazards, i.e., fIres and evacuees.…”

Section: IImentioning

confidence: 99%

A real-time and robust routing protocol for building fire emergency applications using wireless sensor networks

Zeng¹,

Sreenan²,

Sitanayah³

2010

2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)

View full text Add to dashboard Cite

Abstract-Fire monitoring and evacuation for building environments is a novel application for the deployment of wireless sensor networks. In this context, real-time and robust routing is essential to ensure safe and timely building evacuation and the best application of fire fighting resources.Existing routing mechanisms for wireless sensor networks are not well suited for building emergencies, especially as they do not explicitly consider critical and rapidly changing network scenarios. In this paper, a novel real-time and robust routing protocol (RTRR) is presented for building fire emergency applications. It adapts to handle critical emergency scenarios and supports dynamic routing reconfiguration. Simulation results indicate that our protocol satisfies the criteria necessary to support building emergency scenarios.

show abstract

“…As one of the evacuation support systems that are able to detect disasters early and give evacuate guidance, there is a sensor network [1,2]. This system needs to install various senPublished: August 8, 2016 sors (e.g.…”

Section: Introductionmentioning

confidence: 99%

Disaster Detection Using SVDD Group Learning for Emergency Rescue Evacuation Support System

Wada

Higuchi

Komaki

et al. 2016

JASSE

View full text Add to dashboard Cite

Abstract. Many people have got injured and died by sudden disasters such as fires and terrorisms. We have proposed an Emergency Rescue Support System (ERESS) for reducing victims at the time of disaster. ERESS operates under mobile ad-hoc networks (MANET) composed of handheld terminals such as smartphones and tablets. ERESS terminals have disaster detection algorithm and plural sensors such as acceleration, angular velocity, and geomagnetism. ERESS detects the disaster from the behavior analysis of people by the sensors. In this paper, we propose a new disaster detection method by performing the machine learning in the group using a support vector domain description (SVDD). We are able to detect the abnormal behavior of people by using this method. The results of disaster simulation experiments show the validity of the proposed method.

show abstract

Emergency Evacuation using Wireless Sensor Networks

Cited by 86 publications

References 9 publications

Snapshot Centrality Indices in Dynamic FIFO Networks

Snapshot Centrality Indices in Dynamic FIFO Networks

A real-time and robust routing protocol for building fire emergency applications using wireless sensor networks

Disaster Detection Using SVDD Group Learning for Emergency Rescue Evacuation Support System

Contact Info

Product

Resources

About