A distributed architecture for real-time evacuation guidance in large smart buildings

In this paper, we consider the route coordination problem in emergency evacuation of large smart buildings. The building evacuation time is crucial in saving lives in emergency situations caused by imminent natural or man-made threats and disasters. Conventional approaches to evacuation route coordination are static and predefined. They rely on evacuation plans present only at a limited number of building locations and possibly a trained evacuation personnel to resolve unexpected contingencies. Smart buildings today are equipped with sensory infrastructure that can be used for an autonomous situation-aware evacuation guidance optimized in real time. A system providing such a guidance can help in avoiding additional evacuation casualties due to the flaws of the conventional evacuation approaches. Such a system should be robust and scalable to dynamically adapt to the number of evacuees and the size and safety conditions of a building. In this respect, we propose a distributed route recommender architecture for situation-aware evacuation guidance in smart buildings and describe its key modules in detail. We give an example of its functioning dynamics on a use case.

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IoT-based real time intelligent routing for emergent crowd evacuation

Library Hi Tech ◽

10.1108/lht-11-2017-0251 ◽

2019 ◽

Vol 37 (3) ◽

pp. 604-624

Author(s):

Yanlan Mei ◽

Ping Gui ◽

Xianfeng Luo ◽

Benbu Liang ◽

Liuliu Fu ◽

...

Keyword(s):

Decision Making ◽

Real Time ◽

Programming Model ◽

Emergency Evacuation ◽

Guidance System ◽

Programming Approach ◽

Metro Station ◽

Content Type ◽

Crowd Evacuation ◽

Evacuation Route

Purpose The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station. Design/methodology/approach The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced. Findings The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation. Originality/value The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

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Simulation-Based Emergency Evacuation System for Ocean City, Maryland, during Hurricanes

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198105192200118 ◽

2005 ◽

Vol 1922 (1) ◽

pp. 138-148 ◽

Cited By ~ 9

Author(s):

Nan Zou ◽

Shu-Ta Yeh ◽

Gang-Len Chang ◽

Alvin Marquess ◽

Michael Zezeski

Keyword(s):

Real Time ◽

Emergency Evacuation ◽

Evacuation Plans ◽

Time Operation ◽

Simulation Based ◽

Real Time Operation ◽

Ocean City ◽

Optimization And Simulation ◽

Operational Constraints ◽

Model Features

This paper presents a simulation-based system for Ocean City, Maryland, evacuation during hurricanes. The proposed model features integration of optimization and simulation that allows potential users to revise the optimized plan for both planning and real-time operations. Since it is difficult to capture all network operational constraints and driver responses fully with mathematical formulations, six evacuation plans for Ocean City were investigated. Each was optimized initially with the optimization module and then revised on the basis of the results of simulation evaluation. To address potential incidents during the evacuation, the study presents a real-time operation plan with a developed system that allows the responsible operators to concurrently evaluate all candidate responsive strategies and to track the performance over time of the implemented strategy.

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Tsunami evacuation times and routes to safe zones: a GIS-based approach to tsunami evacuation planning on the island of Stromboli, Italy

Journal of Applied Volcanology ◽

10.1186/s13617-021-00104-9 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Emmie M. Bonilauri ◽

Andrew J. L. Harris ◽

Julie Morin ◽

Maurizio Ripepe ◽

Domenico Mangione ◽

...

Keyword(s):

High Risk ◽

Emergency Evacuation ◽

Coastal Zones ◽

Risk Zone ◽

Building Evacuation ◽

Mapping Tool ◽

Evacuation Plans ◽

High Level ◽

Initial Interviews ◽

Safe Zones

AbstractWhile a landslide at the volcanic island of Stromboli (Aeolian Islands, Italy) in December 2002 created a tsunami with a run-up of 10.9 m, two paroxysmal eruptions in the summer of 2019 caused a tsunami with an amplitude of 40 to 20 cm. All three events required rapid, spontaneous emergency evacuations of the beach zone as the time between tsunami generation and impact is around 4 min. These conditions thus require a special consideration of the issue of evacuation capabilities on the island in the event of a volcanogenic tsunami. The purpose of this paper is thus to (i) determine pedestrian evacuation times from high-risk coastal areas to safe zones, (ii) to assess building evacuation ease, and (iii) determine emergency evacuation plans (for buildings and coastal zones). For this purpose, we created a GIS-based risk analysis/mapping tool that also allowed macroscopic evacuation modelling. In our case, the high-risk zone to be evacuated involves an area extending to 10 m a.s.l. and involving 123 individual buildings over an area of 0.18 km2. The results show that 33% of the buildings can be evacuated in 4 min, and that a 10-min warning time is required for a complete and well-distributed evacuation whereby the population is evenly distributed between all evacuation exits to avoid the potential for congestion. Initial interviews of residents in the at-risk zone reveal a high level of awareness and a desire for personalized evacuation scenarios.

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IoT in Action: Design and Implementation of a Building Evacuation Service

Journal of Computer Networks and Communications ◽

10.1155/2017/8595404 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 5

Author(s):

Selahattin Gokceli ◽

Nikolay Zhmurov ◽

Gunes Karabulut Kurt ◽

Berna Ors

Keyword(s):

Low Cost ◽

Real Life ◽

Emergency Evacuation ◽

Building Evacuation ◽

Smart Systems ◽

Emergency Situations ◽

Automation Systems ◽

Effective Performance ◽

And Control ◽

Central Management

With the development of sensor technologies, various application areas have emerged. The usage of these technologies and exploitation of recent improvements have clear benefits on building applications. Such use-cases can improve smart functions of buildings and can increase the end-user comfort. As a similar notion, building automation systems (BAS) are smart systems that target to provide automated management of various control services and to improve resource usage efficiency. However, buildings generally contain hardware and control services from a diverse set of characteristics. The automated and central management of such functions can be challenging. In order to overcome such issues, an Emergency Evacuation Service is proposed for BAS, where requirements of such central management model are analyzed and model content and subservice definitions are prepared. A crucial scenario, which could be a necessity for future BAS, is defined and an approach for evacuation of people in the buildings at emergency situations is proposed. For real-life scenarios, the Evacuation Service is implemented by using a low-cost design, which is appropriate for Internet of Things (IoT) based BAS applications. As demonstrated, the proposed service model can provide effective performance in real-life deployments.

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Accuracy analysis of BLE beacon-based localization in smart buildings

Journal of Ambient Intelligence and Smart Environments ◽

10.3233/ais-210607 ◽

2021 ◽

pp. 1-20

Author(s):

Rosen Ivanov

Keyword(s):

Use Case ◽

Accuracy Analysis ◽

Localization Algorithm ◽

Computing Power ◽

Smart Buildings ◽

Localization Accuracy ◽

Positioning Systems ◽

Deployment Strategy ◽

Accurate Localization ◽

Localization Algorithms

The majority of services that deliver personalized content in smart buildings require accurate localization of their clients. This article presents an analysis of the localization accuracy using Bluetooth Low Energy (BLE) beacons. The aim is to present an approach to create accurate Indoor Positioning Systems (IPS) using algorithms that can be implemented in real time on platforms with low computing power. Parameters on which the localization accuracy mostly depends are analyzed: localization algorithm, beacons’ density, deployment strategy, and noise in the BLE channels. An adaptive algorithm for pre-processing the signals from the beacons is proposed, which aims to reduce noise in beacon’s data and to capture visitor’s dynamics. The accuracy of five range-based localization algorithms in different use case scenarios is analyzed. Three of these algorithms are specially designed to be less sensitive to noise in radio channels and require little computing power. Experiments conducted in a simulated and real environment show that using proposed algorithms the localization accuracy less than 1 m can be obtained.

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