Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation

State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and guidance are only apparent at the end of the evacuation process and cannot then be remedied. Previous research shows that the performance of routing algorithms for evacuation purposes are sensitive to the initial distribution of evacuees, the occupancy levels, the type of disaster and its as well its locations. Thus an algorithm that performs well in one scenario may achieve bad results in another scenario. This problem is especially serious in heuristic-based routing algorithms for evacuees where results are affected by the choice of certain parameters. Therefore, this paper proposes a simulation-based evacuee routing algorithm that optimises evacuation by making use of the high computational power of cloud servers. Rather than guiding evacuees with a predetermined routing algorithm, a robust Cognitive Packet Network based algorithm is first evaluated via a cloud-based simulator in a faster-than-real-time manner, and any "simulated casualties" are then re-routed using a variant of Dijkstra's algorithm to obtain new safe paths for them to exits. This approach can be iterated as long as corrective action is still possible.Comment: Submitted to PerNEM'15 for revie

Context-based multi-agent recommender system, supported on IoT, for guiding the occupants of a building in case of a fire

The evacuation of buildings in case of fire is a sensitive issue for civil society that also motivates the academic community to develop and study solutions to improve the efficiency of evacuating these spaces. The study of human behavior in fire emergencies has been one of the areas that have deserved the attention of researchers. However, this modeling of human behavior is difficult and complex because it depends on factors that are difficult to know and that vary from country to country. In this paper, a paradigm shift is proposed which, instead of focusing on modeling the behavior of occupants, focuses on conditioning this behavior by providing real-time information on the most efficient evacuation routes. Making this information available to occupants is possible with a solution that takes advantage of the growing use of the IoT (Internet of Things) in buildings to help occupants adapt to the environment. Supported by the IoT, multi-agent recommender systems can help users to adapt to the environment and provide the occupants with the most efficient evacuation routes. This paradigm shift is achieved through a context-based multi-agent recommender system based on contextual data obtained from IoT devices, which recommends the most efficient evacuation routes at any given time. The obtained results suggest that the proposed solution can improve the efficiency of evacuating buildings in the event of a fire; for a scenario with two hundred people following the system recommendations, the time they take to reach a safe place decreases by 17.7%.info:eu-repo/semantics/publishedVersio

Development in building fire detection and evacuation system-a comprehensive review

Fire is both beneficial to man and his environment as well as destructive and deadly among all the natural disasters. A fire Accident occurs very rarely, but once it crops up its consequences will be devastating. The early detection of fire will help to avoid further consequences and saves the life of people. During the fire accidents, it is also important to guide people within the building to exit safely. Because of this, the paper gives a review of literature related to recent advancements in building fire detection and emergency evacuation system. It is intended to provide details about fire simulation tools with features, suitable hardware, communication methods, and effective user interface

Multi-storey residential buildings and occupant’s behaviour during fire evacuation in the UK: Factors relevant to the development of evacuation strategies

Purpose – The paper aims to investigate human behaviour during fire evacuations in multistorey residential buildings through a focus on the challenges and obstacles that occupants face. Any variations in response behaviours that are relevant to the evacuation strategies/plans in the UK context of occupancy typical of multi-storey buildings in large cities. Design/methodology/approach – A literature review was conducted to identify the factors occupants face and also the decision-making of occupants regarding methods of egress. A mixed research method was adopted using interviews and a questionnaire survey. The findings from the interviews and survey are benchmarked against the information gathered from the literature review. Findings – The paper identifies various challenges that occupants face when evacuating a multi-storey residential building. In terms of the decision-making process, the research results evidence that occupants could be given more information on the evacuation procedures within their specific building. The paper also finds that occupants remain reluctant to use a lift during evacuation in fire event, irrespective of any signage clearly stating that is appropriate to do so in the context of modern lift technology. Originality/Value – This paper contributes to the body of knowledge available on the evacuation of multi-storey buildings located in large cities within the UK, outlining potential areas for future research, focused on providing an insight of the behavioural decisions made by the occupants make when evacuating a building in the event of a fire

Fog Computing Architecture for Indoor Disaster Management

Most people spend their time indoors. Indoors have a higher complexity than outdoors. Moreover, today's building structures are increasingly sophisticated and complex, which can create problems when a disaster occurs in the room. Fire is one of the disasters that often occurs in a building. For that, we need disaster management that can minimize the risk of casualties. Disaster management with cloud computing has been extensively investigated in other studies. Traditional ways of centralizing data in the cloud are almost scalable as they cannot cater to many latency-critical IoT applications, and this results in too high network traffic when the number of objects and services increased. It will be especially problematic when in a disaster that requires a quick response. The Fog infrastructure is the beginning of the answer to such problems. This research started with an analysis of literature and hot topics related to fog computing and indoor disasters, which later became the basis for creating a fog computing-based architecture for indoor disasters. In this research, fog computing is used as the backbone in disaster management architecture in buildings. MQTT is used as a messaging protocol with the advantages of simplicity and speed. This research proposes a disaster architecture for indoor disasters, mainly fire disasters

Context-aware information in mobile devices

This paper describes a novel approach for indoor location and integration of other services in a university campus using Bluetooth Low Energy (BLE) devices. These BLE devices broadcast a Bluetooth signal in a limited and configured range/area, thus functioning as beacons that provide useful context-aware information to nearby devices operating with custom applications. Such applications can interpret the received signals as location and provide a range of useful services to the end user (students, events attendees), namely, indoor location and navigation or personalized complex workflows that require the interaction of the end user with multiple services within the university campus.info:eu-repo/semantics/acceptedVersio

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Localization, Visualization And Evacuation Guidance System In Emergency Situations

Urban search and rescue is needed for a variety of emergencies or disasters, including tornadoes, floods, dam failures, technological accidents, and terrorist activities. The efficiency to save people is becoming very important. With the development of the technology, people are trying to find a better way to help people get out of the dangerous places as soon as possible. DIORAMA system has been proposed to help with this problem and turns out very successful on improving efficiency during emergency situation. However, the current DIORAMA system is not perfect for all scenarios, for example, there are some outdoor environments do not support GPS service. Also, the RFID reader is very heavy for responders to carry and the indoor environment is not applicable for DIORAMA system. Besides, there are lack of forensic visualization toolkits that are able to help the incident commander analyze the responders’ behavior and efficiency. In this project, we propose a Localization, Visualization and Evacuation Guidance System in Emergency Situations. The functionalities in this system include localization in outdoor environments using BLE. Besides, for outdoor environments, some forensic visualization toolkit that can help the responder analyze the responders’ behavior with the capability of visualization and representation of data clearly as well as replay the task, detect anomalies and visualize the anomalies clearly is also provided in improving the efficiency and organization in the future task. In addition, the system also includes an indoor localization, navigation guidance and visualization system that provides guidance for people to exit a dangerous building as soon as possible. This system is able to localize the position of evacuees, and construct the exit path that helps reduce the escape time as well as provide a navigation guidance that is able to guide the user to the exit. In addition, an analyst simulation application is provided to simulate the evacuees in a building and evaluate the evacuation time for evacuees given specific path generation algorithm

Evaluating a holistic energy benchmarking parameter of lift systems by using computer simulation

At present, there are benchmarking parameters to assess the energy performance of lifts, e.g. one in Germany adopted by VDI (4707-1/2), one internationally published by ISO (BS EN ISO 25745-2:2015), and the other in Hong Kong adopted by The Hong Kong Special Administrative Region (HKSAR) Government. These parameters are mainly checking the energy consumed by a lift drive without considering real time passenger demands and traffic conditions; the one in Hong Kong pinpointing a fully loaded up-journey under rated speed and the two in Europe pinpointing a round trip, bottom floor to top floor and return with an empty car, though including energy consumed by lighting, displays, ventilation etc. A holistic normalization method by Lam et al [1] was developed a number of years ago by one of the co-authors of this article, which can assess both drive efficiency and traffic control, termed J/kg-m, which is now adopted by the HKSAR Government as a good practice, but not specified in the mandatory code. In Europe, the energy unit of Wh has been used but here, Joule (J), i.e. Ws, is adopted to discriminate the difference between the two concepts. In this article, this parameter is evaluated under different lift traffic scenarios using computer simulation techniques, with an aim of arriving at a reasonable figure for benchmarking an energy efficient lift system with both an efficient drive as well as an efficient supervisory traffic control