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

WSN and RFID integration to support intelligent monitoring in smart buildings using hybrid intelligent decision support systems

The real time monitoring of environment context aware activities is becoming a standard in the service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt reaction to potential hazards identified at an early stage to engage appropriate control actions. This requires capturing real time data to process locally at the device level or communicate to backend systems for real time decision making. This research examines the wireless sensor network and radio frequency identification technology integration in smart homes to support advanced safety systems deployed upstream to safety and emergency response. These systems are based on the use of hybrid intelligent decision support systems configured in a multi-distributed architecture enabled by the wireless communication of detection and tracking data to support intelligent real-time monitoring in smart buildings. This paper introduces first the concept of wireless sensor network and radio frequency identification technology integration showing the various options for the task distribution between radio frequency identification and hybrid intelligent decision support systems. This integration is then illustrated in a multi-distributed system architecture to identify motion and control access in a smart building using a room capacity model for occupancy and evacuation, access rights and a navigation map automatically generated by the system. The solution shown in the case study is based on a virtual layout of the smart building which is implemented using the capabilities of the building information model and hybrid intelligent decision support system.The Saudi High Education Ministry and Brunel University (UK

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

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

Multimodal-Transport Collaborative Evacuation Strategies for Urban Serious Emergency Incidents Based on Multi-Sources Spatiotemporal Data (Short Paper)

When serious emergency events happen in metropolitan cities where pedestrians and vehicles are in high-density, single modal-transport cannot meet the requirements of quick evacuations. Existing mixed modes of transportation lacks spatiotemporal collaborative ability, which cannot work together to accomplish evacuation tasks in a safe and efficient way. It is of great scientific significance and application value for emergency response to adopt multimodal-transport evacuations and improve their spatial-temporal collaboration ability. However, multimodal-transport evacuation strategies for urban serious emergency event are great challenge to be solved. The reasons lie in that: (1) large-scale urban emergency environment are extremely complicated involving many geographical elements (e.g., road, buildings, over-pass, square, hydrographic net, etc.); (2) Evacuated objects are dynamic and hard to be predicted. (3) the distributions of pedestrians and vehicles are unknown. To such issues, this paper reveals both collaborative and competitive mechanisms of multimodal-transport, and further makes global optimal evacuation strategies from the macro-optimization perspective. Considering detailed geographical environment, pedestrian, vehicle and urban rail transit, a multi-objective multi-dynamic-constraints optimization model for multimodal-transport collaborative emergency evacuation is constructed. Take crowd incidents in Shenzhen as example, empirical experiments with real-world data are conducted to evaluate the evacuation strategies and path planning. It is expected to obtain innovative research achievements on theory and method of urban emergency evacuation in serious emergency events. Moreover, this research results provide spatial-temporal decision support for urban emergency response, which is benefit to constructing smart and safe cities

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