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.
However, wireless sensor network based emergency navigation systems suffer from inherent disadvantages such as limited computing capability, restrained battery power and restricted storage capacity. Hence, it is difficult for this type of architecture to provide optimal solutions in a timely fashion. Via using static or mobile sensors as thin client and offloading intensive computations to remote servers, cloud enabled emergency navigation systems have the potential to revolutionise this field. By leveraging existing public cloud services such as social network sites, Ref. @cite_12 @cite_10 present emergency warning systems to gather and disperse multi-media emergency information among users. Ref. @cite_16 @cite_14 employ built-in camera on the smart phones to take snapshots and upload to servers to identify the location of evacuees. Based on the extracted data, the cloud-based emergency navigation system can provide appropriate paths for civilians.
@cite_14 @cite_16 @cite_10 @cite_12
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In an emergency, wireless network sensors combined with a navigation algorithm could help safely guide people to a building exit while helping them avoid hazardous areas. We propose a distributed navigation algorithm for emergency situations. At normal time, sensors monitor the environment. When the sensors detect emergency events, our protocol quickly separates hazardous areas from safe areas, and the sensors establish escape paths. Simulation and implementation results show that our scheme achieves navigation safety and quick convergence of the navigation directions. We based our protocol on the temporally ordered routing algorithm for mobile ad hoc networks. TORA assigns mobile nodes temporally ordered sequence numbers to support multipath routing from a source to a specific destination node Opportunistic communications (oppcomms) use low-cost human wearable mobile nodes allowing the exchange of packets at a close range of a few to some tens of meters with limited or no infrastructure. Typically cheap pocket devices which are IEEE 802.15.4-2006 compliant can be used and they can communicate at 2m to 10m range, with local computational capabilities and some local memory. In this paper we consider the application of such devices to emergency situations when other means of communication have broken down. This paper evaluates whether oppcomms can improve the outcome of emergency evacuation in directing civilians safely. We describe an autonomous emergency support system (ESS) based on oppcomms to support evacuation of civilians in a built environment such as a building or supermarket. The proposed system uses a fixed infrastructure of sensor nodes (SNs) to monitor the environment. Hazard information obtained via SNs is disseminated to the individuals, and they spread among the people who are located in this built environment using oppcomm devices carried by these people. The information received by these people can then guide them safely to the exits as the emergency situation evolves over time. We evaluate our scheme using a distributed multi-agent building evacuation simulator (DBES) in the context of evacuation scenarios of a multi-storey office building in the presence of a fire that is spreading. The results show the degree of improvement that the oppcomms can offer. c � 2011 Published by Elsevier Ltd. This paper proposes a group-based framework with dedicated path planning for emergency guiding based on Internet of Things (IoT) technologies. The proposed framework can model the spatiotemporal mobility of indoor people to determine and relieve the congestion of corridors and exits. A dedicated path can be determined to provide the shortest evacuation time for each group of nearby people. The corridor and exit capacities, corridor lengths, clustering motion of a group, concurrent moving of different groups, and up-to-date distribution of group people are considered together to accurately estimate the evacuation time for each group. Based on the estimated evacuation time, evacuation load can be evenly distributed among corridors and exits to alleviate the congestion of all corridors and exits for minimizing total evacuation time. The performance of the proposed framework is evaluated by conducting mathematical analysis and computer simulations, which outperforms existing schemes and can achieve the shortest evacuation time for group-based emergency guiding. In addition, an Android-based prototype with indoor IoT localization technologies is implemented to verify the feasibility of our framework. Emergency response operations can benefit from the use of information systems that reduce decision making time and facilitate co-ordination between the participating units. We propose the use of two such systems and evaluate them with a specialised software platform that we have developed for simulation of disasters in buildings. The first system provides movement decision support to evacuees by directing them through the shortest or less hazardous routes to the exit. It is composed of a network of decision nodes and sensor nodes, positioned at specific locations inside the building. The recommendations of the decision nodes are computed in a distributed manner and communicated to the evacuees or rescue personnel in their vicinity. The second system uses wireless-equipped robots that move inside a disaster area and establish a network for two-way communication between trapped civilians and rescuers. They are autonomous and their goal is to maximise the number of civilians connected to the network. We evaluate both proposed information systems in various emergency scenarios, using the specialised simulation software that we developed.