Evacuee routing algorithms in emergency typically adopt one single criterion to compute desired paths and ignore the specific requirements of users caused by different physical strength, mobility and level of resistance to hazard. In this paper, we present a quality of service (QoS) driven multi-path routing algorithm to provide diverse paths for different categories of evacuees. This algorithm borrows the concept of Cognitive Packet Network (CPN), which is a flexible protocol that can rapidly solve optimal solution for any user-defined goal function. Spatial information regarding the location and spread of hazards is taken into consideration to avoid that evacuees be directed towards hazardous zones. Furthermore, since previous emergency navigation algorithms are normally insensitive to sudden changes in the hazard environment such as abrupt congestion or injury of civilians, evacuees are dynamically assigned to several groups to adapt their course of action with regard to their on-going physical condition and environments. Simulation results indicate that the proposed algorithm which is sensitive to the needs of evacuees produces better results than the use of a single metric. Simulations also show that the use of dynamic grouping to adjust the evacuees' category and routing algorithms with regard for their on-going health conditions and mobility, can achieve higher survival rates.
Research then moved further to the development of complex Emergency Cyber-Physical-Human systems to direct evacuees to exits in a real time @cite_27 with sensor nodes (SNs) responsible for collecting hazard information while the decision subsystem composed of decision nodes (DNs) provides advice to evacuees through visual indicators or portable devices. @cite_29 implement a WSN consisting of sensors that continuously monitor the environment and distribute a danger-level map across the network. Optimization methods have been suggested @cite_12 using distributed decision making with random neural networks @cite_32 @cite_25 to overcome the huge complexity of decision making for a large number of agents in the presence of spatial information to help select exit routes and decide about the appropriate allocation of rescuers and technical assets.
@cite_29 @cite_32 @cite_27 @cite_25 @cite_12
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Information systems that provide decision support in an efficient and timely manner can prove beneficial for emergency response operations. In this paper we propose the use of a system that provides movement decision support to evacuees by directing them through the shortest or less hazardous routes to the exit and evaluate it with a specialised software platform that we have developed for simulation of disasters in buildings. The system operates in a distributed manner, and computes the best evacuation routes in real-time while a hazard is spreading inside the building. It is composed of a network of decision nodes and sensor nodes, positioned in specific locations inside the building. The recommendations of the decision nodes are computed in a distributed manner, at each of the decision nodes, which then communicate them to evacuees or rescue personnel located in their vicinity. We use a multi-agent simulation platform for Building Evacuation that we developed, in order to evaluate our proposed system in various emergency scenarios. Our simulation results show that the overall outcome of the evacuation procedure is improved when the decision support system is in operation. Recently, Wireless Sensor Networks (WSNs) have been widely discussed in many applications. In this paper, we propose a novel Three-Dimensional (3D) emergency service that aims to guide people to safe places when emergencies happen. At normal time, the network is responsible for monitoring the environment. When emergency events are detected, the network can adaptively modify its topology to ensure transportation reliability, quickly identify hazardous regions that should be avoided and find safe navigation paths that can lead people to exits. In particular, the structures of Three-Dimensional buildings are taken into account in our design. Simulation results shows that our protocols can adapt emergencies quickly at low message cost and can find safer paths to exits than existing results Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited computation, communication, memory, and energy resources that are being used for huge range of applications where the traditional infrastructure-based network is mostly infeasible. The sensor nodes are densely deployed in a hostile environment to monitor, detect, and analyze the physical phenomenon and consume considerable amount of energy while transmitting the information. It is impractical and sometimes impossible to replace the battery and to maintain longer network life time. So, there is a limitation on the lifetime of the battery power and energy conservation is a challenging issue. Appropriate cluster head (CH) election is one such issue, which can reduce the energy consumption dramatically. Low energy adaptive clustering hierarchy (LEACH) is the most famous hierarchical routing protocol, where the CH is elected in rotation basis based on a probabilistic threshold value and only CHs are allowed to send the information to the base station (BS). But in this approach, a super-CH (SCH) is elected among the CHs who can only send the information to the mobile BS by choosing suitable fuzzy descriptors, such as remaining battery power, mobility of BS, and centrality of the clusters. Fuzzy inference engine (Mamdani’s rule) is used to elect the chance to be the SCH. The results have been derived from NS-2 simulator and show that the proposed protocol performs better than the LEACH protocol in terms of the first node dies, half node alive, better stability, and better lifetime. The evacuation of a building is a challenging problem, since the evacuees most of the times do not know or do not follow the optimal evacuation route. Especially during an ongoing hazard present in the building, finding the best evacuation route becomes harder as the conditions along the paths change in the course of the evacuation procedure. In this paper we propose a distributed system that will compute the best evacuation routes in real-time, while a hazard is spreading inside the building. The system is composed of a network of decision nodes and sensor nodes, positioned in specific locations inside the building. The recommendations of the decision nodes are computed in a distributed manner, at each of the decision nodes, which then communicate them to evacuees or rescue personnel located in their vicinity. We evaluate our proposed system in various emergency scenarios, using a multi-agent simulation platform for Building Evacuation. Our results indicate that the presence of the system improves the outcome of the evacuation with respect to the evacuation time and the injury level of the evacuees.