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This paper proposes a load-balancing framework for distributed emergency guiding based on wireless sensor networks. A load-balancing guiding scheme is designed and an analytical model is derived to reduce the total evacuation time of people indoors. The guiding scheme can provide the fastest path for people to reach an exit according to the evacuation time estimated using the analytical model. Based on thorough research, this is the first distributed solution in which corridor capacity and length, exit capacity, and the concurrent movement and distribution of people are considered in estimating the evacuation time and planning escape paths. Using the proposed framework, congestion in corridors and at exits can be eased to substantially reduce the total evacuation time. Analytical and simulation results show that this approach outperforms existing schemes and can prevent people from following local-optimal guiding directions that increase the evacuation time. A prototype called the Load-balancing Emergency Guiding System (LEGS) is implemented; this system can be used to compare the evacuation times and guiding directions provided by existing schemes and the proposed scheme for various distributions of people.

This paper proposes a load-balancing framework for emergency guiding based on wireless sensor networks. We design a load-balancing guiding scheme and derive an analytical model in order to reduce the total evacuation time of indoor people. The guiding scheme can provide the fastest path to an exit for people based on the evacuation time estimated by the analytical model. This is the first distributed solution which takes the corridor capacity and length, exit capacity, concurrent move, and people distribution into consideration for estimating evacuation time and planning escape paths. Through the proposed framework, the congestion of certain corridors and exits can be released to significantly reduce the total evacuation time. Analytical and simulation results show that our approach outperforms existing works, which can prevent people from following the local optimal guiding direction with the longer evacuation time in total. We also implement a prototype, called Load-balancing Emergency Guiding System (LEGS), which can compare evacuation time and guiding directions of existing schemes and ours under different people distribution.