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The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

The purpose of this paper is to propose a theoretical framework of applying the Internet of Things (IoT) technologies to the intelligent evacuation protocol in libraries at emergency situations.

The authors conducted field investigations on eight libraries in Wuhan, China, analyzed the characteristics of crowd gathering in libraries and the problems of the libraries’ existing evacuation plans. Therefore, an IoT-based intelligent evacuation protocol in libraries was proposed. Its basic structure consisted of five components: the information base, the protocol base, the IoT sensors, the information fusion system and the intelligent evacuation protocol generation system. In the information fusion system, Dempster–Shafer (D-S) evidence theory was employed as the information fusion algorithm to fuse the multi-sensor information at multiple time points, so as to reduce the uncertainty of disaster prediction. The authors also conducted a case study on the Library L in Wuhan, China. A specific evacuation route was generated for a fire and the crowd evacuation was simulated by the software Patherfind.

The proposed IoT-based evacuation protocol has four distinguishing features: scenario corresponding, precise evacuation, dynamic correction and intelligent decision-making. The case study shows that the proposed protocol is feasible in practice, indicating that the IoT technologies have great potential to be successfully applied to the safety management in libraries.

The software and hardware requirements as well as the Internet network requirements of IoT technologies need to be further discussed.

The proposed IoT-based intelligent evacuation protocol can be widely used in libraries, which is one of the inspirations for the use of IoT technologies in modern constructers.

The application of IoT technologies in libraries is a brand-new topic that has drawn much attention in academia recently. The crowd safety management in libraries is of great significance, and there is little professional literature on it. This paper proposes an IoT-based intelligent evacuation protocol, aiming at improving the safety management in libraries at emergency situations.