Prof. Litao Han Profile

Prof. Litao Han

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Proceedings Article | 10 October 2023 Paper

Entropy-based layered evacuation strategy and simulation for multi-storey building fire scene

Litao Han, Hongmei Li, Guoyu Liu

Proceedings Volume 12799, 127994D (2023) https://doi.org/10.1117/12.3005811

KEYWORDS: Fire, Modeling, 3D modeling, Visibility, Computer simulations, Visualization, Solid modeling, Visual process modeling, Standards development, Safety

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In case of a fire, it is the primary task of fire emergency response to safely and quickly evacuate indoor personnel to a safe area. Aiming at the characteristics of fire development and evacuation of multi-storey buildings, a layered evacuation strategy based on entropy is proposed for multi-storey buildings. With the help of PyroSim software to simulate the fire combustion process, the influence of the spread state of fire smoke on the selection of escape path exit in the building was analysed. Using AnyLogic, an agent modeling and simulation platform, making hybrid modelling of agents, discrete-event simulations and simulation of fire spread using system dynamics. Considering various influencing factors such as the gender, age, evacuation speed, and spatial distribution of the evacuated population, a simulation model close to the real layered evacuation process of personnel was established. The entropy optimization path selection strategy was used to make full use of various exits. The simulation results show that the fire smoke has different effects on different floors; By comparing the two plans, Plan B is obviously better than Plan A, so as to improve the effective occupation time of exit; The stratified evacuation strategy under the influence of fire smoke can reduce the evacuation time, improve the evacuation efficiency, and effectively ensure the safety of evacuees.

Proceedings Article | 8 June 2023 Paper

A real-time step detection algorithm based on dynamic peak-valley change threshold screening and dual-time threshold constraints

Qiaoli Kong, Tianfa Wang, Litao Han, Jingwei Han

Proceedings Volume 12707, 1270750 (2023) https://doi.org/10.1117/12.2681008

KEYWORDS: Detection and tracking algorithms, Tunable filters, Signal detection, Signal filtering, Signal processing

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As indoor inertial navigation, Pedestrian Dead Reckoning (PDR) has attracted much attention because its positioning results are not affected by the signal of smartphones. Due to the accumulated error of PDR, it is mostly used to improve indoor positioning accuracy by combining with absolute positioning technologies such as Wi-Fi and geomagnetism. The accuracy and efficiency of step detection in PDR have an important impact on the fusion positioning system. The existing step detection algorithms and the built-in pedometer of Android smartphones have the phenomenon of the delayed output of step detection results, which affects the efficiency of real-time indoor positioning based on PDR. In this paper, a real-time step detection algorithm based on dynamic peak-valley change threshold screening and dual-time threshold constraints is proposed. First, the true peak and true valley accelerations are screened according to the amplitude of peak-valley change based on the dynamic peak drop threshold and valley rise threshold, to eliminate the influence of noise near peak-valley values. Then, the peak-valley accelerations are further determined according to the dual-time threshold constraints. The accuracy and efficiency of step detection are effectively improved. This paper has completed experiments on the self-developed Android APP, and the experimental results show that the accuracy and efficiency of step detection are better than the pedometer provided by smartphones.

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