<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>As a densely populated place, the occurrence of accidents on campus causes serious concerns, while the construction of an intelligent and safe campus is also one of the hotly debated topics. Starting from the perspective of the development process of security events, this paper comprehensively perfects each stage and applies reasonable methods, hoping to reduce the cost of human and material resources in campus security. First, the abnormal behaviour data set and the identification model based on time and space fusion are constructed to identify the abnormal behaviours on campus. Further on, through the agent reward function construction and state transfer function solution and algorithm research, the multi-intelligent-agent tracking and cooperation based on the game idea are realised to provide efficient real-time security alarm and decision suggestion. Finally, the safety resource path planning platform is designed, and the simulation analysis is conducted combined with the traffic network of New Normal University. The results turn out to identify the abnormal behaviour, work out the optimal decision as well as figure out the optimal path of security resources planning and verify the effectiveness of the mathematical model in a simulation manner.</p>
</abstract>

As a densely populated place, the occurrence of accidents on campus causes serious concerns, while the construction of an intelligent and safe campus is also one of the hotly debated topics. Starting from the perspective of the development process of security events, this paper comprehensively perfects each stage and applies reasonable methods, hoping to reduce the cost of human and material resources in campus security. First, the abnormal behaviour data set and the identification model based on time and space fusion are constructed to identify the abnormal behaviours on campus. Further on, through the agent reward function construction and state transfer function solution and algorithm research, the multi-intelligent-agent tracking and cooperation based on the game idea are realised to provide efficient real-time security alarm and decision suggestion. Finally, the safety resource path planning platform is designed, and the simulation analysis is conducted combined with the traffic network of New Normal University. The results turn out to identify the abnormal behaviour, work out the optimal decision as well as figure out the optimal path of security resources planning and verify the effectiveness of the mathematical model in a simulation manner.

An intelligent campus simulation system based on game

School of Computer Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"An intelligent campus simulation system based on game"}

As a densely populated place, the occurrence of accidents on campus causes serious concerns, while the construction of an intelligent and safe campus is also...

An intelligent campus simulation system based on game

Published Online: Dec 12, 2022

Page range: 1169 - 1180

Received: Oct 08, 2022

Accepted: Nov 19, 2022

DOI: https://doi.org/10.2478/amns.2021.2.00315

Keywords
Intelligent campus, behavior recognition, intelligent decision-making, resource planning, intelligent simulation

© 2022 Zhou Zheng Hao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

An intelligent campus simulation system based on game

Published Online: Dec 12, 2022

Page range: 1169 - 1180

Received: Oct 08, 2022

Accepted: Nov 19, 2022

DOI: https://doi.org/10.2478/amns.2021.2.00315

KeywordsIntelligent campus, behavior recognition, intelligent decision-making, resource planning, intelligent simulation

© 2022 Zhou Zheng Hao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Intelligent campus, behavior recognition, intelligent decision-making, resource planning, intelligent simulation