中圖分類號(hào)： TP391.4；TP181 文獻(xiàn)標(biāo)識(shí)碼： A DOI： 10.19358/j.issn.2096-5133.2022.03.012 引用格式： 劉凱源. 基于C3D的化學(xué)實(shí)驗(yàn)室人員不安全行為模式識(shí)別[J].信息技術(shù)與網(wǎng)絡(luò)安全,，2022,，41(3)：71-77.
Patterns recognition of unsafe behavior in chemical laboratory based on C3D
Liu Kaiyuan
(School of Information Technology and Cyber Security，People′s Public Security University of China,，Beijing 100038,，China)
Abstract： In order to prevent chemical laboratory safety accidents caused by unsafe behavior，a patterns recognition method of unsafe behavior in chemical laboratory based on 3D convolutional network(C3D) is proposed. Firstly, five typical unsafe behavior patterns are defined. Then a university chemical laboratory is used as the study area to construct a dataset containing simulated unsafe behavior records. The patterns recognition model of unsafe behavior in chemical laboratory based on C3D is finally established, and the model performances in different scenarios are validated. The results show that under the circumstance that observed unsafe behaviors are from a specific person in a specific experimental scenario, the average F1-score on test set exceeds 97%. As well as, for non-specific persons and scenarios, the model can effectively identify some unsafe behaviors. The results of this research are expected to provide technical support for prediction, early warning and prevention of unsafe behaviors in chemical laboratory.
Key words : unsafe behavior,；chemical laboratory,；pattern recognition；3D convolutional network
