保护城市安全免受危险品侵害的决斗系统No Longer Sleeping with a Bomb: A Duet System for Protecting Urban Safety from Dangerous Goods |
|
课程网址: | https://videolectures.net/videos/kdd2017_wang_dangerous_goods |
主讲教师: | Jingyuan Wang |
开课单位: | KDD 2017研讨会 |
开课时间: | 2017-10-09 |
课程语种: | 英语 |
中文简介: | 近年来,全球大都市不断发展,城市安全成为现代城市生活的重中之重。在各种威胁中,通过城市及其周边运输的天然气和危险化学品等危险品越来越成为我们每天睡觉的“炸弹”。在学术界和政府中,人们都在努力解决危险货物运输(DGT)问题,但仍需要进一步的研究来量化这个问题,并从大数据的角度探索其内在动态。在本文中,我们提出了一种称为DGeye的新系统,该系统的特点是DGT轨迹数据和人类活动数据之间的“二重奏”,用于识别危险区域。此外,DGeye创新性地将风险模式作为DGT管理的重点,并在它们之间建立因果关系网络,用于痛点识别、归因和预测。在北京和天津两个城市的实验证明了DGeye的有效性。特别是,DGeye部署后,促使北京政府为著名的桂街美食街铺设了 |
课程简介: | Recent years have witnessed the continuous growth of megalopolises worldwide, which makes urban safety a top priority in modern city life. Among various threats, dangerous goods such as gas and hazardous chemicals transported through and around cities have increasingly become the deadly “bomb” we sleep with every day. In both academia and government, tremendous efforts have been dedicated to dealing with dangerous goods transportation (DGT) issues, but further study is still in great need to quantify the problem and explore its intrinsic dynamics in a big data perspective. In this paper, we present a novel system called DGeye, which features a “duet” between DGT trajectory data and human mobility data for risky zones identification. Moreover, DGeye innovatively takes risky patterns as the keystones in DGT management, and builds causality networks among them for pain points identification, attribution and prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGeye. In particular, DGeye after deployment has driven the Beijing government to lay down gas pipelines for the famous Guijie food street. |
关 键 词: | 危险货物运输; 大数据; DGT轨迹数据 |
课程来源: | 视频讲座网 |
数据采集: | 2024-12-25:liyq |
最后编审: | 2024-12-26:liyq |
阅读次数: | 8 |