设计一个使用公开犯罪数据和众包的公共安全移动系统

Yun Huang, Yang Wang, Corey White
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引用次数: 4

摘要

随着越来越多的城市开放犯罪数据和参与式传感的扩散,我们探索通过使用公开的犯罪数据和众包来改善当地社区公共安全的方法。我们首先进行了一次在线调查,以更好地了解雪城大学(SU)社区的公共安全需求。受调查结果的启发,我们与SU的公共安全部门(DPS)合作开发并部署了一个Android移动应用程序;这款应用整合了谷歌地图上发布的安全事件和加州大学校园警报。我们介绍了我们与DPS共同设计这个系统的经验,挑战和我们最初的应用程序发布的经验。为了设计有效的公共安全信息众包,我们进行了一个实验室实验,研究了影响人们共享决策的因素。结果表明,一天中的时间和地点类型都会显著影响人们的共享决策。这些见解为我们重新设计系统提供了信息,以“推动”人们及时报告安全相关信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing a mobile system for public safety using open crime data and crowdsourcing
With more cities opening up crime data and the proliferation of participatory sensing, we explore ways to improve public safety of a local community by using open crime data and crowdsourcing. We first conducted an online survey to better understand the public safety needs of the Syracuse University (SU) community. Inspired by the survey results, we developed and deployed an Android mobile app in collaboration with the Department of Public Safety (DPS) at SU; the app integrates published safety incidents on a Google Map and SU campus alerts. We present our experience of co-designing this system with the DPS, challenges and experience of our initial app release. To design effective crowdsourcing of public safety information, we conducted a lab experiment to investigate what factors affect people's sharing decisions. The results suggest that both time of day and type of location significantly affect people's sharing decisions. These insights inform a re-design of our system to "nudge" people to report safety related information timely.
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