• Research on Data-Driven Smart City Risk Identification Mechanism in Jiangsu Province
    ID:173 Submission ID:123 View Protection:ATTENDEE Updated Time:2022-05-13 15:44:50 Hits:459 Oral Presentation

    Start Time:2022-05-26 15:00 (Asia/Shanghai)

    Duration:15min

    Session:[S8] Public Security and Emergency Management [S8-1] Public Security and Emergency Management-1

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    Abstract
    Jiangsu Province, as a major province with various resources in China, faces a lot of risks while developing its economy and society. Therefore, establishing a timely, effective and accurate risk identification mechanism has become a key issue in preventing urban risks and maintaining urban order. This subject builds an index system on the basis of literature research and Delphi expert consultation method, and based on entropy weight method, evaluates the ability of emergency risk identification in Jiangsu Province from four aspects: planning and preparation, risk identification development, supervision and communication, and improvement. According to the evaluation results, it is concluded that in the risk identification of emergencies in Jiangsu Province, there are problems such as weak awareness of risk identification, poor timeliness and delay, lag in platform construction, in-depth development, and barriers to information sharing. Then, by drawing on the experience of domestic and foreign emergency risk identification capacity building models, the countermeasures and suggestions for building a risk identification mechanism for smart cities in Jiangsu Province are put forward: strengthen the construction of digital government, and promote the development of risk identification; break information barriers and achieve accurate risk identification; strengthen Algorithm correlation, promote the coordination of risk identification; straighten out the algorithm power relationship, promote the technicalization of risk identification operation; build a digital order, strengthen algorithm ethics and algorithm responsibility.
    Keywords
    Smart city; Emergencies; Risk Identification.
    Speaker
    Rui ZHANG
    China University of Mining and Technology

    Submission Author
    睿 張睿 中國礦業大學
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