A Public Safety Deduction Framework Based on Real-Time Big Data

Chen, Bin; Luo, Yihang; Qiu, Xiaogang

doi:10.1007/978-981-10-2669-0_62

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…Integrating AI in public safety governance and crisis management is an important area of research with significant implications for societal well-being. Studies discuss the need for responsible AI practices in crisis resilience management and present a roadmap with six propositions to address challenges and considerations related to equity, fairness, biases, explainability and transparency, accountability, privacy, inter-organizational coordination, and public engagement [22]. The research proposed a Disaster City Digital Twin paradigm that integrates AI algorithms and approaches to improve situation assessment, decision-making, and coordination among various stakeholders [23].…”

Section: Ai Integration In Public Safety Governance and Crisis Manage...mentioning

confidence: 99%

“…A study discusses using AI systems to ensure public safety in a "smart city" and proposes developing a regulatory framework in Belarus to protect citizens' rights [25]. investigation proposes a public safety deduction framework based on big real-time data to find the most optimal emergency decision plan [22]. study systematically reviews the prevalence and content of ethical guidance for disaster response, finding that most of the literature focuses on the ethical justifications for crisis standards of care, triage, and international issues [26].…”

Section: Ai Integration In Public Safety Governance and Crisis Manage...mentioning

confidence: 99%

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Construction and Path of Urban Public Safety Governance and Crisis Management Optimization Model Integrating Artificial Intelligence Technology

Wang

2023

Sustainability

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As urbanization and population growth continue to accelerate in China, maintaining public safety and crisis management has become increasingly complex. To address this issue, this research article proposes a new model for optimizing urban public safety governance and crisis management by integrating artificial intelligence (AI) technology with a focus on sustainability. This study aims to explore the construction and path of an urban public safety governance and crisis management optimization model integrating artificial intelligence (AI) technology in China. We developed a linear regression model to examine the relationship between public safety technologies and outcomes, with public safety outcomes (PSO) as the dependent variable and public safety governance structure (PSGS), AI-driven data collection and analysis (AIDC&A), crisis prediction and early warning system (CPEWS), AI-assisted decision-making (AIADM), and public safety response mechanisms (PSRM) as independent variables. The model summary revealed that the independent variables accounted for a moderate proportion of the variance in public safety outcomes, with an R² value of 0.5 and an adjusted R² value of 0.45. The results supported the hypothesis that the integration of different public safety technologies has a positive impact on public safety outcomes. The effective governance structure, AI-driven data collection and analysis, crisis prediction and early warning system, AI-assisted decision-making, and efficient public safety response mechanisms were all found to be crucial for enhancing public safety outcomes. The proposed model was validated through a case study in a Chinese city, with feedback from stakeholders confirming its effectiveness. Overall, the findings suggest that the urban public safety governance and crisis management optimization model integrating AI technology can significantly improve public safety management in urban areas.

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Section: Ai Integration In Public Safety Governance and Crisis Manage...mentioning

confidence: 99%

Section: Ai Integration In Public Safety Governance and Crisis Manage...mentioning

confidence: 99%

Construction and Path of Urban Public Safety Governance and Crisis Management Optimization Model Integrating Artificial Intelligence Technology

Wang

2023

Sustainability

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“…With technology development, an intelligent monitoring system related to Industry 4.0 has been adapted for real-time monitoring of MHIs [105][106][107]. Kong et al [107] developed a data-driven warning method for CIPs, introducing information technology to the monitoring system to achieve early-warning.…”

Section: Monitoring and Warningmentioning

confidence: 99%

A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks

et al. 2020

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The increasing demand for chemical products has driven the construction and development of chemical industrial areas, or so-called ‘chemical industrial parks’ (CIPs), but this has intrinsically raised the risk of major accidents. Therefore, it is significant and urgent to summarize the state of art and research needs in the field of CIP safety. In this paper, a keyword co-occurrence analysis of 116 scientific articles was conducted to support the classification of research topics in this field, then an overview of those research topics was presented to investigate the evolution of safety research with respect to CIPs. Specifically, the way that safety assessments are conducted, as well as how safety management and safety technology in such areas are classified and investigated, followed by detailed descriptions of representative methods and their contributions to CIP safety, are discussed. An integrated safety framework for CIPs is proposed to organize safety approaches and measures systematically. Based on the classification and analysis of studies on management, assessment, and technology related to CIP safety, the research trends and future directions and challenges are discussed and outlined. Those results are useful for improving theoretical method and industrial strategies, and can advance the safety and sustainability development of CIPs.

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“…Rescue organizers can quickly and accurately receive information, grasp the evacuation of personnel and vehicles, the use of rescue personnel and materials, and take timely measures to improve rescue efficiency [21]. To sum up, the traffic emergency response system based on the Internet of Things will have advantages over the traditional emergency response system [22]. The match between the Internet of Things technology and the data information collection system under emergencies is shown in Fig.…”

Section: Applicability Analysis Of Internet Of Things Technology In U...mentioning

confidence: 99%

Design of Traffic Emergency Response System Based on Internet of Things and Data Mining in Emergencies

Liu

Wang

2019

IEEE Access

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Urban emergencies are hard to avoid. Traffic emergency response after an incident plays an important role in reducing losses and is a key link in urban emergency management. However, the traditional traffic management methods have been difficult to face the complicated conditions and requirements in such problems. The introduction of Internet of Things and data mining technology to establish a traffic emergency response system under urban emergencies can significantly improve the level of urban emergency response and realize efficient intensive management. The system mainly includes sub-systems, such as personnel evacuation data collection system, vehicle operation data collection system, rescue material distribution data collection system, personnel settlement place data collection system, traffic bayonet intelligent identification system, etc. It also devises the working programs for command management, personnel evacuation and disaster disposal in case of emergency, and improves the urban emergency support management system. With the support of Internet of Things and the data mining technology, the traffic emergency response system can timely and accurately control the flowing information of personnel and vehicles, quickly and conveniently resettle personnel and vehicles, effectively carry out follow-up rescue work, effectively improve rescue efficiency and improve the level of urban management.INDEX TERMS Internet of Things, data mining, emergencies, emergency rescue, system design.

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A Public Safety Deduction Framework Based on Real-Time Big Data

Cited by 6 publications

References 3 publications

Construction and Path of Urban Public Safety Governance and Crisis Management Optimization Model Integrating Artificial Intelligence Technology

Construction and Path of Urban Public Safety Governance and Crisis Management Optimization Model Integrating Artificial Intelligence Technology

A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks

Design of Traffic Emergency Response System Based on Internet of Things and Data Mining in Emergencies

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