The Construction of Smart Cities and Big Data Governance Strategies Based on Artificial Intelligence

To tackle the challenge of sluggish resource scheduling in smart city management, the author introduces a study focused on smart city development leveraging artificial intelligence and big data governance strategies. The research uses the Cloud Management Module to monitor the various hardware equipment, and establishes the target functionality of the Cloud Computing Resource Scheduling. Through the application of PSO to this goal function, a optimal scheme is created for the Cloud Resource Scheduling. Experimental results demonstrate that the system achieves optimal resource utilization, nearing 100%, whereas the other two systems have lower utilization rates, both under 90%. This indicates that, compared to similar systems, this approach offers superior overall utilization. The system is capable of efficiently managing smart cities and providing real-time monitoring of urban conditions. When scheduling resources, it achieves shorter task completion times and higher system efficiency, ensuring maximum resource utilization.

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Publication Details

Journal
Scalable Computing Practice and Experience
Published
2025-07-14
DOI
https://doi.org/10.12694/scpe.v26i5.4716
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

The Construction of Smart Cities and Big Data Governance Strategies Based on Artificial Intelligence

Yinping Li
Scalable Computing Practice and Experience
E-commerce and Technology Innovations
article

The Construction of Smart Cities and Big Data Governance Strategies Based on Artificial Intelligence

Yinping Li
article en

Abstract

To tackle the challenge of sluggish resource scheduling in smart city management, the author introduces a study focused on smart city development leveraging artificial intelligence and big data governance strategies. The research uses the Cloud Management Module to monitor the various hardware equipment, and establishes the target functionality of the Cloud Computing Resource Scheduling. Through the application of PSO to this goal function, a optimal scheme is created for the Cloud Resource Scheduling. Experimental results demonstrate that the system achieves optimal resource utilization, nearing 100%, whereas the other two systems have lower utilization rates, both under 90%. This indicates that, compared to similar systems, this approach offers superior overall utilization. The system is capable of efficiently managing smart cities and providing real-time monitoring of urban conditions. When scheduling resources, it achieves shorter task completion times and higher system efficiency, ensuring maximum resource utilization.

Scalable Computing Practice and ExperienceVol. 26(5)
Anhui University (CN)
Openalex Percentile: Top 68%
E-commerce and Technology Innovations
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