Author(s)

Hai Wang

Corresponding Author

Hai Wang

Abstract

With the accelerating pace of urbanization, municipal infrastructure has become increasingly vital in ensuring urban operations and residents' quality of life. Traditional maintenance and management models commonly suffer from information silos, delayed responses, and inefficient resource allocation, failing to meet the demands of modern, refined urban governance. The emergence of big data technology offers new approaches and tools for intelligent municipal infrastructure management. This paper systematically explores optimization pathways for municipal infrastructure maintenance and management from a big data-driven perspective. The study first clarifies the application logic of big data in infrastructure management, emphasizing the critical role of data collection, integration, and sharing in enhancing management efficiency. It constructs a predictive and preventive maintenance model based on big data analysis, proposing a shift from “reactive repair” to “proactive prevention” through machine learning and lifecycle prediction. and explores the value of decision support systems in optimizing resource allocation, enhancing emergency response, and aiding management decisions. While big data technology can effectively advance the scientific and intelligent maintenance and management of municipal infrastructure, challenges remain in data standardization, privacy protection, and cross-departmental coordination. This research provides theoretical support and practical reference for smart city development.

Keywords

Big Data, Municipal Infrastructure, Maintenance Management, Predictive Modeling, Decision Support, Smart Cities