Abstract
The smart city operation and management center with a hierarchical data-driven architecture has already become one of the most widely used solutions for smart cities in practice, solving the problems associated with data acquisition, data gathering and storage, data processing, and data application. At present, the construction of smart city operation and management center faces bottlenecks such as incomplete top-level design theory, the insufficient integration capability of software and hardware, the low efficiency of data collection and aggregation, and the lack of intelligence in data analysis and application. Aiming to address the above problems, this paper proposes a `two-dimension, three-layer, and six-goal' top-level design model for a smart city, with six principles for a smart city operational pattern, and focuses on three key technologies: (1) infrastructure integration and application, (2) multidimensional perception data collection and aggregation, and (3) intelligent data analysis and data service. Following the guidance of this model, Longgang District of Shenzhen has constructed a smart city operation and management center including integrated ICT infrastructure, an urban fine management system, and an intelligent urban data analysis and service system. The actual effects and quantitative improvements in the practical case show that the top-level design model of a smart city proposed in this paper has achieved successful results, and it thereby offers an applicability model of a smart city that can be referenced and replicated.
Highlights
The modern city has been upgraded from a binary space to a ternary space linking physics, human society, and information networks [1]
The top-level design method emphasizes the integrity of complex engineering, pays attention to the close combination of design and actual needs, and considers all levels and elements as a whole from the overall perspective to achieve the overall goal of the system
1) DATA-DRIVEN ARCHITECTURE MODELS OF SMART CITIES There are a variety of research views on smart city architecture models, such as designs focused on IoT [36], designs based on service-oriented architecture (SOA) architecture [37,38,39], and designs from the ecosystem perspective [40,41]
Summary
The modern city has been upgraded from a binary space to a ternary space linking physics, human society, and information networks [1]. The rapid construction and development of smart cities has gradually led to the prominence of problems in the interconnection and interoperability of business systems, data aggregation and sharing, the improvement in governance capability by data application, and the massive heterogeneous data processing of smart cities. These problems pose great challenges to the improvement in the urban intelligence level and the endogenous driving force of sustainable development, and offer great opportunities for the key technologies and engineering practice of datadriven smart city systems.
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