- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Cities worldwide are attempting to transform themselves into smart cities. Recent cases and studies show that a key factor in this transformation is the use of urban big data from stakeholders and physical objects in cities. However, the knowledge and framework for data use for smart cities remain relatively unknown. This paper reports findings from an analysis of various use cases of big data in cities worldwide and the authors' four projects with government organizations toward developing smart cities. Specifically, this paper classifies the urban data use cases into four reference models and identifies six challenges in transforming data into information for smart cities. Furthermore, building upon the relevant literature, this paper proposes five considerations for addressing the challenges in implementing the reference models in real-world applications. The reference models, challenges, and considerations collectively form a framework for data use for smart cities. This paper will contribute to urban planning and policy development in the modern data-rich economy.
The fundamental aspect of recent and expected data-based smart city innovations is not ICT, data, or intelligent infrastructure, but the new applications for value creation for stakeholders (e.g., citizens). The use of urban big data contributes to the creation of information for stakeholders to perform their processes better and create value. The main contribution of this paper is the development of knowledge and frameworks for data use for smart cities drawing from this applicationoriented perspective. The proposed classification scheme suggests four reference models to create value for citizens, visitors, local government, and companies using the data obtained from them. There are at least six challenges in transforming urban data into information for smart cities. The proposed five considerations for the collection, management, and analysis of urban data will help address those challenges in implementing the reference models.