Smart City Gnosys
Smart city article details
| Title | Graph Theory Algorithms In Optimizing Urban Infrastructure In Smart Cities |
|---|---|
| ID_Doc | 28275 |
| Authors | Panǎ-Micu F. |
| Year | 2024 |
| Published | ACM International Conference Proceeding Series |
| DOI | http://dx.doi.org/10.1145/3670243.3670266 |
| Abstract | Creating smart cities is an increasingly debated aspiration in our society, as these cities, benefiting from advanced technologies, contribute to improving the quality of life for residents. In this context, graph theory proves to be a particularly important tool in the optimization processes of urban infrastructure networks. The main objective of the research is to identify key concepts from graph theory that can be applied in the creation of smart cities with the aim of optimizing urban infrastructure networks. Starting from this objective, the research will focus on defining key concepts from graph theory, such as Kruskal's algorithm for determining a minimum-cost spanning tree and Dijkstra's algorithm, which establishes the minimum-cost path from a starting node to any other node in a graph. Subsequently, the article will include examples illustrating how graph theory can be used to model the urban infrastructure network. Dijkstra's algorithm is applicable to identifying the most efficient transportation routes, reducing congestion and travel time, as well as optimizing pipeline networks and water distribution. On the other hand, Kruskal's algorithm aims to optimize areas of the smart city such as efficient resource management, green space planning, and sustainable connectivity. Therefore, in this article, we will explore the potential that graph theory can have in optimizing the urban infrastructure of a smart city and increasing the efficiency and sustainability of this type of city. The optimal choice of connections and networks can contribute to creating an urban environment that meets the needs of residents in a sustainable and efficient manner. © 2024 ACM. |
| Author Keywords | Dijkstra's algorithm; innovation; Kruskal's algorithm; optimization; smart city |
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