Search Results (11)

The concept of digital twins (DTs) has expanded to encompass buildings and cities, with urban building energy modeling (UBEM) playing a crucial role in predicting urban-scale energy consumption via modeling individual energy use and interactions. As a virtual model within urban digital twins (UDTs), UBEM offers the potential for managing energy in sustainable cities. However, UDTs face challenges with regard to integrating large-scale data and relying on bottom-up UBEM approaches. In this study, we propose an AI agent-based intelligent urban digital twin (I-UDT) to enhance DTs’ technical realization and UBEM’s service functionality. Integrating GPT within the UDT enabled the efficient integration of fragmented city-scale data and the extraction of building features, addressing the limitations of the service realization of traditional UBEM. This framework ensures continuous updates of the virtual urban model and the streamlined provision of updated information to users in future studies. This research establishes the concept of an I-UDT and lays a foundation for future implementations. The case studies include (1) data analysis, (2) prediction, (3) feature engineering, and (4) information services for 3500 buildings in Seoul. Through these case studies, the I-UDT was integrated and analyzed scattered data, predicted energy consumption, derived conditioned areas, and evaluated buildings on benchmark. Full article

To improve the informatization construction and intelligent decision-making level of river and lake basin management, the water quality of a digital twin basin was considered as the starting point and a water quality evaluation platform for Chuancheng River and Baihe River in Nanyang City, Henan Province was established. Based on digital twin technology, the platform establishes a virtual space city model, uses the long short-term memory algorithm to establish a water quality prediction model, draws the distribution of water pollution factors in two dimensions based on Kriging interpolation, simulates the pollutant diffusion in three dimensions based on numerical simulation, and finally builds a visual platform for evaluation and analysis. The platform combines digital twin with three models: one-dimensional (1D) water quality data processing, two-dimensional pollutant distribution, and three-dimensional (3D) pollutant diffusion simulation to achieve visual and comprehensive management of water quality assessment. Compared with the traditional 1D water quality data management platform, the proposed digital twin 3D urban river water quality evaluation platform system solves the problems of low visualization degree, single management, and incomplete analysis, as well as provides a new technical guarantee for the management of urban river water quality. Full article

China has been on a new journey pursuing high-quality development, an important element of which is global value chain (GVC) upgrading. The smart city pilot policy, which aims at reshaping the urban development model in China, is carried out and regarded conducive to achieving high-quality development. Nevertheless, regarding whether and how smart cities could promote GVC upgrading, research is scant. We adopted the approach of time-varying difference-in-differences (DID) and used a dataset that encompassed 174 prefecture-level cities between 2005 and 2017 to investigate the impact of China’s smart city pilot policy on the GVC upgrading of cities. The findings indicate that, firstly, GVC upgrading is significantly enhanced by building smart cities in China. Secondly, this favorable influence on GVC upgrading is mainly through channels of informatization, innovation, and industrial structure adjustment. Thirdly, the influence is more pronounced in eastern cities and cities with better conditions in terms of human capital, fiscal capacity, and information infrastructure. This research provides evidence and policy implications for China to move forward with the smart city establishment in a bid to upgrade GVCs and achieve high-quality growth. Full article

Within the domain of architectural urban informatization, the automated precision recognition of two-dimensional paper schematics emerges as a pivotal technical challenge. Recognition methods traditionally employed frequently encounter limitations due to the fluctuating quality of architectural drawings and the bounds of current image processing methodologies, inhibiting the realization of high accuracy. The research delineates an innovative framework that synthesizes refined semantic segmentation algorithms with image processing techniques and precise coordinate identification methods, with the objective of enhancing the accuracy and operational efficiency in the identification of architectural elements. A meticulously curated data set, featuring 13 principal categories of building and structural components, facilitated the comprehensive training and assessment of two disparate deep learning models. The empirical findings reveal that these algorithms attained mean intersection over union (MIoU) values of 96.44% and 98.01% on the evaluation data set, marking a substantial enhancement in performance relative to traditional approaches. In conjunction, the framework’s integration of the Hough Transform with SQL Server technology has significantly reduced the coordinate detection error rates for linear and circular elements to below 0.1% and 0.15%, respectively. This investigation not only accomplishes the efficacious transition from analog two-dimensional paper drawings to their digital counterparts, but also assures the precise identification and localization of essential architectural components within the digital image coordinate framework. These developments are of considerable importance in furthering the digital transition within the construction industry and establish a robust foundation for the forthcoming extension of data collections and the refinement of algorithmic efficacy. Full article

China’s modernization endeavors to advance both material and spiritual civilization concomitantly; nevertheless, the nation presently faces a pressing issue of urban pollution. This research examines how the introduction of information technology has affected environmental pollution in Chinese cities. By utilizing a panel dataset consisting of 214 prefecture-level cities in China spanning from 2005 to 2017, we employed a time-varying DID model with smart city pilot projects serving as a quasi-natural experiment to assess the impact of informatization on environmental pollution. The establishment of smart cities has remarkably elevated the information quotient of urban areas. Additionally, the results indicate a significant reduction in pollution levels in urban areas as a result of informatization, which remained robust even after conducting a series of rigorous tests to ensure the reliability of the findings. Mechanism analysis shows that informatization of smart cities affects the environmental governance behavior of enterprises and governments. Consequently, the implementation of informatization in smart cities can effectively alleviate environmental pollution by means of both the technique effect and structure effect. This finding calls for the Chinese government to improve informatization by promoting smart city pilot projects to build sustainable cities. Full article

With globalization and informatization, cross-border areas have become increasingly critical interactive spaces, experiencing rapid development and extensive changes in residents’ cross-border travel, constantly changing the spatial patterns of neighboring cities. However, existing studies lack in-depth discussions of the new spatiotemporal characteristics of human activities, spatial pattern evolution, and the driving factors behind them. Therefore, taking the Guangzhou-Foshan metropolitan area as a case, this paper focus on the analysis of the cross-city travel of residents in these border areas in 2019, and investigated the evolution of spatial patterns and the driving forces in the border area during 1985–2020. We found that, instead of the previous one-way attraction pattern caused by the spread of residence, a large number of cross-city trips for leisure and entertainment purposes emerged, and the one-way unbalanced flow, “Foshan to Guangzhou”, changed to two-way circulation. We also explore the scenario in which the travel behavior of urban dwellers in these two cities considerably interacts with the effect of urban structure to produce the observed mobility patterns. Second, we determined the spatial pattern of the Guangzhou-Foshan region from 1985 to 2020 to be on of spreading expansion, with Liwan District as the central core, connecting to several sub-centers. The cross-border area in the Guangzhou-Foshan region represented a compact, extremely high degree of integration and a well-matched functional space. Third, driven by the forces stemming from the planning guidelines and the improving transportation network construction in the border area, the growth points of the two cities continued to expand toward the borderline regarding integrated development, while the growth axis was mainly in the direction of the city border, urban arterial roads, and subway lines. We concluded with development suggestions for increasing travel interactions and optimizing spatial patterns to build a common vision of the whole Guangzhou-Foshan pattern of integration. Full article

Since the reform and opening-up in 1978, a remarkable achievement has been made in poverty reduction in China. Many previous studies have analyzed the poverty reduction effects of economic growth, fiscal expenditure, education levels, information technology, urbanization, foreign trade, industrial development and other factors. As a bridge between production and consumption, the agricultural products circulation industry has an important role on the income growth of rural residents. However, the construction level of China’s agricultural products circulation infrastructure lags behind, resulting in a decline in the efficiency and quality of agricultural products supply, and farmers are also facing the embarrassing situation of increasing production without increasing income. Therefore, in this study, we selected the China’s provincial panel data from 2003 to 2017 to analyze the effect of agricultural products distribution infrastructure in narrowing the income gap between urban and rural residents and poverty reduction in China. First, we review the extant literature and elaborate the poverty reduction path of agricultural products circulation industry; secondly, we build models step by step and select nine variables; lastly, we carry out regression analysis on the overall poverty reduction effect of China’s agricultural products circulation industry, the poverty reduction effect of internal factors of agricultural products circulation industry and regional spatial heterogeneity with Stata software. Our results showed that the development level of the agricultural products circulation industry and the degree of opening-up have significant positive effects on narrowing the income gap between urban and rural residents and poverty reduction varied, with different regions in China. Among all the internal factors of development of agricultural products circulation industry in poverty reduction, the core explanatory variable is the investment in agricultural products circulation infrastructure with the largest poverty reduction effect, followed by the human capital, informatization level and number of employees of the agricultural products circulation industry, and the poverty reduction effects of the four internal development factors have had significant regional differences in China. Our findings further complement the internal mechanism of agricultural product circulation infrastructure on poverty reduction in China, suggest that we should apply appropriate strategies and give priority to the internal development factor of the agricultural product circulation industry, with the largest poverty reduction effect according to local conditions in different regions, and so be better able to achieve the targeted poverty alleviation and offer insights for the rural poverty reduction in other countries, especially in the developing countries. Full article

The optimal design of a building and city, including the balance of their energy performance, must include requirements from a wide range of areas, especially electrical engineering, informatics, technical equipment of buildings, construction and architecture, psychology and many other fields. It is the optimal design, simulation and modelling that are most reflected in the energy requirements of buildings while meeting the requirements of energy sustainability. The impact of buildings and cities on the environment is crucial and unmistakable. It should be emphasized that an inappropriately (architecturally or technologically) designed building with state-of-the-art control technology will still have worse properties than an optimally designed building without a control system. This inspired us to design a building energy model (BEM) with the implementation of a Smart Grid in a decentralized sustainable energy system, which is a microgrid from renewable energy sources (RES). This inspired us to conduct an analysis of simulation models (simultaneous simulations) to show the possibility of their application in the process of fully satisfying energy needs in a given urban region. The main goal is to design an original methodology for the design of smart “Nearly Zero Energy Buildings” (NZEB) and subsequent energy sustainability solutions. This led us to use Hybrid Optimization of Multiple Energy Resources (HOMER), PV*SOL (2D solar software design tool for the photovoltaic system performance), Monte Carlo and DesignBuilder. The EMB was designed based on the Six Sigma design quality management methodology. In the process of integrating Smart Grids with energy efficiency solutions for buildings, an original optimization basis was designed for smart buildings and smart urban areas. The proposed EMB was verified in an experiment. Full article

For the lack of quantitative basis of traffic sign combination information, this paper established a model of information quantity of urban road traffic signs by analyzing the driver’s information processing and the visual recognition of traffic signs combined with theories of informatics. It used various analytical methods to build a model of the relationship between the traffic sign information quantity (TSIQ) and the driver’s visual recognition. Based on factors, the relationship between the TSIQ and the driver’s visual recognition was studied and analyzed to provide a reference for the design of urban traffic sign layout information. The results show that the TSIQ can explain 61% of the driver’s recognition time (DRT). The more information the road traffic sign conveys, the longer DRT will be. The TSIQ’s threshold is 642 bits, and exceeding this value will cause information overload. Different influence factors have a certain impact on drivers’ visual recognition distance (VRD). The male VRD is shorter than the female. The VRD of the young driver is larger than the old driver. The VRD of a novice driver is longer than an experienced driver, while the visual recognition sign of an experienced driver is shorter. Full article

In view of intensified disasters and fatalities caused by natural phenomena and geographical expansion, there is a pressing need for a more effective environment logging for a better management and urban planning. This paper proposes a novel utility computing model (UCM) for structural health monitoring (SHM) that would enable dynamic planning of monitoring systems in an efficient and cost-effective manner in form of a SHM geo-informatics system. The proposed UCM consists of networked SHM systems that send geometrical SHM variables to SHM-UCM gateways. Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. The inputs of the prediction algorithm are geometrical variables, environmental variables, and payloads. The proposed SHM-UCM is unique in terms of its capability to manage heterogeneous SHM resources. This has been tested in a case study on Qatar University (QU) in Doha Qatar, where it looked at where SHM nodes are distributed along with occupancy density in each building. This information was taken from QU routers and zone calculation models and were then compared to ideal SHM system data. Results show the effectiveness of the proposed model in logging and dynamically planning SHM. Full article

Streetscapes have presented a long-standing interest in many fields. Recently, there has been a resurgence of attention on streetscape issues, catalyzed in large part by computing. Because of computing, there is more understanding, vistas, data, and analysis of and on streetscape phenomena than ever before. This diversity of lenses trained on streetscapes permits us to address long-standing questions, such as how people use information while mobile, how interactions with people and things occur on streets, how we might safeguard crowds, how we can design services to assist pedestrians, and how we could better support special populations as they traverse cities. Amid each of these avenues of inquiry, computing is facilitating new ways of posing these questions, particularly by expanding the scope of what-if exploration that is possible. With assistance from computing, consideration of streetscapes now reaches across scales, from the neurological interactions that form among place cells in the brain up to informatics that afford real-time views of activity over whole urban spaces. For some streetscape phenomena, computing allows us to build realistic but synthetic facsimiles in computation, which can function as artificial laboratories for testing ideas. In this paper, I review the domain science for studying streetscapes from vantages in physics, urban studies, animation and the visual arts, psychology, biology, and behavioral geography. I also review the computational developments shaping streetscape science, with particular emphasis on modeling and simulation as informed by data acquisition and generation, data models, path-planning heuristics, artificial intelligence for navigation and way-finding, timing, synthetic vision, steering routines, kinematics, and geometrical treatment of collision detection and avoidance. I also discuss the implications that the advances in computing streetscapes might have on emerging developments in cyber-physical systems and new developments in urban computing and mobile computing. Full article