Intelligent City Construction Research Articles

Research on building extraction from remote sensing imagery using efficient lightweight residual network

Automatic building extraction from very high-resolution remote sensing images is of great significance in several application domains, such as emergency information analysis and intelligent city construction. In recent years, with the development of deep learning technology, convolutional neural networks (CNNs) have made considerable progress in improving the accuracy of building extraction from remote sensing imagery. However, most existing methods require numerous parameters and large amounts of computing and storage resources. This affects their efficiency and limits their practical application. In this study, to balance the accuracy and amount of computation required for building extraction, a novel efficient lightweight residual network (ELRNet) with an encoder-decoder structure is proposed for building extraction. ELRNet consists of a series of downsampling blocks and lightweight feature extraction modules (LFEMs) for the encoder and an appropriate combination of LFEMs and upsampling blocks for the decoder. The key to the proposed ELRNet is the LFEM which has depthwise-factorised convolution incorporated in its design. In addition, the effective channel attention (ECA) added to LFEM, performs local cross-channel interactions, thereby fully extracting the relevant information between channels. The performance of ELRNet was evaluated on the public WHU Building dataset, achieving 88.24% IoU with 2.92 GFLOPs and 0.23 million parameters. The proposed ELRNet was compared with six state-of-the-art baseline networks (SegNet, U-Net, ENet, EDANet, ESFNet, and ERFNet). The results show that ELRNet offers a better tradeoff between accuracy and efficiency in the automatic extraction of buildings in very highresolution remote sensing images. This code is publicly available on GitHub (https://github.com/GaoAi/ELRNet).

Cross-level and multiscale CNN-Transformer network for automatic building extraction from remote sensing imagery

ABSTRACT Automatic building detection from remote sensing images holds significant applications in various domains, including cartography, land-use change detection, urban planning, and 3D intelligent city construction. Driven by the innovation of deep learning technology, convolutional neural networks (CNNs) have emerged as a powerful framework for automatic interpretation, exhibiting hierarchical feature generation and robust representation for building extraction. However, the inherent computational limitations of convolutional operators hinder the acquisition of an effective global receptive field. Recent advancements in deep learning have witnessed the adoption of the multi-head self-attention (MHSA) mechanism by Transformer, presenting the superiority of global context construction. Nonetheless, this network structure encounters difficulties in effectively modelling two-dimensional spatial structure features with scale variation in semantic segmentation and often has huge parameters with high algorithm complexity. To address the above problems, this paper proposed a hybrid deep neural network synergistically harnessing the superiority of CNN and Transformer to extract buildings from remote sensing images. Meanwhile, an improved MHSA mechanism is developed to facilitate the construction of multiscale global representations, concurrently reducing computational complexity. Furthermore, the cross-level MHSA modules the semantic correlation between the deep and shallow-level features to refine spatial fine-grained information. The proposed method was comprehensively evaluated on two building datasets via quantitative analysis and visualization. The experimental results confirmed that the developed network and modules outperform other state-of-the-art methods and can effectively improve the accuracy (93.4% F1-score on the WHU dataset, 89.38% F1-score on the CAMB dataset) with high efficiency for building extraction.

Promoting Urban Innovation through Smart Cities: Evidence from a Quasi-Natural Experiment in China

It is of great theoretical and practical significance to investigate the influence of intelligent city construction on urban innovation. Based on the data of 238 cities in China from 2006 to 2019, this paper utilizes the staggered difference-in-differences (staggered DID) model and the mediating effect model to examine the impact and mechanisms of smart city construction on urban innovation. We find that China’s smart city pilot policies significantly promote urban innovation. Mechanism analysis shows that this innovation promotion effect acts through improving urban informatization, government financial expenditure on science and technology, and the upgrading of the city’s industrial structure. Further analysis shows that smart city construction has a stronger promoting effect on innovation in cities of a larger scale, that located in the eastern region, and have a lower level of science and education. Overall, our findings provide new insights into urban innovation and objectively assess the impact of smart city construction in China.

Framework Design of an Edge Gateway System Supporting Multi-Protocol Standardized Access Detection

Recently, intelligent city construction has been promoted with the development of the Internet of things (IoT). The edge IoT gateway plays a critical role as the data aggregation core and processing center. Most existing gateways mainly solve heavy data storage and processing loads in cloud computing centers. There is less attention paid to multi-protocol data transmission and fusion. However, multiple products with different protocols in an IoT system require a flexible gateway compatible with multiple protocols. This paper proposes a multi-protocol edge gateway. The frame design was based on the actual demand for edge data acquisition. The gateway hardware platform used an RK3399 chip transplanted from the embedded operating system. It could support simultaneous multi-protocol access to ZigBee, LoRa, Bluetooth, and Wi-Fi. We combined the plug-and-play (PnP) hardware device access detection scheme with the system onboard interface driver to realize dynamic access detection and unified device management. In addition, the gateway also integrated data storage and access functions and partial edge computing functions. Finally, the experiment results verified that the multi-protocol edge gateway could meet the demand for data access and device control.

Study on the impact of intelligent city pilot on green and low-carbon development

The intelligent city pilot policy is a major measure in China to promote urban development from factor driven and investment driven to innovation driven. Intelligent city construction can effectively coordinate specialized production factors and information sharing mechanism, promote digital information technology innovation, promote smart industry cluster, and expand ecological scenarios of clean industry application, so as to reduce carbon emissions. This paper reveals the internal mechanism of intelligent city construction to promote carbon emission reduction. Based on the quasi-natural experiments carried out in three batches of pilot construction of intelligent cities since 2012, the difference-in-difference model (DID) is used to identify its impact on urban carbon emissions. The research results show that the pilot construction of intelligent cities is conducive to reducing carbon emissions, which is still robust under multiple scenarios such as placebo test and endogenous test. Heterogeneity analysis shows that the pilot policies have a more significant carbon emission reduction effect on the Beijing-Tianjin-Hebei urban agglomeration, non-resource-based cities, and non-old industrial bases. After further quantitative analysis of 917 pilot policy texts based on Simhash algorithm, Jieba word segmentation, and word frequency statistics, it is found that intelligent industry policies reduce carbon emissions by driving data elements agglomeration and optimizing industrial structure, while intelligent government and intelligent people's livelihood policies improve energy efficiency and reduce carbon emissions through green technological innovation. Counterfactual tests using machine learning algorithms show that the later the pilot batch, the better the sustainable carbon emission reduction effect of intelligent city pilot policies.

The Planning and Construction Path of Innovative and Intelligent Park Cities Based on Big Data Technology

By analyzing the historical background of the times and summarizing the current situation of urban development research at home and abroad, we find that there is a lack of theoretical and practical research related to intelligent park cities. Therefore, this paper first starts with the connotation of park city theory, focuses on the improvement of planning methods, and studies the application paths of big data technology in the planning and construction of park cities. Taking Jinzhai Country as the research object, this paper further illustrates the applicability of this research method at the macrolevel. In the context of the park city, we analyze the problems of the current status of city construction in general and explore the path of “planning concept first, big data-assisted design” for innovative and intelligent city construction. According to the study, the overlook corridor control has an impact on the building height. In terms of landscape protection, overlook system simulation is the other key factor. In addition, the analytic hierarchy process is the basis for development intensity control. The results show that big data technology can assist in the landscape conservation, morphology formation, and efficient operation of Jinzhai Country Park City. Our aim is to achieve the protection and utilization of its ecological environment and natural resources and thus to comprehensively coordinate the multidimensional urban spaces and build a park city model. As an urban development model that meets the requirements of being “people-oriented, efficient, green, and aesthetic” in the new stage, park cities need to be faced by researchers in order to further realize the overall city goal and vision for the whole society to be smart. It also provides relevant design ideas and methods for the planning and construction of park cities in other similar cities or regions.

Rapid Reconstruction of 3D Structural Model Based on Interactive Graph Cuts

The image-based 3D reconstruction technique has been applied in many scenarios of civil engineering, such as earthquake prevention and disaster reduction, construction monitoring, and intelligent city construction. However, the traditional technique is time-consuming, and the modeling efficiency has become a bottleneck limiting its application in emergency scenarios. In this paper, a rapid reconstruction method is proposed which combines the traditional image-based 3D reconstruction technique and an interactive graph cuts algorithm. Firstly, a sequence of images is collected around the target structure. Then, the images are preprocessed using the interactive iterative graph cuts algorithm to extract the target from each image. Finally, the resulting sequence of images is used to perform the 3D reconstruction. During the preprocessing, only a few images require manual intervention while the rest can be processed automatically. To verify the modeling accuracy of the proposed method, a column that has been destroyed is selected as a target for 3D reconstruction. The results show that compared with the traditional method, the modeling efficiency of the fast reconstruction method is doubled. In addition, the modeling accuracy is 97.65%, which is comparable to the modeling accuracy of the traditional method (97.73%); as well, by comparing the point clouds, the alignment between the two models is tremendously close, with tiny difference. The proposed rapid reconstruction method can be applied in emergency scenarios, such as rapid assessment in post-disaster situations.

Research on Intelligent City Talent Information Fusion Management and Talent Training System Optimization Based on Data Mining

Objectives: Smart city is the product of a new round of information technology reform and the further development of knowledge economy. It is a manifestation of the deep integration of industrialization, urbanization and informatization and the progress towards a higher stage. The standardization of smart city construction must be combined with the reality of smart city construction and carry out the standardization work pertinently. Intelligent city construction is accelerating step by step. Internet technology, mobile communication technology and intelligent terminals are combined to infiltrate into all areas of social life. This paper makes full use of the concepts and technological achievements of smart city construction. From the aspects of data regulation and results building, conflict detection and contradiction coordination, results management and resource sharing. Research on the construction of multi-information information fusion visualization system for sharing, unified, efficient and dynamic updating. The open big data teaching mode is used to conduct theoretical study and practical exercises online. Let learners master the necessary knowledge and skills as soon as possible, and provide sufficient and excellent big data talents for enterprises in a timely manner.

Discussion on the Application of Computer Network in Intelligent City

Promoting the construction of intelligent city is a recognized viewpoint at home and abroad at present. Speeding up the construction of intelligent city is an effective grasp to further promote the governance of intelligent city in China and enhance the efficiency of government management. It is also an inevitable choice to innovate and optimize social and economic management, improve people’s livelihood public services, optimize modern industrial structure and promote economic structural transformation. A street lamp control system based on computer network is designed to analyze the application prospect of computer network technology in the future development of intelligent city. The system meets the basic requirements of 0.3 S and 80% in data transmission rate and success rate, respectively.

A scheme for intelligent blockchain-based manufacturing industry supply chain management

Supply chain management as an indispensable component in intelligent city construction has faced great opportunities with the fast development of AI, Internet of Things, big data and mobile communication. Blockchain, as a heated and promising area, features some key characteristics that make it an optimal solution to problems in traditional supply chain management and can also act as a great platform to these cutting-edge technologies. In this paper, a design scheme of integrated platform for information service provided by participants in supply chain and based on Ethereum blockchain is proposed. System architecture and smart contracts are designed to guarantee the security enhancement from blockchain can be fully exploited. Some common and vital problems in the blockchain-based scheme are also discussed and solved, among which a data-driven credit evaluation scheme workable on chain is put forward and a cross-chain architecture is designed to make the system more secure, intelligent and scalable.

Exploration on the Development Mode of Engineering Management Informatization in BIM Times

In order to speed up the construction of project management informatization in China, we have investigated and studied the Internet-based information platform and characteristics of project management in Europe and the United States. The author creatively puts forward the overall goal, design principle and technical framework of engineering management informatization in China. And then this paper points out that the ideal path for integrating BIM GIS into CIM, which will support the construction of intelligent city. Through the research and judgment of government organization, construction main body and commercial platform R&D mode, we must seize the historical opportunity of informatization and promote the transformation and upgrade of enterprises. Only in this way, can we improve the level of government administration and promote the reform development of construction industry in our country.

Visual module based on VSLAM

With the rapid development of science and technology, VSLAM (real-time positioning and map construction technology) has been widely used in AR/VR, robots, drones and unmanned aerial vehicles and other fields because of its unique theory and application value in the era of artificial intelligence. However, there are still difficulties on indoor and outdoor positioning navigation and image scene understanding, such as auxiliary rescue after disaster, inspection of large factories, etc. In addition, the combination entity of VSLAM and artificial intelligence has not realized the popularization of consumption level. A vision system positioning module based on VSLAM technology can be transferred to be the carrier of any intelligent robots, which can be used in post-disaster auxiliary rescue, intelligent inspection of large factories, intelligent logistics sorting field and the construction of intelligent city in the future. People can save rescue time, help save life, reduce economic loss and the safety risk of rescue personnel on the auxiliary disaster rescue and intelligent inspection with it. At the same time, it can help achieve intelligent logistics sorting (and its scope expansion) by setting up network with 5G (5th generation wireless systems) in logistics community distribution.

Establishment of Urban Real Estate Archives Information Management Platform Based on BIM Cloud Technology

The modern information technology, represented by real estate file information model (BIM), cloud platform and big data, has developed rapidly in the development and management of urban real estate, and the basic framework of intelligent city (CIM) based on big data and information model has been gradually formed. There are many problems in urban real estate archives management in China, such as insufficient information, low visualization and intelligence, which can not meet the needs of various professional applications, including real estate evaluation and transaction, real estate maintenance and management, and the future needs of intelligent cities for urban real estate information sharing and intelligent management. By using BIM cloud technology, this study can solve the problem of 3D visualization and management information of real estate archives in the receiving and keeping of real estate archives. It plays an active role in realizing the intelligence of real estate archives and the construction of intelligent city in the future.

Research on urban anti-terrorism intelligence perception system from the perspective of Internet of things application

Objective/significance Based on the urgent needs of the status quo of urban anti-terrorism, combining the present situation of intelligent city construction, we carry out the research on the key problems such as the collection and analysis of counter-terrorism information for urban environment. This paper puts forward a kind of city anti-terrorism information perception system based on the Internet of things, and realizes to improve the level of surveillance and early warning of terrorist activities facing the urban environment. Method/Process The system collects and merges the heterogeneous information of terrorism, which is based on the information perception layer, the intelligence identification layer and the intelligence inference layer, which is based on the city's focal area. To filter suspicious information by constructing a semantic database of terrorist action signals Combined with complex event processing and machine learning technology, real-time monitoring and mining prediction of mass event flow, using the comparison between historical data of terrorist attacks and real-time data, increased the area of counter-terrorism intelligence. Results/Conclusions We hope to provide a better model and an exploratory study on the construction of the counter-terrorism early warning for the urban environment.

Study on the Construction and Application of 3D Geographic Information Services for the Smart City

Abstract. Smart City, whose main characteristics are intelligence and interconnection capability, has become an important goal of some cities’ development. This paper, based on urban three-dimensional geographic information characteristics, analyses 3D geographic information requirements in the Smart City construction and development process, proposes construction and management methods for 3D geographic information. Furthermore, this paper takes Shanghai Geographic Information Public Service Platform as an example, discusses 3D geographic information application in multiple fields, and proves that it is an effective ways to promote Intelligent City construction.

Thinking of the Planning and Construction of Intelligent City

With the rapid development of space technology, the global strategic model towns, intelligent city as an important way of new-type urbanization plays in the urbanization wave of a new round of the role. The article first defines the concept and characteristics of Intelligent City, and expounds the planning strategy of intelligent city from the point of view of city planning.