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Smart city article details

Title Application Of Remote Sensing Techniques In The Construction And Management Of Smart Cities
ID_Doc 9979
Authors Ismayilov J.; Binnataliyeva T.
Year 2024
Published Lecture Notes in Networks and Systems, 1251 LNNS
DOI http://dx.doi.org/10.1007/978-3-031-81567-6_8
Abstract The development of digital technologies has a positive effect on all areas of industry and agriculture. It should also be noted that the use of digital technologies in many cases is both economically efficient and, on the other hand, increases the accuracy of the results. Recently, smart city concepts have been put forward in many countries of the world, and intensive work is being carried out in this area. Building a smart city is a complex process that involves the use of multiple technologies. Currently, remote sensing (RS) technology and related integration methods are widely used to assist in smart city construction. Until recent times, RS technologies were used only in the design and planning of residential areas, environmental monitoring of the construction area, but now RS has become one of the important technologies in the construction and management of smart cities. Compared to traditional methods, RS technology usually has the advantages of high efficiency and low cost. At the same time, it should be noted that RS and other related digital technologies and methods can be applied to various aspects of smart city construction. For example, it can be used in conducting environmental monitoring during the use of city transport, monitoring illegal buildings, monitoring the landscape of the city and, in other words, green areas, monitoring oil pollution that may occur in the Caspian Sea, and other issues. Regarding urban traffic pollution monitoring, RS-related technologies have a positive correlation accuracy in traffic pollution monitoring. Currently, satellite systems equipped with advanced optical and radar sensors allow obtaining 3D images, which are also widely used in the smart city concept. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Author Keywords Change detection; Deep learning; Internet of things; Remote sensing; Smart city


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