Journal articles on the topic 'Intelligenza urbana'
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1
Tricarico, Luca, Rosamaria Bitetti, and Maria Isabella Leone. "L'innovazione sociale nelle politiche urbane. Un caso studio nel contesto italiano." TERRITORIO, no. 96 (September 2021): 108–15. http://dx.doi.org/10.3280/tr2021-096010.
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Il contributo analizza i caratteri di una politica urbana che applica e incorpora concetti e approcci tipici dell'innovazione sociale. Con questo obiettivo, esamina un caso studio, ‘Un acceleratore per l'economia di territorio', promosso dal comune di Milano con una serie di partner locali e inserito nel framework governativo del Fondo per l'innovazione sociale (fis). Il progetto per la creazione di ‘economie di prossimità' sarà realizzato combinando strumenti finanziari a impatto sociale e percorsi di accelerazione per lavoro e impresa nelle aree periferiche. L'ipotesi che si vuole qui verificare è se l'innovazione sociale possa essere non solo il contenuto, ma anche il metodo di una politica place-based di sviluppo territoriale: acquisendo conoscenza dispersa, innescando processi di intelligenza collettiva nella ridefinizione dei bisogni sociali e proponendo soluzioni condivise dall'interesse di più attori.
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Tricarico, Luca, Rosamaria Bitetti, and Maria Isabella Leone. "L'innovazione sociale nelle politiche urbane. Un caso studio nel contesto italiano." TERRITORIO, no. 96 (September 2021): 108–15. http://dx.doi.org/10.3280/tr2021-096010.
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Il contributo analizza i caratteri di una politica urbana che applica e incorpora concetti e approcci tipici dell'innovazione sociale. Con questo obiettivo, esamina un caso studio, ‘Un acceleratore per l'economia di territorio', promosso dal comune di Milano con una serie di partner locali e inserito nel framework governativo del Fondo per l'innovazione sociale (fis). Il progetto per la creazione di ‘economie di prossimità' sarà realizzato combinando strumenti finanziari a impatto sociale e percorsi di accelerazione per lavoro e impresa nelle aree periferiche. L'ipotesi che si vuole qui verificare è se l'innovazione sociale possa essere non solo il contenuto, ma anche il metodo di una politica place-based di sviluppo territoriale: acquisendo conoscenza dispersa, innescando processi di intelligenza collettiva nella ridefinizione dei bisogni sociali e proponendo soluzioni condivise dall'interesse di più attori.
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Zhou, Xi, Mengnan Wang, Dexiang Deng, and Xi Li. "Design and Construction of Urban Waste Intelligent Treatment System." E3S Web of Conferences 199 (2020): 00011. http://dx.doi.org/10.1051/e3sconf/202019900011.
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With the rapid expansion of urban scale, urban waste disposal has become an important issue for ecological environment construction. In order to seek the coordinated development of economy and environment, we systematically intervene in urban waste intelligent treatment plans and management through design thinking and methods, and build urban waste intelligent treatment systems to achieve waste volume control, waste monitoring, classified collection, stacking and transportation, processing and Reprocessing production forms a controllable intelligent operation chain, which realizes the collaboration of human brain intelligence and artificial intelligence to improve the level of urban waste treatment and management capabilities.
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Wang, Ji Zhe, and Zhan Jie Wang. "Architecture Design of Urban Intelligent Transportation Using Cloud Computing." Advanced Materials Research 605-607 (December 2012): 2549–52. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2549.
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This article does a further research on the technologies of cloud computing and intelligent public transportation, designs a human-centered intelligent public transportation system, improves the connection between passengers and vehicles, vehicles and vehicles. Technologies of BeiDou messaging, capacity sensor, RFID and Web are used to improve the intelligence of public transportation information platform. This article makes an architecture design in intelligent transportation based on cloud computing and uses the embedded system as the core. The architecture allows passengers to obtain needed vehicles’ information through various services whenever and wherever, and strongly supports intelligent control and schedule of multi-vehicles and multi-lines. The system lays a good foundation for the intelligent city.
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Gong, Fanghai. "Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm." Advances in Multimedia 2022 (September 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/5178515.
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In order to transform three-dimensional space path planning into two-dimensional plane path planning problem and greatly reduce the search time, an intelligent heuristic search algorithm based on artificial intelligence is proposed. The heuristic search algorithm is analyzed and introduced, and A is chosen. A two-dimensional spatial environment model of picking robot path planning is investigated, and a spatial model of picking robot path planning is established by raster method. Then, considering the whole day operation time, the whole day operation time is divided into several periods. With the help of heuristic search algorithm, the most reasonable operation time interval of each period is found, so as to provide reliable reference for the decision-making organization of urban rail transit operation on how to arrange the train rationally. The experimental results show that the improved A ∗ algorithm can significantly improve the moving path of the picking robot and make the planned path smoother, which confirms the feasibility and superiority of the improved algorithm. The operation decision of urban rail transit is obtained through experiments. After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635 e -001, while the average optimal value is 6.83551939 e -001. After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785 e -001. The average optimal value is 6.83745935 e -001. After 789 iterations, the genetic algorithm obtains the optimal value of 6.83921100 e -001, and the average optimal value is 6.84410765 e -001. Through the comparative analysis, it can be seen that compared with the other two optimization algorithms, the heuristic search algorithm is significantly better than the other two optimization algorithms, both in terms of the optimal value and the number of optimization iterations. The results show that the heuristic search algorithm is a fast, accurate, and reliable optimization method to solve the problem of accurate scheduling of urban rail transit departure interval. It is proved that the intelligent heuristic search algorithm of artificial intelligence computer can realize the path planning effectively.
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Xu, Binjie. "Risk Assessment of Green Intelligent Building Based on Artificial Intelligence." Computational Intelligence and Neuroscience 2022 (September 15, 2022): 1–8. http://dx.doi.org/10.1155/2022/7584853.
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Green smart building is the development direction of future architecture. It is of great significance to carry out risk assessment. Fire risk is the key content of building risk, so this paper takes fire risk as the research object, with the help of artificial intelligence technology, to carry out the risk assessment research of green smart buildings. With the rapid development of the economy, urban fire risk factors are increasing, and the fire situation is becoming more and more serious. Building fire risk assessment is an important measure to effectively prevent and control urban building fires. This paper uses Internet of Things data to carry out fire risk assessment and realize Internet of Things data mining. Collect a large number of expert samples to build training samples, train the green intelligent building monomer fire risk assessment and prediction model based on deep neural network, constantly adjust the model parameters to optimize the model, and finally verify and modify the model.
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Yang, Xuan, Zhiyan Pu, and Lei Zhang. "Designing Data Visualization Using Artificial Intelligence for Urban Intelligent Transportation Scenarios." Mobile Information Systems 2022 (August 27, 2022): 1–11. http://dx.doi.org/10.1155/2022/3967267.
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Artificial intelligence refers to a simulation extension and expansion technology that has found its presence in various applications and research domains. Artificial intelligence allows the related theories to portray similar to human intelligence. It combines developments in several fields, including computer science, statistics, and linguistics. The research objects of data visualization can be divided into three aspects: data, visualization technology, and visualization performance. This paper aims to study the data visualization design of artificial intelligence in urban intelligent transportation scenarios. It predicts the traffic flow via the traffic control method using neural network. It provides an effective way for timely dredging and alleviating problems, such as traffic jams and establishing alternative routes. This paper firstly analyzes the methods of artificial intelligence, traffic control methods, and data visualization and then designs the visualization based on artificial intelligence in traffic scenarios. By comparing the accuracy analysis of different models, the experimental results show that the error of the peak traffic flow is less than 10% and the lowest error value is 2.2%.
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Cao, Min. "Architecture and application of intelligent heating network system based on cloud computing platform." Thermal Science 25, no. 4 Part B (2021): 2889–96. http://dx.doi.org/10.2298/tsci2104889c.
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The vigorous development of Internet-related technologies such as big data, the IoT, and cloud computing has brought intelligent central heating networks? intelligent upgrade opportunities. The article discusses the current situation of the urban central heating system and its intelligence and analyzes the new characteristics of the intelligent central heating network under the new situation. Because of the existing central heating system?s existing problems, we have designed a complete set of sys?tem architecture and heating networks? application plans.
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Pal, Santosh. "STUDY OF SPIRITUAL INTELLIGENCEAMONG D.EL.ED. STUDENTS." International Journal of Research -GRANTHAALAYAH 7, no. 7 (July 31, 2019): 143–47. http://dx.doi.org/10.29121/granthaalayah.v7.i7.2019.740.
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The present study has been conducted to explore the status of development of spiritual intelligence among D.El.Ed. students. 92 students were selected as the sample for the study. Spiritual Intelligence Scale (SIS) developed by K. S. Misra was used to collect the data from students of D.El.Ed. I and III semester. t-ratio was computed to analyze the data. The significant gender, and locality differences in spiritual intelligence score are found. Male students are found more spiritually intelligent than females. Urban students had greater spiritual intelligence than rural students. No significant difference was found in the spiritual intelligence of D.El.Ed. I and III semester students.
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Maldonado Silveira Alonso Munhoz, Paulo Antonio, Fabricio da Costa Dias, Christine Kowal Chinelli, André Luis Azevedo Guedes, João Alberto Neves dos Santos, Wainer da Silveira e Silva, and Carlos Alberto Pereira Soares. "Smart Mobility: The Main Drivers for Increasing the Intelligence of Urban Mobility." Sustainability 12, no. 24 (December 21, 2020): 10675. http://dx.doi.org/10.3390/su122410675.
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Urban mobility plays a key role in the ecosystems of complex smart cities. It is considered a key factor in enabling cities to become more intelligent, which highlights the importance of identifying the drivers that improve the intelligence of cities. In this study, we investigate the main drivers with the potential to increase urban mobility intelligence and assign them a priority. Following on from a systematic review of the literature, we conducted broad and detailed bibliographic research based on the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). We also surveyed 181 professionals working in the field concerned to confirm the importance of different drivers and assign them a level of priority. The results show that 27 drivers identified in the literature were considered important, of which seven, related to city governance and technical solutions, were considered the most important to increase urban mobility intelligence.
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Wu, Yun Na, and Ru Hang Xu. "Intelligent Research for Chinese Intelligent Urban Construction Problems and Solutions - Intelligent Traffic Forecast." Advanced Materials Research 951 (May 2014): 3–6. http://dx.doi.org/10.4028/www.scientific.net/amr.951.3.
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Smart city is a promising form for future city management. Intelligent transportation plays an important role in the smart city. Traffic forecast is an important way to realize intelligent traffic. This paper proposed a method to solve the complex mapping problem in traffic forecast based on BP artificial neural intelligence method. Data of the City of Alexandria in the U.S. is used to testify the feasibility of the method. The result shows that this method shows good performance in solving complex mapping problem.
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Hong, Chao, Jianmin Shi, Yan Xing, and Zejun Chang. "Research on the Coupling and Coordinated Development of Sports Tourism and Cultural Industry under the Background of Artificial Intelligence Era." Wireless Communications and Mobile Computing 2022 (April 11, 2022): 1–6. http://dx.doi.org/10.1155/2022/3191655.
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In the new era of rapid development of intelligent information, sports tourism and cultural industry have become a new goal to improve China’s urban competitiveness and realize the development of urban industry. Based on the integration of sports tourism industry and cultural industry, this paper establishes the relevant information data interface mode. This paper constructs the information coupling system model of sports tourism industry and cultural industry under the background of artificial intelligence era and obtains the corresponding data results by using the invisible statistical logic computer independent judgment (IDIJA) method of artificial intelligence system under the condition of incomplete data. The application of the coordinated development system of coupling industry can realize the rapid development of sports tourism and cultural reconstruction mode and achieve the new effect of intelligent sports tourism cultural comprehensive experience. It can not only improve the people’s quality of life but also provide feasible suggestions for improving the continuous development of the coupling and coordination of sports tourism and cultural industry.
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Cao, Yaoguang, Yuyi Chen, and Lu Liu. "Research prospect of autonomous driving decision technology under complex traffic scenarios." MATEC Web of Conferences 355 (2022): 03031. http://dx.doi.org/10.1051/matecconf/202235503031.
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Decision-making system is the essential part of the autonomous vehicle “brain”, which determines the safety and stability of vehicles, and is also the key to reflect the intelligent level of autonomous vehicles. Compared with simple scenarios such as expressway, urban traffic scenarios have the characteristics of complex and frequent interaction between traffic participants. Carrying out in-depth research on complex traffic scenarios and optimizing autonomous decision-making algorithms are the key methods for the purpose of promoting the application of autonomous driving technologies. In the future, we can further combine the artificial intelligence methods such as cognitive or knowledge map, behaviour prediction of traffic participants, and humanoid intelligence, so as to enhance the intelligent level of autonomous driving.
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Lin, Qiang. "Research on Traffic Informatization and Intelligent Construction Based on Urban Traffic Big Data." Academic Journal of Science and Technology 4, no. 2 (January 4, 2023): 125–28. http://dx.doi.org/10.54097/ajst.v4i2.4121.
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Urban traffic is a new traffic demand network defined by residents' travel behavior and community relationship. From the management level, we should actively study and explore the construction of urban traffic informatization and intelligence, strengthen the operation efficiency of infrastructure and the dynamic supervision of traffic in various fields and subsystems of the city, and promote the integrated management of urban network operation, management, emergency response, treatment and maintenance. Under the background of big data, build an information and intelligent system of urban traffic to solve the problems of poor standardization, low level of digitalization, poor sharing and wide sources of existing cost control information. From the perspective of system architecture and function, the framework of urban traffic informatization and intelligent system should include four levels, namely, perception layer, network layer, data layer and application layer. The information system under this construction idea can comprehensively collect the operation and management data of urban transportation enterprises, and then analyze all kinds of operation indicators.
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Shan, Pengyu, and Wan Sun. "Data-Driven Winter Landscape Design and Pleasant Factor Analysis of Elderly Friendly Parks in Severe Cold Cities in Northeast China under the Background of Artificial Intelligence." Security and Communication Networks 2022 (August 17, 2022): 1–11. http://dx.doi.org/10.1155/2022/8218468.
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Urban parks not only combine the greening of the city with the natural landscape but also are places for people’s daily fitness, leisure, entertainment, and activities to meet their psychological needs. At present, the design of our country’s northeast severe cold city park is not perfect, which cannot fully highlight the regional characteristics and show the local winter natural landscape. Under the background of the lagging development of the northeast severe cold city park, we use artificial intelligence technology and data-driven algorithm to design a new northeast severe cold city elderly friendly park. The experimental results are as follows: (1) we analyze the development trend of population aging in our country. As the main demanders of urban parks, the elderly determined the research direction of the experiment, investigated the needs of different people for the park, and designed the function of the park according to the needs of the park. (2) On the basis of retaining the traditional garden design, show artificial intelligence technology in the design of urban parks and transforming the urban park design with intelligent construction can not only let tourists have better entertainment and exercise but also enable residents to better invest in the park surroundings. Intelligent park design can not only show the unique park landscape but also relieve the pressure of tourists.
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Wang, Jing, Dang Que Nguyen, Tatiana Bonkalo, and Oleg Grebennikov. "Smart governance of urban data." E3S Web of Conferences 301 (2021): 05005. http://dx.doi.org/10.1051/e3sconf/202130105005.
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This paper focuses on the smart governance of urban data. Recently, the idea of an intelligent city has gained increased attention among technologists, urban scientists, stakeholders, companies and policy makers in the last decades. The new paradigm of the cities in the 21st century and what it entails is seen by everyone, including the authors of this article, as a viable response to the unprecedented rate of urbanization most nations are experiencing. Advanced smart cities are beginning to go beyond infrastructure and to use big data. The whole idea behind smart cities is to harness intelligent technologies and data-driven contextual governance models to mitigate and prevent the challenges that arise when an estimated 2 billion people move to urban areas. This is why collecting and analysing urban data becomes a key priority in this field. The development of Big Data analysis using the Artificial Intelligence (AI) becomes the domain of urban governments and stakeholders. This research contemplates over these issues and provides many examples from around smart cities around the world that can be used as reference points or inspiration for the policy-makers engaged in the smart city governance and urban planning.
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Zhang, Qi, Hongyang Li, Xin Wan, Martin Skitmore, and Hailin Sun. "An Intelligent Waste Removal System for Smarter Communities." Sustainability 12, no. 17 (August 22, 2020): 6829. http://dx.doi.org/10.3390/su12176829.
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With the continuous progress of urbanization, the discharge of municipal solid waste has profoundly affected human production/living and social ecological health, and waste disposal has become one of the key issues all over the world. In the context of intelligent technology, this paper innovates the way of waste disposal according to the development direction of a smart city and the requirement of sustainable development strategy. An intelligent urban waste removal system is developed using a ROS (Route Operation System) robot operating system and RRT (Rapid Exploration of Random Trees) path planning algorithm. With a background of data management, the entire process of intelligent automatic waste removal is triggered by automatic communication from individual waste bins to a waste collection vehicle (WCV) where the bin needs to be emptied, and the automatic collection and transportation by the WCV in response. In combination with the IoT (Internet of Things), the system provides scientific data support for the intelligent layout of communities and even urban waste bins to greatly enhance the development of intelligence communities and smart cities.
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Lv, Chengshuang, Jiaojiao Xu, and Caihui Wang. "Intelligent Strategies to Improve Food Safety Supervision Model." International Journal of Education and Humanities 1, no. 1 (December 15, 2021): 21–27. http://dx.doi.org/10.54097/ijeh.v1i1.197.
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Intelligent supervision effectively deals with food safety problems from four aspects: concept, subject, activity and object. This paper makes a qualitative analysis on the current situation of intelligent supervision of food safety in Beijing, Tianjin and Hebei, compares and studies the intelligent supervision modes of food safety in three coastal areas in eastern China, constructs the analysis framework of intelligent supervision of food safety, and improves the intelligent supervision mode of food safety in Beijing, Tianjin and Hebei. By studying the policy path of intelligent supervision of food safety, extract the three-stage three source stream model of supervision mode from standard cultivation, informatization to standard unification and intelligence, to better promote the intelligent supervision mode in the country. For the challenges still faced by food safety supervision, it is proposed to improve the top-level design and strengthen the intelligent supervision mechanism of cross regional coordination; Promote the cooperation and sharing of data resources and optimize the cross regional risk early warning mechanism; Consolidate the rural digital foundation and realize the integration mechanism of urban and rural food safety supervision.
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Zhihui, Gao, and Zou Guangtian. "Intelligent Data Mining of Computer-Aided Extension Residential Building Design Based on Algorithm Library." Complexity 2021 (February 18, 2021): 1–9. http://dx.doi.org/10.1155/2021/6690746.
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In recent years, with the development of construction industry, more scientific, systematic, fast, and intelligent calculation methods are needed to coordinate urban development and fierce market competition, and mathematical algorithm library plays an important role in artificial intelligence. Therefore, the author uses computer mathematical algorithm and extension theory to study and analyze the residential building design and intelligent data mining. It is found that the research of the computer-aided expression method of extension building planning is mainly the expression of the input and output system of extension building planning. It includes knowledge representation, system outline design, system flow, and interface expression based on the mathematical database.
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Gagarina, S. N., N. N. Chausov, and V. N. Levkina. "IMPROVING THE EFFICIENCY OF URBAN TRANSPORT INFRASTRUCTURE BASED ON DIGITAL TECHNOLOGIES." Vestnik Universiteta, no. 7 (September 7, 2020): 68–75. http://dx.doi.org/10.26425/1816-4277-2020-7-68-75.
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The need to improve the efficiency of transport infrastructure, which is an important subsystem of urban services as a determinant of the quality of life of the city’s population, has been substantiated. The factors that determine the quality of the urban transport system, the features of urban transport have been highlighted. Transport infrastructure development in Russia has been analysed. It has been proved that in the conditions of the formation of the digital economy, artificial intelligence systems are an effective tool for decision-making. In the formation of intelligent systems for managing urban transport flows, the use of network models has been proposed, for which mathematical methods are necessary to obtain not only point, but also interval estimates of the model parameters, taking into account a priori uncertainty.
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Saci, Houda, and Ewa Berezowska-Azzag. "Sécurité alimentaire et durabilité urbaine des modèles alimentaires alternatifs : analyse multicritère basée sur les objectifs de développement durable et l’aménagement urbain durable." Cahiers Agricultures 30 (2021): 35. http://dx.doi.org/10.1051/cagri/2021019.
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Cet article présente une évaluation théorique de la performance urbaine des modèles alimentaires alternatifs dans la prise en charge des objectifs de développement durable (ODD) en vue d’améliorer la sécurité alimentaire urbaine. Elle concerne les modèles des systèmes alimentaires les plus relatés dans la littérature, à savoir le système alimentaire territorialisé (SAT), le City-Region Food System (CRFS) et le système alimentaire urbain intelligent (SAUI) en émergence. Ce travail s’ancre dans le champ du développement urbain durable et pose comme hypothèse l’existence d’une corrélation entre la proximité urbaine des modèles alimentaires alternatifs et leur performance dans l’intégration des objectifs de développement durable. L’évaluation est basée sur une analyse multicritère à scores qui croise deux approches évaluatives déclinées en cibles : une approche normative par les objectifs de développement durable et une autre opérationnelle par l’aménagement urbain durable (AUD). La méthode proposée se veut holistique et systémique contrairement aux méthodes d’évaluation de durabilité agricole existantes. Les scores sont interprétés par des taux d’adéquation des cibles de l’aménagement urbain durable aux objectifs de développement durable et d’appropriation de ces derniers par les domaines de l’écosystème urbain. Les résultats montrent des profils de durabilité des modèles laissant supposer une complémentarité fonctionnelle entre eux. Cependant, c’est le système alimentaire urbain intelligent qui serait le modèle le plus performant avec des taux supérieurs au seuil minimum global de durabilité, suivi par le City-Region Food System, ce qui confirme notre hypothèse de départ. La discussion des résultats pointe les limites de l’évaluation en termes d’objectivité de l’approche, de contextualisation de l’analyse et des contraintes d’applicabilité du système alimentaire urbain intelligent. Enfin, l’étude ouvre une perspective de recherche sur la modélisation d’un système alimentaire urbain intelligent opérationnel, dont ce travail constitue le premier pas.
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Dash, Bibhu, and Pawankumar Sharma. "Role of Artificial Intelligence in Smart Cities for Information Gathering and Dissemination (A Review)." Academic Journal of Research and Scientific Publishing 4, no. 39 (July 5, 2022): 58–75. http://dx.doi.org/10.52132/ajrsp.e.2022.39.4.
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The rise in urban population and technological innovation has resulted in climatic, technological, and economic changes that can severely impact the value of life in cities. In reaction to the changes, the idea of smart cities has been developed, which refers to the novel application of information communication technology to minimize the severe impacts on the cities and their occupants. Artificial Intelligence is among the technologies being adopted to develop smart cities. Research shows that Artificial Intelligence (AI) is improving rapidly, and it plays a substantial role in helping intelligent city-wide systems in various domains. Thus, it is vital to decide the modern research advances to realize the role played by Artificial Intelligence in smart cities for intelligence gathering and dissemination. Also, there is a need to analyze the relationship between Artificial Intelligence and smart cities scientifically. To identify this relationship, this research paper will focus on the role of Artificial Intelligence, its applications, and the challenges associated with concepts and technologies identified as Artificial Intelligence in smart cities. Therefore, this research paper attempts to give insights into Artificial Intelligence's role in smart cities for intelligence gathering and dissemination.
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Chen, Yuou. "Research on Application of Computer Artificial Intelligence Technology in Intelligent Substation Monitoring System." Highlights in Science, Engineering and Technology 1 (June 14, 2022): 182–87. http://dx.doi.org/10.54097/hset.v1i.459.
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Aiming at the problem of the large number of devices and no backup in the intelligent substation monitoring system with the measurement and control devices configured at intervals, a new system architecture of the intelligent substation monitoring system is proposed. The article adopts the method of intelligent control to realize the accurate triggering of the data signal in the test process. The test system automatically captures and parses MMS messages and generates test reports to achieve the optimization of data processing closed-loop testing. Finally, a distributed improvement was made to the traditional centralized construction scheme of urban indoor substations, and the economic benefit analysis proved the scientific and economy of the new scheme.
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Wang, Ying, and Xu Zhang. "Autonomous garbage detection for intelligent urban management." MATEC Web of Conferences 232 (2018): 01056. http://dx.doi.org/10.1051/matecconf/201823201056.
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With the development of smart city in major cities at home and abroad, especially the management of smart city, how to improve the intelligence level of urban environment monitoring and evaluation has become an important research topic. It is of great value to rapidly and accurately detect garbage from urban images in the application of intelligent urban management. This paper aims to adopt a deep learning strategy for automatic garbage detection. By training a Faster R-CNN open source framework with region proposal network and ResNet network algorithm, we look over garbage detection results on garbage images. In addition, to improve the accuracy of the method, a data fusion and augmentation strategy is proposed. As a result, experiments show that the method has favorable generalization ability and high-precision detection function.
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WU, C. Z., X. P. YAN, G. H. HUANG, and Y. P. LI. "AN INTELLIGENT AGENT MOBILE EMISSIONS MODEL FOR URBAN ENVIRONMENTAL MANAGEMENT." International Journal of Software Engineering and Knowledge Engineering 18, no. 04 (June 2008): 485–502. http://dx.doi.org/10.1142/s0218194008003751.
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In this study, we developed a microcosmic mobile emissions model based on an intelligent agent model of vehicles. The intelligent agent was first introduced into a micro-traffic flow system. Individual differences in driver behavior were considered, and the theory of probability was applied to reflect the distribution of drivers' stochastic characteristic dispositions. Each vehicle expressed its intelligence through its own character by perceiving the leading vehicle. From an operational perspective, differences in drivers' dispositions were reflected by a weighted coefficient. Finally, a hybrid microcosmic mobile emissions model was proposed. Its coefficients were determined using traffic data and experiments. Because it addresses more aspects of the car-following process, this model is theoretically superior to previous models, as verified by a numerical simulation. The proposed model was applied to a case study of the emissions from ten vehicles in an urban setting. The model effectively estimated mobile emissions rates. The results indicate that the model can reflect individual differences among drivers and demonstrate that reckless drivers generate more emissions.
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Liu, Xingyu. "Vehicle Route Planning Using A* Algorithm in Real-world Roads." Journal of Physics: Conference Series 2400, no. 1 (December 1, 2022): 012040. http://dx.doi.org/10.1088/1742-6596/2400/1/012040.
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Abstract With the technical progress in the fields of robotics as well as artificial intelligence, many intelligent algorithms which focus on robot path planning problems have been developed so far. A* algorithm is an efficient and technically mature path planning algorithm that can efficiently solve robot path planning problems. In this context, this paper proposes an improved A* algorithm to plan roads for automobiles in urban areas, introduce time factors into the cost function, select an urban area, use grid map modeling, and simulate in the MATLAB environment. The final result shows that this kind of algorithm can efficiently solve the problem of automobile road planning.
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Mi, Shuo, and Lanqi Yang. "The Application of Artificial Intelligence in the Field of Transportation." SHS Web of Conferences 144 (2022): 03001. http://dx.doi.org/10.1051/shsconf/202214403001.
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Urban traffic is the lifeblood of urban economic activities and plays a very important role in the development of the urban economy and the improvement of people’s living standards. Although the automobile industry brings convenience, it also brings a heavy burden to urban traffic. The imbalance of urban traffic supply and demand has become a serious problem faced by major cities, especially in large cities, the phenomenon of traffic congestion. This not only affects the normal operation of the city, but also reduces the daily work efficiency of people. This paper is based on mature scientific principles and physical devices, such as dynamic Bayesian network, machine vision, machine learning, pattern recognition technology, temperature sensor, optical fiber sensor, etc. The application of artificial intelligence technology in highway traffic is discussed in detail, which lays a theoretical foundation for the development of intelligent traffic in the future.
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Babu, Dr A. Mahesh, Barapati Akhil, and Naveen Kumar Pochampally. "Smart Cities and Intelligent Transport Systems." International Journal of Applied and Structural Mechanics, no. 31 (January 28, 2023): 22–25. http://dx.doi.org/10.55529/ijasm.31.22.25.
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The integration of technology into cities and transportation networks has the potential to improve the quality of life for residents, reduce congestion and pollution, and increase the overall efficiency of urban cities and their transportation system. Smart cities use technology to improve the efficiency and sustainability of urban areas. This can include things like smart lighting, the internet of things (IoT), energy management, artificial intelligence and smart transportation systems. An intelligent transport system is a component of a smart city that uses technology, to improve the efficiency and safety of the transportation network. This can include things like traffic management systems, real-time passenger information, and intelligent traffic signals. Together all smart cities and ITS can help to reduce congestion, improve air quality, and make cities more liable to residents. Intelligent transport systems (ITS) can revolutionise the way people commute in metro cities. ITS offer a wide range of approaches to providing multiple transportation types, advanced infrastructure, and traffic mobility management solutions. It uses several electronics, wireless and communication technologies to provide consumers with access to a smarter, safer, and fast way to travel around the city
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Zheng, Zhilei, and Chuan Jiang. "A Mode of Intelligent Equipment Monitoring Optimization Based on Dynamic Programming Algorithm." Computational Intelligence and Neuroscience 2022 (March 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/1569428.
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With the continuous development of the national economy and scientific productivity, urban construction and people’s living standards are also getting higher and higher. Although people enjoy increasingly convenient life, the demand for intelligence is getting higher and higher. Digital intelligent equipment has the functions of data collection, calculation and analysis, diagnostic and early warning, and communication functions. Analyze the status quo and existing problems of the development of intelligent equipment, as well as analyze and research key monitoring technologies in the use and development of digital intelligent equipment and provide optimal solutions for intelligent equipment hardware development requirements, software development, and model algorithms. Intelligent equipment monitoring is related to all aspects of people’s livelihood, and its intelligent development is related to the public role in this field in the future. Accurate results of monitoring can provide data support for schools, research institutions, the public, and the government. At the same time, it is also an important basis for formulating social policies. At present, the commonly used monitoring method usually adopts time series algorithm. Through literature review, it is found that the algorithm has the problem of distortion of correct data, which affects the accuracy of monitoring results. Based on the above reasons, this article combines the wavelet function with the planning algorithm and proposes a dynamic programming algorithm, which removes the redundant monitoring data in turn and clusters the distortion monitoring data with the wavelet function, which improves the accuracy and computational efficiency of the algorithm and gives full play to the monitoring of intelligence. The simulation results using MATLAB show that the planning algorithm can eliminate 90% of redundant monitoring data and improve the extraction rate of characteristic monitoring data. At the same time, the accuracy of the planning algorithm reaches 95%, and the calculation time is less than 25 s, which is better than the static planning algorithm. Therefore, the dynamic programming algorithm can better utilize the intelligence, convenience, and efficiency of the equipment to optimize the monitoring model.
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Wu, Yong, Liang-Yun Zhao, Ye-Xiang Jiang, Wei Li, Ye-Sheng Wang, Huan Zhao, Wei Wu, and Xiong-Jian Zhang. "Research and Application of Intelligent Monitoring System Platform for Safety Risk and Risk Investigation in Urban Rail Transit Engineering Construction." Advances in Civil Engineering 2021 (September 11, 2021): 1–10. http://dx.doi.org/10.1155/2021/9915745.
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In recent years, the construction scale of urban rail transit project is still in a high growth stage. In addition, the geology and surrounding environment of crossing lines are complex, and all kinds of safety accidents are still in a high incidence stage. Based on the investigation and summary of safety risk events and their causes in urban rail transit engineering construction at home and abroad, this paper fully combines the current national security management policies, introduces the “dual control” concept of safety risk classification and hidden danger investigation, and develops the intelligent monitoring system platform for urban rail transit engineering construction based on advanced technologies such as intelligent Internet of Things, 3D visualization, and artificial intelligence. It realizes the intelligent collection and analysis of engineering field monitoring data, the dynamic early warning management of engineering risk sources, the process embedding “dual control” mechanism of safety risk and hidden danger investigation, the real-time supervision of large equipment operations such as shield and hoisting, and the real-time control of high-risk operation sections such as contact channels. At the same time, the traceability and assessment management of the safety supervision process are strengthened. The parties involved in the project can realize the synchronous sharing of information through the platform and improve the efficiency of on-site safety and quality control.
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Griffin, S., W. Bauwens, and K. Ahmad. "Urban Drainage Modelling Intelligent Assistant." Water Science and Technology 29, no. 1-2 (January 1, 1994): 427–36. http://dx.doi.org/10.2166/wst.1994.0691.
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The work reported here focuses on research being conducted within the Artificial Intelligence Group at the University of Surrey and the Laboratory of Hydrology at Vrije Universiteit Brussel under the COMETT programme. The paper describes the “Urban Drainage Modelling Intelligent Assistant,” a computer-based tool kit which provides guidance, instruction and support for training on aspects of network modelling in urban drainage design and simulation models commonly used in Europe. The tool kit comprises four interrelated, interactive components: an expert system, a data preparation and model execution tool, a document browsing facility, and a term bank. The results of the work are illustrated with the aid of snapshots of the system in use. The specific emphasis here is on the role played by each component in a) the transfer of knowledge within both an inter-disciplinary field such as urban drainage modelling (hydrology, hydraulics, mathematics, computing), and a multilingual community (of particular importance in Europe at present) and b) the training of novices in urban drainage, enabling them to grasp the domain primitives, their interrelationships and meanings.
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Slam, Nady, Wushour Slamu, and Pei Wang. "A Prototype Intelligent Decision-Support System with a Unified Planning and Learning Capabilities." International Journal on Artificial Intelligence Tools 26, no. 06 (December 2017): 1750025. http://dx.doi.org/10.1142/s0218213017500257.
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This article summarizes reviews regarding the evolution of intelligent decision-support systems (IDSS). After doing an extensive literature survey, it was apparent that the theoretical foundation of IDSS has not undergone much improvement. The emergence and development of Artificial General Intelligence (AGI) provides a new theoretical perspective for constructing and developing IDSS. An AGI project, Non-Axiomatic Reasoning System (NARS), is built into the framework of a unified reasoning system, with a logic, Non-Axiomatic Logic (NAL). In this paper, we propose a formal model with unified planning, learning and uncertainty representation capabilities using NAL. We have developed a prototype decision-support system for urban fire-fighting within this framework, and obtained results demonstrating that this method can provide an effective way for intelligent decision-support systems.
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Inder, Silva, and Shi. "Learning Control Policies of Driverless Vehicles from UAV Video Streams in Complex Urban Environments." Remote Sensing 11, no. 23 (November 20, 2019): 2723. http://dx.doi.org/10.3390/rs11232723.
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The way we drive, and the transport of today are going through radical changes. Intelligent mobility envisions to improve the efficiency of traditional transportation through advanced digital technologies, such as robotics, artificial intelligence and Internet of Things. Central to the development of intelligent mobility technology is the emergence of connected autonomous vehicles (CAVs) where vehicles are capable of navigating environments autonomously. For this to be achieved, autonomous vehicles must be safe, trusted by passengers, and other drivers. However, it is practically impossible to train autonomous vehicles with all the possible traffic conditions that they may encounter. The work in this paper presents an alternative solution of using infrastructure to aid CAVs to learn driving policies, specifically for complex junctions, which require local experience and knowledge to handle. The proposal is to learn safe driving policies through data-driven imitation learning of human-driven vehicles at a junction utilizing data captured from surveillance devices about vehicle movements at the junction. The proposed framework is demonstrated by processing video datasets captured from uncrewed aerial vehicles (UAVs) from three intersections around Europe which contain vehicle trajectories. An imitation learning algorithm based on long short-term memory (LSTM) neural network is proposed to learn and predict safe trajectories of vehicles. The proposed framework can be used for many purposes in intelligent mobility, such as augmenting the intelligent control algorithms in driverless vehicles, benchmarking driver behavior for insurance purposes, and for providing insights to city planning.
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Mao, W. Q. "Study on the Construction and Application of 3D Geographic Information Services for the Smart City." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-4 (April 23, 2014): 41–44. http://dx.doi.org/10.5194/isprsannals-ii-4-41-2014.
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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.
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Bonette, Luiz Rodrigo, and João Gilberto Mendes dos Reis. "Composição, concentração e classificação do transporte urbano de massa inteligente e sustentável em quatro cidades inteligentes." Research, Society and Development 10, no. 13 (October 3, 2021): e37101320634. http://dx.doi.org/10.33448/rsd-v10i13.20634.
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As cidades inteligentes aperfeiçoam o seu sistema de transporte de massa através da sua oferta diversificada dos seus modos de transporte urbano para o transporte público. Existem opções de tecnologias inteligentes e sustentáveis que podem ser embarcadas e estarem disponíveis para utilização nesse sistema. A composição do sistema de transporte urbano de massa é um serviço público/privado e consorciado ofertado para uma demanda de cidadãos que visa a melhoria da mobilidade urbana. O transporte urbano de massa pode ser classificado partindo do levantamento de dados, tais como: os tipos de modos de transporte de massa existentes, as tecnologias inteligentes disponíveis e as fontes de energia aplicadas para a locomoção. Nesta pesquisa foi aplicado o método de estudo de caso múltiplo do sistema de transporte de massa, com o uso da técnica de triangulação de três bases de dados coletados em 2020. O objetivo deste estudo foi analisar e compreender a composição e a concentração dos sistemas de transporte urbano de massa de quatro cidades inteligentes com perfil metropolitano e classificar essas cidades inteligentes utilizando relatórios e painéis (dashboard) com o auxílio do software Power Business Intelligence (BI) da Microsoft como ferramenta de análise final. Considera-se que esses sistemas de transporte urbano de massa metropolitanos são construídos historicamente em estágios de evolução tecnológica e são implantados nas cidades inteligentes de acordo com as necessidades de mobilidade urbana das cidades, e podem ser classificados como mais ou menos diversos, mais ou menos tecnológicos e mais ou menos limpos ou poluentes.
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Changjie, Liu, Xiao Yiqing, Zhang Bo, Zhang Bijia, Xi Shufeng, and Jiao Yuanyuan. "Construction and Thoughts of Intelligent “Three-Prevention” System in Shenzhen." E3S Web of Conferences 292 (2021): 02064. http://dx.doi.org/10.1051/e3sconf/202129202064.
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Modern science and technology is a weapon against natural disasters. Shenzhen is a city of technology and innovation and we should endeavor to address flood control, drought relief and wind mitigation (named “three-prevention” in this context). In particular, we should vigorously promote the improvement of technology, and make use of modern information technologies such as big data, internet of things, cloud computing and artificial intelligence to create intelligent three-prevention system. This paper described in detail the characteristics and the construction status of the intelligent three-prevention system as well as the future development direction, in order to achieve the construction goals of the overall situation probing of the three-prevention, real-time decision-making assistance, flat command and control and urban resilience development. Since the intelligent three-prevention system’s launch in April 2020, it has started more than 20 times of emergency response against typhoon and flood. The whole process functions of front-end intelligent perception, fine dynamic simulation, real-time forecast and early warning, emergency command and post-disaster assessment have been preliminarily realized.
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Yu, Haoxuan, and Shuai Li. "2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE 2021)." Proceedings 72, no. 1 (April 28, 2021): 2. http://dx.doi.org/10.3390/proceedings2021072002.
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On 27 March 2021, the 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE 2021) was officially held in Nanchang, China. The Conference invited the IEEE Fellow Professor Guo Yong-xin from the National University of Singapore and the IET Fellow Professor Gao Liang from Huazhong University of Science and Technology of China, as well as other experts, to make the special speeches. The conference focused on the practical application of big data, the development of artificial intelligence and the innovation of Internet of things technology, and the conference provided a platform for academic exchanges among experts and, the experts present reported their own research progress and made prospects for the future development of big data such as application of big data in enterprise decision making, artificial intelligence such as intelligent endoscope in medicine, Internet of Things such as the Internet of Vehicles in urban transport.
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Kircher, Roland, Johannes Kluehspies, Eckert Fritz, and Reiner Koehler. "Mobility on demand – vision of a flexible future urban mobility." Transportation Systems and Technology 5, no. 2 (July 19, 2019): 130–38. http://dx.doi.org/10.17816/transsyst201952130-138.
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Background: The present situation in megacities is characterized by traffic congestion, capacity limits of public transportation systems. In addition, environmental regulations due to potential health risks will have an increasing impact on urban transportation systems.
Aim: In this paper, we describe major technology trends in transportation and in information and communication systems which will influence urban transportation in future megacities. Based on these trends a vision of a sustainable urban transportation system is developed.
Method: In a first step, trends in urban development and the individual needs are analyzed. Digitalization of transportation and communication technologies offer new business opportunities for Artificial Intelligence (AI) based services.
Results: The intelligent combination of advanced transportation technologies in large buildings and AI based services enables a vision of Mobility on Demand, representing a flexible and sustainable urban transportation in future megacities.
Conclusion: The vision Mobility on Demand illustrates the effective and flexible integration of individual transportation needs into public transportation systems. Depending on the standards of future individual vehicles such vehicles could be integrated seamlessly into the urban Maglev transportation system.
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Li, Mingxing, Hao Zhang, Cheng Xu, Chenyang Yan, Hongzhe Liu, and Xuewei Li. "MFVC: Urban Traffic Scene Video Caption Based on Multimodal Fusion." Electronics 11, no. 19 (September 21, 2022): 2999. http://dx.doi.org/10.3390/electronics11192999.
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With the development of electronic technology, intelligent cars can gradually realize more complex artificial intelligence algorithms. The video caption algorithm is one of them. However, current video caption algorithms only consider single-visual information when applied to urban traffic scenes, which leads to the failure to generate accurate captions of complex sets. The multimodal fusion algorithm based on Transformer is one of the solutions to this problem. However, the existing algorithms have the difficulties of a low fusion performance and high computational complexity. We propose a new video caption Transformer-based model, the MFVC (Multimodal Fusion for Video Caption), to solve these issues. We introduce audio modal data and the attention bottleneck module to increase the available information to describe the generative model and improve the model effect with less operation costs through the attention bottleneck module. Finally, the experiment is conducted on the available datasets, MSR-VTT and MSVD. Meanwhile, to verify the effect of the model on the urban traffic scene, the experiment is carried out on the self-built traffic caption dataset BUUISE, and the evaluation index confirms the model. This model can achieve good results on both available datasets and urban traffic datasets and has excellent application prospects in the intelligent driving industry.
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Galle, Nadinè J., Sophie A. Nitoslawski, and Francesco Pilla. "The Internet of Nature: How taking nature online can shape urban ecosystems." Anthropocene Review 6, no. 3 (September 23, 2019): 279–87. http://dx.doi.org/10.1177/2053019619877103.
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Many of our cities are going digital. From self-driving cars to smart grids to intelligent traffic signals, these smart cities put data and digital technology to work to drive efficiency and improve the quality of life for citizens. Yet, the natural capital upon which cities rely risks being left behind by the digital revolution. Bringing nature online is the next frontier in ecosystem management and will change our relationship with the natural world in the urban age. In this article, we introduce the ‘Internet of Nature’ to bridge the gap between greener and smarter cities and to explore the future of urban ecosystem management in an age of rapid urbanisation and digitisation. The creation of an Internet of Nature, along with the ecosystem intelligence it provides, is an opportunity to elicit and understand urban ecosystem dynamics, promote self-sufficiency and resilience in ecosystem management and enhance connections between urban social and ecological systems.
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Chunjie, Liu, Sun Yu, Zhao Yuqing, and Cai Qing. "Consideration on Construction and Development of Shanghai Smart Metro." New Metro 1, no. 1 (December 2, 2020): 1–10. http://dx.doi.org/10.37819/nm.001.01.0072.
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The degree of intelligence and service level of urban rail transit has significant influence on the measurement of intelligent transportation. In this paper, the importance of smart metro development is discussed from the perspectives of national development background, technology development trends, and people’s basic requirements, and the features of smart metro in multiple levels are analyzed. On this basis, the construction target, system architecture, and construction methods of smart metro are put forward, and the applications of smart metro are elaborated from smart construction, smart operation and maintenance, and smart service.
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Lira Cortes, Ana Laura, and Carlos Fuentes Silva. "Artificial Intelligence Models for Crime Prediction in Urban Spaces." Machine Learning and Applications: An International Journal 8, no. 1 (March 31, 2021): 1–13. http://dx.doi.org/10.5121/mlaij.2021.8101.
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This work presents research based on evidence with neural networks for the development of predictive crime models, finding the data sets used are focused on historical crime data, crime classification, types of theft at different scales of space and time, counting crime and conflict points in urban areas. Among some results, 81% precision is observed in the prediction of the Neural Network algorithm and ranges in the prediction of crime occurrence at a space-time point between 75% and 90% using LSTM (Long-ShortSpace-Time). It is also observed in this review, that in the field of justice, systems based on intelligent technologies have been incorporated, to carry out activities such as legal advice, prediction and decisionmaking, national and international cooperation in the fight against crime, police and intelligence services, control systems with facial recognition, search and processing of legal information, predictive surveillance, the definition of criminal models under the criteria of criminal records, history of incidents in different regions of the city, location of the police force, established businesses, etc., that is, they make predictions in the urban context of public security and justice. Finally, the ethical considerations and principles related to predictive developments based on artificial intelligence are presented, which seek to guarantee aspects such as privacy, privacy and the impartiality of the algorithms, as well as avoid the processing of data under biases or distinctions. Therefore, it is concluded that the scenario for the development, research, and operation of predictive crime solutions with neural networks and artificial intelligence in urban contexts, is viable and necessary in Mexico, representing an innovative and effective alternative that contributes to the attention of insecurity, since according to the indices of intentional homicides, the crime rates of organized crime and violence with firearms, according to statistics from INEGI, the Global Peace Index and the Government of Mexico, remain in increase.
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Qingmei, Yang, Wang Lihui, and Zhang Yansong. "Innovative design based on intelligent mobile folding studio." E3S Web of Conferences 179 (2020): 02059. http://dx.doi.org/10.1051/e3sconf/202017902059.
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This article introduces the interactive and operable working principle, basic composition and overall performance of intelligent mobile folding studios, and briefly reviews the development overview of mobile folding studios at home and abroad, and makes prospects and innovative designs for its future development requirements and market requirements. Designed an intelligent mobile folding studio suitable for the public and multi-regions, which can be used to meet the needs of office workers, workers and amateurs such as modern urban white-collar workers, and has also broken the limitations of long-term fixed regionalization. Comprehensive use of key technologies such as manufacturing and manipulation control, programming, intelligence, and 3D Max modeling software for 3D structural design, and based on this analysis of the application prospects and development trends of mobile folding studios.
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Ma, Guofeng, Sheng Tan, and Shanshan Shang. "The Evaluation of Building Fire Emergency Response Capability Based on the CMM." International Journal of Environmental Research and Public Health 16, no. 11 (June 3, 2019): 1962. http://dx.doi.org/10.3390/ijerph16111962.
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The construction of smart cities is a theme of urban development, and building fires greatly threaten public safety and urban environmental governance, in which fire emergency management is one of the key factors. However, most studies on the evaluation of emergency response capacity ignore the process of improvement, as well as the intelligence and practicality of the results. The evaluation system of building fire emergency response capability maturity (FE-CMM) was innovatively proposed based on the capability maturity model (CMM), including the evaluation index, evaluation grade, evaluation method, and evaluation process. At the same time, a plug-in for evaluating fire emergency response capability was developed based on the building information modeling (BIM) platform. Finally, an empirical study was carried out in combination with the case of a district fire center. The research demonstrates that the evaluation system can effectively judge the maturity of fire emergency response capability, and the established plug-in can preliminarily realize the intelligent evaluation of building fire emergency response capability, which improves the practice and intelligence of the fire emergency response capability evaluation system when fully considering the process of improvement. It has guiding significance for ex ante control and refined management of building fires, thus providing support for urban public safety and environmental governance.
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Dushkin, Roman. "Multi-agent systems for cooperative ITS." Тренды и управление, no. 1 (January 2021): 42–50. http://dx.doi.org/10.7256/2454-0730.2021.1.34169.
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This article presents an original perspective upon the problem of creating intelligent transport systems in the conditions of using highly automated vehicles that freely move on the urban street-road networks. The author explores the issues of organizing a multi-agent system from such vehicles for solving the higher level tasks rather than by an individual agent (in this case – by a vehicle). Attention is also given to different types of interaction between the vehicles or vehicles and other agents. The examples of new tasks, in which the arrangement of such interaction would play a crucial role, are described. The scientific novelty is based on the application of particular methods and technologies of the multi-agent systems theory from the field of artificial intelligence to the creation of intelligent transport systems and organizing free-flow movement of highly automated vehicles. It is demonstrated the multi-agent systems are able to solve more complex tasks than separate agents or a group of non-interacting agents. This allows obtaining the emergent effects of the so-called swarm intelligence of the multiple interacting agents. This article may be valuable to everyone interested in the future of the transport sector.
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邬, 妤琼. "The Linkage of “Sensors, Data, and Artificial Intelligence” Empowers the Urban Intelligent Governance at Grassroots Level." Sustainable Development 12, no. 05 (2022): 1446–51. http://dx.doi.org/10.12677/sd.2022.125165.
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Liu, Qi, and Zhenzhen Huang. "Research on intelligent prevention and control of COVID-19 in China’s urban rail transit based on artificial intelligence and big data." Journal of Intelligent & Fuzzy Systems 39, no. 6 (December 4, 2020): 9085–90. http://dx.doi.org/10.3233/jifs-189307.
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Since December 2019, the outbreak of novel coronavirus pneumonia has brought great challenges to global public health, which is the most serious epidemic over the past hundred years. The urban rail transit is an important part of public transport in large cities with characteristic of intensive passengers and confined space, which is easy to become viral infection intermediary. In order to prevent and control the situation of the epidemic, the police’s public security department for urban rail transit and the urban rail transit operation company have established a three-layer filter network, which is composed of safety inspection, patrol and temporary interrogation, and intelligent police service, and this network implements the deep learning technology to identify key persons, prohibited luggage, and the body temperature of passengers. For the problem of uncertainty in total passenger flow and its density, this paper proposes a method for re-establishing the passenger flow model to focus on data monitoring, and resetting the threshold value of alarm to control the passenger density. In view of the difficulty of passenger identification caused by mask during the epidemic, this paper proposes a systematic schema of timely adjusting face recognition algorithm, modifying the alarm threshold, using iris recognition system, carrying out information collision comparison, deep mining and intelligent judging, which discover the high-risk groups of epidemic prevention and control in time. China’s police’s public security department for urban rail transit aims at prevention of virus input, infection, riot, fake new, scientific prevention and control, and has made precise policy implementation to hold urban rail transit’s covid-19 intelligent prevention and control work, finally won the battle and effectively guaranteed the people’s life safety and health.
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Wang, Shangen, and Wei Zhang. "The Risk Model of Traffic Engineering Investment and Financing by Artificial Intelligence." Computational Intelligence and Neuroscience 2022 (August 3, 2022): 1–9. http://dx.doi.org/10.1155/2022/9402472.
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This study aims to analyze the influencing factors and mechanisms of investment and financing risks in transportation projects so that regions do not restrict the transportation investment and financing risk models in all areas to achieve intelligent transportation financial risk assessment. Firstly, the investment and financing modes are studied and analyzed. According to the analysis of intellectual investment and the financing report of traffic engineering infrastructure, a traffic engineering investment and a financing model based on intelligent computing is established, which is based on artificial intelligence (AI) big data analysis technology. Secondly, the investment and the financing risk model of traffic engineering is established based on multimodal learning. Finally, the urban traffic engineering of Xi’an is taken as the research object. Based on its investment and financing data in the construction of urban roads, the risk assessment is carried out. Combined with risk influencing factors, the accuracy of the intelligent calculation in the risk assessment model is calculated. Different grades of urban transportation projects have different risks in the investment and financing of transportation projects. The results show that different levels of urban transport projects have different risks in the investment and financing (IAF) performance of transport projects. Among them, the risk index of the first-class project is the highest, reaching 0.55. The risk index of the second-class project is 0.49. The results before and after using the flow engineering IAF risk model are compared. In the test results of traffic engineering risk, all target risks did not increase after the AI-based traffic engineering IAF is tested. The model test results for credit risk and financial risk are the highest at 70 and 60, respectively. Combined with the actual urban development situation, this study can provide investment and financing risk models for urban transportation projects in different regions and provide a reference for the resource control of transportation projects. This study uses AI to learn and analyze traffic engineering investment and financing data and more accurately provide data references for traffic engineering investment and financing risk models.
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Erazo-garzón, Lenín Xavier. "LA EVOLUCIÓN DE LA URBE HACIA LAS CIUDADES INTELIGENTES." UDA AKADEM, no. 1 (June 13, 2018): 58–69. http://dx.doi.org/10.33324/udaakadem.vi1.131.
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En el siglo XXI, debido a la creciente concentración de la población en los núcleos urbanos, las ciudades se enfrentan a grandes retos de sostenibilidad de la sociedad a largo plazo, a fin de convertirse en verdaderos polos de desarrollo económico, social y cultural. Como respuesta a esta problemática, las iniciativas estratégicas de ciudad inteligente (Smart City) se han expandido por todo el mundo y el Ecuador no ha sido la excepción. Tanto el gobierno central como los gobiernos seccionales están emprendiendo importantes proyectos en el marco de la ciudad inteligente; sin embargo, dentro de la sociedad ecuatoriana, este concepto aún resulta poco conocido y familiar.Frente a esta circunstancia, este trabajo de investigación tiene como propósito clarificar la visión del concepto de ciudad inteligente, mediante una revisión bibliográfica de la literatura científica y comercial, que responde a las siguientes interrogantes: ¿Qué es una ciudad inteligente? ¿Es un concepto que ha surgido recientemente? y de no ser así ¿Cómo ha evolucionado este concepto? ¿Qué áreas o sistemas del entorno urbano abarca el concepto de ciudad inteligente? ¿Qué servicios puede prestar? entre las más importantes.
Palabras clave: ciudad inteligente, ciudad ubicua, entorno urbano, inteligencia urbana, internet de las cosas, sensores, domótica
AbstractDue to the increasing concentration of population in urban areas in the XXI century, cities are facing major sustainable challenges of society in the long term so as to become real centers of economic, social and cultural development. In response to this problem, strategic initiatives of a Smart City have expanded worldwide, and Ecuador is not an exception. Both the central government and regional governments are undertaking major projects in the framework of the smart city; however, this concept is still little known and unfamiliar within the Ecuadorian society. Given this circumstance, this research paper aims to clarify the perspective of the smart city concept through a bibliographic review of the scientific and commercial literature, which answers the following questions among the most important ones: What is a smart city? Is it a concept that has emerged recently? And if not, how this concept has evolved? What areas or systems of the urban environment encompass the concept of smart city? What services can it provide?Keywords: Smart City, Ubiquitous City, Urban Environment, Urban Intelligence, Internet of Things, Sensors, Home Automation
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Lai, Yuan. "Urban Intelligence for Planetary Health." Earth 2, no. 4 (November 18, 2021): 972–79. http://dx.doi.org/10.3390/earth2040057.
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The health of human-being and our planet are incessantly interlinked, and such links often exist in the context of cities. This article articulates urban intelligence as an essential capacity for cities to be more adaptive and responsive to face the risks in the context of climate change and global pandemics. Urban intelligence includes data intelligence, design intelligence, and crowd intelligence, which collectively contribute to planetary health with better understandings in cities’ complex physical-environmental-technical-social dynamics. In the long run, urban intelligence supports cities by enabling a better conceptual understanding of human-earth conflicts, transdisciplinary research in the science of the cities, and governmental collaborations at the local and global scale.