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ARTIFICIAL INTELLIGENCE in Urban Planning.docx

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Ngoc Tuyen
Ngoc Tuyen

The document discusses artificial intelligence and its applications in urban planning. It defines AI as the ability of computers or robots to perform tasks typically done by humans using human expertise. The document then discusses how AI could be used for automated urban planning by developing machine learning models to analyze spatial data and generate optimal land use configurations. However, developing such models poses challenges in how to evaluate land use plans, train AI systems on existing urban patterns, and assess generated land use setups. The document concludes by providing examples of how AI is being used or could be used in Sydney to optimize public transportation, monitor air quality, improve women's safety, manage traffic systems, and detect water pipe leaks.

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ARTIFICIAL INTELLIGENCE? The capacity of a computer or a robot controlled by a computer to do tasks that are typically carried out by persons due to the fact that these tasks need human information and expertise is the definition of artificial intelligence (AI) (As & Basu, 2022). The term "computer-based intelligence" refers to the simulation of human intellect in computers that have been programmed to behave and reason in the same way as people. The word may also be given to any computer that demonstrates characteristics associated with a human mind, such as the ability to learn and basic thinking. The best quality of an AI is its capacity to identify and pursue courses of action that are likely to result in the greatest number of unobstructed paths leading to the accomplishment of a certain objective. ARTIFICIAL INTELLIGENCE in Urban Planning No matter where on the globe you are, the people who live nearby have a significant impact on their communities. As a result, the people who live there have their identities shaped by the communities in which they are embedded (Lang, 2021). Regardless, agreements for community land use, context, and asset identification are often the consequence of models backed by competent urban organizers. The actual design of human settlements is managed by urban planning, which also provides assistance for the purposeful development of urban, rural, and provincial regions. A viable metropolitan arrangement helps to offset the operational and social limitations of a metropolitan framework. It aims to promote personal happiness while simultaneously reducing congestion and accidents, waste and pollution, as well as crime percentages and taxation rates. Although the concept of AI-enabled mechanized urban planning is intriguing, the scientists almost immediately ran into three problems: how to measure a land-use design plan; how to build up an AI structure that can become familiar with the great and the terrible of existing urban communities in terms of land-use arrangement strategies; and how to assess the nature of the framework's created land-use setups. While the concept of AI-enabled mechanized urban planning is intriguing, the scientists almost immediately ran into three problems. The experts began by characterizing the topic of computerized urban planning as a learning job on the configuration of land-use given the surrounding spatial conditions (Fujita et al., 2021).
They conceptualized the organization of land use as a longitude-scope channel tensor with the intention of developing a technology that would be able to construct such tensors for spontaneous regions. Drawing on urban geology, human mobility, and financial information, the team developed an unpleasant learning framework that they named LUCGAN with the goal of producing attractive area use configurations. LUCGAN is designed to first understand depictions of the settings of a virgin region and then to afterwards develop an optimum land-use setup response for the area. Effects of Artificial Intelligence when being put Into Practice in Sydneys ways of living The use of artificial intelligence is contingent on the potential of improving, streamlining, and expanding the scope of a wide variety of tasks. Their systems can differentiate between many instances, fulfill various expectations and decisions, and ultimately carry out and actions with speed and accuracy. The quantity of information that can be gathered by apps, cameras, and sensors is directly proportional to the level of productivity that can be achieved with the models. In the context of the city, the use of technology that is based on the employment of computerized reasoning has been considered as a way to enhance the management of urban communities, especially those that are denser and have larger impacts. Within the context of this particular scenario, computerized thinking, the enhancement of urban systems, and city the board are all able to be strongly tied to one another. However, it is also essential to have a solid understanding of the true requirements of the people who live in urban areas and the ways in which AI might work to enhance urban circumstances. In addition, participation in the network is essential so that users may have faith in the systems and figure out how to correct any errors that may occur. The following actions are examples of applications of artificial intelligence consciousness systems that are either in their early phases of development or are already in use. All of these systems have plans in place to make the management of urban systems more efficient.
The Optimization of Public Transportation There have been numerous applications of artificial intelligence in the public transportation system in cities, ranging from robots that are capable of communicating information to commuters at stations and transportation points to computer systems that maximize bus network connections with real-time timesheets utilizing data such as passenger volume and the total number of daily trips per line. The study of user experiences may also be gathered, saved, and integrated by apps based on the usage of AI, supporting potential adjustments to user pathways, employing multimodal travel, and increasing adhesion to the public transport network (Misuraca & Noordt, 2020). Monitoring the Quality of the Air A variety of actions have resulted in the establishment of organizations of sensors that are equipped for capturing air samples, analyzing them, and informing the general community about the quality of the air in both large and small metropolitan areas. Despite the presence of contamination indications, the amount of petroleum derivative particles may be determined by rotating professionals to a nearby forest fire before the situation spirals out of control. Safer Streets for Women The use of apps that collect data directly from customers allows artificial intelligence to determine whether or not a certain path is considered to be safe for women. The existence of development in the roadways, police, commercial foundations, public illumination, or badgering is often connected with the gathering and accessibility of data. Management of the Traffic System Urban communities have the capacity to increase the monitoring and information analysis of travel routes, traffic signal regulation, and camera following with the use of traffic systems that are positioned in artificial intelligence (AI). Video systems enable the recognition of various vehicle types, accident identification, and the differentiation between cars and persons walking, and they use this information to activate traffic flow control devices and analyze potential strategies for the future. Detection of Water Losses in Pipes Using sound sensors that collect stream frequencies in lines is one of the methods that may be used to identify water spills from other types of water leaks. An application that deconstructs the narrative by means of a data set stored in the cloud may be used to access this information. This
program is able to distinguish between noises coming from pipes that normally carry water and lines that are designed to contain overflow. References As, I., & Basu, P. (2022). Artificial intelligence in urban planning and design : technologies, implementation, and impacts. Elsevier. Fujita, H., Selamat, A., Lin, J. C.-W., & Ali, M. (2021). Advances and trends in artificial intelligence : artificial intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings. Part I. Springer. Lang, V. (2021). Digital fluency : understanding the basics of artificial intelligence, blockchain technology, quantum computing, and their applications for digital transformation. Springer. Misuraca, G., & Noordt, C. van. (2020). AI Watch - artificial intelligence in public services : overview of the use and impact of AI in public services in the EU. Publications Office of the European Union.

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ARTIFICIAL INTELLIGENCE in Urban Planning.docx

  • 1. ARTIFICIAL INTELLIGENCE? The capacity of a computer or a robot controlled by a computer to do tasks that are typically carried out by persons due to the fact that these tasks need human information and expertise is the definition of artificial intelligence (AI) (As & Basu, 2022). The term "computer-based intelligence" refers to the simulation of human intellect in computers that have been programmed to behave and reason in the same way as people. The word may also be given to any computer that demonstrates characteristics associated with a human mind, such as the ability to learn and basic thinking. The best quality of an AI is its capacity to identify and pursue courses of action that are likely to result in the greatest number of unobstructed paths leading to the accomplishment of a certain objective. ARTIFICIAL INTELLIGENCE in Urban Planning No matter where on the globe you are, the people who live nearby have a significant impact on their communities. As a result, the people who live there have their identities shaped by the communities in which they are embedded (Lang, 2021). Regardless, agreements for community land use, context, and asset identification are often the consequence of models backed by competent urban organizers. The actual design of human settlements is managed by urban planning, which also provides assistance for the purposeful development of urban, rural, and provincial regions. A viable metropolitan arrangement helps to offset the operational and social limitations of a metropolitan framework. It aims to promote personal happiness while simultaneously reducing congestion and accidents, waste and pollution, as well as crime percentages and taxation rates. Although the concept of AI-enabled mechanized urban planning is intriguing, the scientists almost immediately ran into three problems: how to measure a land-use design plan; how to build up an AI structure that can become familiar with the great and the terrible of existing urban communities in terms of land-use arrangement strategies; and how to assess the nature of the framework's created land-use setups. While the concept of AI-enabled mechanized urban planning is intriguing, the scientists almost immediately ran into three problems. The experts began by characterizing the topic of computerized urban planning as a learning job on the configuration of land-use given the surrounding spatial conditions (Fujita et al., 2021).
  • 2. They conceptualized the organization of land use as a longitude-scope channel tensor with the intention of developing a technology that would be able to construct such tensors for spontaneous regions. Drawing on urban geology, human mobility, and financial information, the team developed an unpleasant learning framework that they named LUCGAN with the goal of producing attractive area use configurations. LUCGAN is designed to first understand depictions of the settings of a virgin region and then to afterwards develop an optimum land-use setup response for the area. Effects of Artificial Intelligence when being put Into Practice in Sydneys ways of living The use of artificial intelligence is contingent on the potential of improving, streamlining, and expanding the scope of a wide variety of tasks. Their systems can differentiate between many instances, fulfill various expectations and decisions, and ultimately carry out and actions with speed and accuracy. The quantity of information that can be gathered by apps, cameras, and sensors is directly proportional to the level of productivity that can be achieved with the models. In the context of the city, the use of technology that is based on the employment of computerized reasoning has been considered as a way to enhance the management of urban communities, especially those that are denser and have larger impacts. Within the context of this particular scenario, computerized thinking, the enhancement of urban systems, and city the board are all able to be strongly tied to one another. However, it is also essential to have a solid understanding of the true requirements of the people who live in urban areas and the ways in which AI might work to enhance urban circumstances. In addition, participation in the network is essential so that users may have faith in the systems and figure out how to correct any errors that may occur. The following actions are examples of applications of artificial intelligence consciousness systems that are either in their early phases of development or are already in use. All of these systems have plans in place to make the management of urban systems more efficient.
  • 3. The Optimization of Public Transportation There have been numerous applications of artificial intelligence in the public transportation system in cities, ranging from robots that are capable of communicating information to commuters at stations and transportation points to computer systems that maximize bus network connections with real-time timesheets utilizing data such as passenger volume and the total number of daily trips per line. The study of user experiences may also be gathered, saved, and integrated by apps based on the usage of AI, supporting potential adjustments to user pathways, employing multimodal travel, and increasing adhesion to the public transport network (Misuraca & Noordt, 2020). Monitoring the Quality of the Air A variety of actions have resulted in the establishment of organizations of sensors that are equipped for capturing air samples, analyzing them, and informing the general community about the quality of the air in both large and small metropolitan areas. Despite the presence of contamination indications, the amount of petroleum derivative particles may be determined by rotating professionals to a nearby forest fire before the situation spirals out of control. Safer Streets for Women The use of apps that collect data directly from customers allows artificial intelligence to determine whether or not a certain path is considered to be safe for women. The existence of development in the roadways, police, commercial foundations, public illumination, or badgering is often connected with the gathering and accessibility of data. Management of the Traffic System Urban communities have the capacity to increase the monitoring and information analysis of travel routes, traffic signal regulation, and camera following with the use of traffic systems that are positioned in artificial intelligence (AI). Video systems enable the recognition of various vehicle types, accident identification, and the differentiation between cars and persons walking, and they use this information to activate traffic flow control devices and analyze potential strategies for the future. Detection of Water Losses in Pipes Using sound sensors that collect stream frequencies in lines is one of the methods that may be used to identify water spills from other types of water leaks. An application that deconstructs the narrative by means of a data set stored in the cloud may be used to access this information. This
  • 4. program is able to distinguish between noises coming from pipes that normally carry water and lines that are designed to contain overflow. References As, I., & Basu, P. (2022). Artificial intelligence in urban planning and design : technologies, implementation, and impacts. Elsevier. Fujita, H., Selamat, A., Lin, J. C.-W., & Ali, M. (2021). Advances and trends in artificial intelligence : artificial intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings. Part I. Springer. Lang, V. (2021). Digital fluency : understanding the basics of artificial intelligence, blockchain technology, quantum computing, and their applications for digital transformation. Springer. Misuraca, G., & Noordt, C. van. (2020). AI Watch - artificial intelligence in public services : overview of the use and impact of AI in public services in the EU. Publications Office of the European Union.