{"id":114184,"date":"2020-10-06T08:53:28","date_gmt":"2020-10-06T12:53:28","guid":{"rendered":"https:\/\/www.ucf.edu\/news\/?p=114184"},"modified":"2023-03-16T13:58:11","modified_gmt":"2023-03-16T17:58:11","slug":"where-artificial-intelligence-meets-urban-planning","status":"publish","type":"post","link":"https:\/\/www.ucf.edu\/news\/where-artificial-intelligence-meets-urban-planning\/","title":{"rendered":"Where Artificial Intelligence Meets Urban Planning"},"content":{"rendered":"

Before you ever step into a new coffee shop, years of urban planning have gone into building that brick-and-mortar building in your neighborhood.<\/p>\n

Urban planning is a multi-faceted discipline in which planners collect data points from targeted areas to determine if a store, hospital or other types of buildings are likely needed in that area. It also involves determining if the needed infrastructure to support the building is there or needs to be added. The data provides context to planners and includes things such as geographic factors, socioeconomic statistics and human mobility.<\/p>\n

This kind of planning can take years to configure, but for first-year computer science doctoral student<\/a> Dongjie Wang, that isn\u2019t efficient. Wang has developed an artificial intelligence program called the Land-Use Configuration Generative Adversarial Network (LUCGAN). This program is made to learn the context of an area through human data input and then develop solutions for urban planners. It could potentially save time and money for communities involved in planning new neighborhoods.<\/p>\n

LUCGAN is based on a deep Generative Adversarial Network, a machine-learning technique in which a machine is trained in a specific \u2018set.\u2019 This learning occurs after the machine is presented with a data distribution, or a list that includes all points of data; with this information the machine can produce infinite probability points that could be inserted into a graph, or in this case an axis.<\/p>\n

Deep learning is patterned in many ways after human learning, but where the brain connects learning through neurons, LUCGAN uses networks to gather data points and correlate them.<\/p>\n