Application of Machine Learning and Artificial Intelligence for Automatic Layout Generation for Smart Cities

Over the years, cities have developed significantly and major urbanisation has taken place. New roads, highways, and transportation routes are being worked on everyday all over the world. With the increase of population and human needs, quality of life has become very important. An area is considered to be a smart city when the city's operations are not only smooth but also extremely efficient, leading to a significant increase of ease in the people's lives. Our research aims to use machine learning and basic artificial intelligence concepts to enable people, especially policymakers and organisations, to generate unique, quick and efficient layouts for a smart city. Python libraries such as NumPy, SciPy, Pandas, and Matplotlib were used to develop a tool to optimise urban planning by creating layouts consisting of various zones. Constraint based algorithm concepts along with basic artificial intelligence concepts such as optimization, distance and heuristics and random sampling are used. The generator considers 16 zones, each individually colour coded, while also keeping in mind transportation networks, environment and amenities. The solution offers a dynamic and customisable tool for scenario management and future development planning.