Machine Learning-Driven Innovations for Sustainable Smart Cities: Insights From Olongapo City, Philippines

Abstract

Urbanization is an ongoing process that is gradually defining the context of the contemporary world; studies show that by 2050, 67. It projects that 9 percent of the global population will live in developed urban areas by 2050, up from today's 55 percent (United Nations, 2018). The Philippines' Olongapo City is one of the ideal examples of how utilizing the power of advanced analytics in machine learning for innovations can help foster SD in cities. The current paper focuses on the concerns experienced in Olongapo City, the particular ML solutions that were used to resolve these concerns, and the generalization of AI development in handling city management. Thus, the given study shows the possibilities of ML in enriching the concept of sustainable smart cities.