  A modern-day society demands resilient, reliable, and smart urban
infrastructure for effective and in telligent operations and deployment.
However, unexpected, high-impact, and low-probability events such as
earthquakes, tsunamis, tornadoes, and hurricanes make the design of such robust
infrastructure more complex. As a result of such events, a power system
infrastructure can be severely affected, leading to unprecedented events, such
as blackouts. Nevertheless, the integration of smart grids into the existing
framework of smart cities adds to their resilience. Therefore, designing a
resilient and reliable power system network is an inevitable requirement of
modern smart city infras tructure. With the deployment of the Internet of
Things (IoT), smart cities infrastructures have taken a transformational turn
towards introducing technologies that do not only provide ease and comfort to
the citizens but are also feasible in terms of sustainability and
dependability. This paper presents a holistic view of a resilient and
sustainable smart city architecture that utilizes IoT, big data analytics,
unmanned aerial vehicles, and smart grids through intelligent integration of
renew able energy resources. In addition, the impact of disasters on the power
system infrastructure is investigated and different types of optimization
techniques that can be used to sustain the power flow in the network during
disturbances are compared and analyzed. Furthermore, a comparative review
analysis of different data-driven machine learning techniques for sustainable
smart cities is performed along with the discussion on open research issues and
challenges.
