Monitoring air quality in modern cities has become a major issue for planning and decision making of enhanced living environments. Industrial and domestic sources and, predominantly, automobiles are accountable for pollutant exhausts that decisively disturb healthy lifestyle in urban areas. Consequently, quality of air must be estimated in real-time to deliver a spatiotemporal database for improved data processing and visualization. Conventional air quality monitoring systems in smart cities have been fabricated on sparse regulatory monitoring, improved with satellite data and prediction techniques. However, technologies related to Industry 4.0 like Internet of Things (IoT), big data, machine learning, artificial intelligence, and computing platforms are reforming smart cities globally. Smart cities can harness these technologies combined with conventional approaches for effective air quality monitoring and to provide enhanced living environments. In order to integrate technical implications of pollutants and prevailing IoT-based mobile computing frameworks for monitoring air pollution, we review several cutting-edge researches found in the literature. This study presents a perspective regarding the existing opportunities in addressing the issues related to air quality monitoring in smart cities. We discuss the reimbursements of integrating mobile computing and IoT technologies in monitoring and evaluating environmental quality in smart cities. Also, we describe the challenges and future directions in leveraging these technologies to estimate air pollution levels and risks.