Air quality monitoring in smart cities is fundamental for public health and sustainable urban development. Internet of Things (IoT) architectures based on serverless computing, such as the combination of ESP32-C, Raspberry Pi 4, and AWS Serverless services (Lambda, API Gateway, DynamoDB), promise significant benefits in terms of scalability, efficiency, and reduced operational costs for this purpose. This study is a systematic review that aimed to identify and synthesize existing empirical evidence on the technical and economic viability of this specific architecture for urban air quality monitoring. The findings reveal a notable absence of specific implementations or direct comparative evaluations that match this precise hybrid architecture in the published literature. The review concludes that the technical and economic viability of this configuration has not been conclusively established through empirical comparison Furthermore, the methodological quality assessment of identified studies, using an adapted ROBIS tool, showed that the existing literature often lacks reproducible details regarding hardware configurations, software versions, network parameters, raw data avail-ability, and statistical significance tests, which prevents a rigorous validation of the potential advantages of such systems. Therefore, this review underscores a critical need for future empirical research to validate the expected advantages of this architecture in terms of latency, availability, and cost-effectiveness.