Air pollution is a major problem in developing countries and around the world causing lung diseases such as asthma, chronic bronchitis, emphysema, and chronic obstructive pulmonary disease. Therefore, innovative methods and systems for predicting air pollution are needed to reduce such risks. Some Internet of Things (IoT) technologies have been developed to assess and monitor various air quality parameters. In the context of IoT, Artificial intelligence is one of the main segments of smart cities that enables collecting a large amount of data to make recommendations, predict future events and help make decisions. Big data, as part of artificial intelligence, greatly contributes to making further decisions, determining the necessary resources, and identifying critical places thanks to the large amount of data it collects. This paper proposes a solution, with the integration of the Internet of Things (IoT), to predict pollution for any given day. This paper aims to show how sensor-derived data in smart air pollution monitoring solutions can be used for intelligent pollution management. By collecting data from the air pollution sensor that sends the data to the server via. NET 6 REST API endpoint and places it in a SQL Server database together with additional weather data that is collected from REST API for that part of the day, a dataset is created through the ETL process in Jupyter notebook. Linear regression algorithms will be used for making predictions. By detecting the largest sources of air pollution, artificial intelligence solutions can proactively reduce pollution and thus improve health conditions and reduce health costs.

Nowadays, when applications are being developed faster with the introduction of agile methodologies and new technologies, microservices are emerging. The microservices make applications easier to create and maintain when broken down into smaller parts, which form a whole application. RabbitMQ acts as an intermediary between the various services. It reduces the load and delivery time on server web applications by delegating tasks that would typically take a lot of time and resources. Message queuing allows web servers to respond quickly to requests rather than being forced to perform complex procedures that can take more time and resources. AMQP (Advanced Message Queuing Protocol) is a message protocol that deals with publishers and consumers like any other messaging system. Publishers produce messages while consumers download and process them. The job of message brokers, such as RabbitMQ, is to ensure that messages from publishers go to the right consumers. To do this, the broker uses two key components: exchange and order. We demonstrated that the style of microservice architecture is an approach to the development of an application as a set of small services, each in charge of its own process and communication with other services.