In order to raise the nation’s cleaning standards, specific steps are now being implemented. An increasing number of people are taking proactive steps to keep their environment clean. Additionally, the government initiates a number of initiatives to improve sanitation. In order to remind the businesses to promptly empty the bin, we shall work to develop a mechanism. Using the Internet of Things (IoT) to monitor garbage collection systems at a reasonable cost has been the main focus of the majority of the literature’s current work. While an IoT-based technology can monitor a waste collection system in real time, it cannot manage the overspill gasses that spread. Waste that is not properly disposed of results in harmful gasses, and radiation exposure has a negative impact on the environment, human health, and the greenhouse system. Given the significance of air pollutants, waste management and air pollution concentration monitoring and forecasting are highly necessary. Here, we describe an The Internet of Things (IoT) smart bin that forecasts air pollution in the vicinity of the bin and manages garbage disposal using an ESP 8266 model. For the purpose of generating alarm messages about bin condition and estimating the quantity of air pollutant carbon monoxide (CO) in the air at a given time, we experimented with a conventional model such as the ESP8266 and an ultrasound sensor. The generation and delivery of the alarm message to a sanitary worker was delayed by 4s as a result of the system. Together with messages from the warning mechanism, the system offered real-time garbage level monitoring. By using machine learning, the suggested works provide better accuracy than current solutions that rely on straightforward methods.