Air pollution is amongst the most important determinants to human health. World Health Organization stated that air pollution has become a critical health issue for millions of people worldwide. It is a major risk factor for many health issues including skin infections, lung cancer, heart disease, throat and eye disorder, asthma, bronchitis and respiratory ailments. Air pollution not only causes health concerns, but it also poses a severe threat to our world. Pollutants from sources like automobiles and factories contribute to the greenhouse effect, with CO2 emissions being one of the most major contributors. Due to growing smog and ozone depletion, climate change is being widely discussed at global conferences and has been a hot problem for the world during the last few decades. The authors specifically address significant issues such as air pollution monitoring and health monitoring in this work by employing sensors that were previously viewed as limitations in an existing smart electric bike monitoring system. Statistical linear methods have been used in the past to solve the air pollution prediction problem, however due to the complexity and variance in time-series data, these strategies can give inaccurate air pollution predictions. Data from sensors installed on public transportation vehicles will be collected, processed, and distributed by the proposed system.