The cumulative amount of greenhouse gases that are shaped by our actions is a carbon footmark. In the US, the total carbon footmark of a humanoid is 16 tonnes, one of the largest amounts in the world. The average is closer to 4 tonnes worldwide. The average universal carbon footmark per year requirements is to drop below 3 tonnes by 2050 to have the utmost chance of stopping a 2°C point rise in worldwide temperature. Rahul et al. already predicted that the carbon footprint reduced by 17% with the use of IoT-enabled services. In this research study a novel approach to reduce carbon footprint using IoT with reinforcement AI learning is presented, which further reduced carbon footprint by 5% when using and nearly 7% when it is done using Q-Learning. The detailed findings are included to demonstrate the result.