Using Cognitive IOT In Vehicle System for On Actual Time Monitoring of CO2 Emission with Temperature and Alcohol Detector

One of the pressing environmental challenges we face today is the phenomenon of global warming, primarily driven by the release of greenhouse gases. Among these gases, carbon dioxide stands out as a significant contributor, with its emissions leading to a warming effect on the Earth's surface. Protecting our environment requires us to address and manage these changes effectively, presenting a considerable challenge. For long-term control of carbon dioxide emissions at their source, there is a growing recognition of the need for preventive and control technologies. This paper aims to employ IoT technology, utilizing Raspberry Pi's CO2 sensitivity, to monitor emissions from various sources such as public transportation, industries, and forest fires. Continuous monitoring of carbon dioxide levels within a city will help identify areas with the highest pollution levels. Additionally, this initiative seeks to implement an intelligent system for early detection of forest fires, also known as wildfires. These uncontrolled fires in natural areas pose significant threats to both ecosystems and human resources. It's noteworthy that wildfires emit more CO2 gas than initially assumed, impacting state climate targets. Integrating these efforts with IoT enhances security and enables various services, including the deployment of a Simple Notification Service (SNS) to alert mobile users about high CO2 levels in specific areas. Furthermore, this model aims to extend its capabilities to include the detection of temperature in heated vehicle components, such as engines, using temperature detectors. Moreover, alcohol detectors will be utilized to monitor alcohol consumption by vehicle drivers, enhancing safety measures on the road. Keywords: SNS (Simple Notification Service), IoT (Internet of Things), GPS (Global Positioning System), GVG (Green Vehicle Guide), MAQUMON (Mobile Air Quality Monitoring Network).