This project presents a statistical analysis of CO2 emissions in public utility vehicles based on road grade, acceleration, and vehicle-specific power, utilizing IoT technology with Raspberry Pi for real-time monitoring. The system incorporates a CO2 sensor to measure the vehicle’s carbon dioxide emissions, which are displayed on an LCD screen for immediate feedback. If the CO2 levels exceed a predefined threshold, the system triggers an alert, sending a message containing the current CO2 level and GPS location of the vehicle via GSM technology to the concerned authorities. Additionally, this data is uploaded to ThingSpeak, an IoT analytics platform, for further analysis and long-term monitoring. This solution aims to enhance air quality management, enable better monitoring of public transport emissions, and provide insights for improving the efficiency of public utility vehicles, contributing to sustainable urban mobility.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

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