Accessible Carbon Emission Assessment System

This paper presents an integrated system for real-time carbon emission tracking and management utilizing IoT, AI/ML, and interactive technologies. IoT-based sensors continuously monitor data from electricity consumption, fuel usage, and transportation activities to ensure accurate and up-to date carbon footprint calculations. Based on these inputs, the system computes emissions in real-time and applies machine learning regression models to predict future carbon outputs. Personalized carbon reduction strategies are generated, tailored to each user’s activities. An intuitive data visualization module displays emission trends through graphs, heatmaps, and comparative reports, simplifying analysis and promoting awareness. To further enhance user engagement and foster sustainable behavior, a gamification layer incorporating points, badges, and leaderboards is integrated. Together, these modules form a dynamic, data-drivenplatform that empowers users to monitor, predict, and actively reduce their carbon footprint.