Trash to transparency: Footprint accounting with smart sensor dustbins and AI analytics

Life on Earth depends on the environment. Effective waste management is crucial for achieving environmental sustainability. However, current waste disposal systems lack real-time monitoring, data collection, transparency, and accountability-a serious issue that has persisted for the last three decades.To address this problem, this paper proposes an integrated solution that combines IoT-enabled smart sensor dustbins with Artificial Intelligence (AI) to monitor, analyze, and optimize waste management practices. This study explores the role of AI in sustainable accounting by focusing on smart sensor dustbins in industrial settings, which automate waste segregation and estimate pollutant contributions. These smart sensor dustbins equipped with sensors including weight, fill-level, motion, and gas sensors-to collect real-time data on waste type, volume, and disposal frequency. The data is then transmitted to a cloud-based platform where AI algorithms perform analytics to track waste generation patterns, detect abnormalities, and estimate carbon and environmental footprints. The platform features a dashboard that visualizes waste trends, footprint scores, and compliance with sustainability goals, such as the UN Sustainable Development Goals (SDGs). This fusion of hardware and AI, enables data-driven waste footprint accounting and promotes transparency in environmental reporting. By transforming raw data into meaningful metrics, this project paves the way for more sustainable urban living and informed decision-making in waste governance.