A Low-Cost Analytics Stack for County-Scale Organics Diversion and Anaerobic Digestion Performance: Design, Validation, and Policy KPIs

In this paper, an advanced low-cost analytics model is introduced to monitor the organization and obtain maximum effectiveness of the county-level organics diversion and anaerobic digestion. The system being proposed combines Extract Transform Load (ETL) pipelines, the capability for predictive modeling and interactive dashboard visualization in order to provide decision-makers with actionable information to optimize waste management policies. In designing the framework, real-time monitoring of the performance and strategic planning can be carried out in the predictor of the rate of contamination prediction and throughput/yield modeling with the help of digester, contamination rate prediction algorithms and throughput system modeling. It builds on the current USDA data infrastructure and is shown to be very economical, when traditional methods, of monitoring as well as very accurate, when it comes to predictions of performance. Key performance indicators (KPIs) are built into monthly dashboard reports to help drive the evidence-based policy decisions. As demonstrated in tests for validation in 3 pilot counties, it accurately predicts contamination 87% of the time, and has a 92% correlation with actual measures of digester performance. The framework is a Scaled-up approach to Optimizing efficacy Organic Waste Handling, County level where circular economy implementation and viable waste to energy implementation can be directly applied.