IoT and Greenhouse Gas (GHG) Emissions Models for Creating Sustainable Communities

Chapter 4 demonstrates how Internet of Things (IoT) infrastructure, Class 10 veterinary sensors, and edge AI models transform each cow’s rumination pattern into a real-time greenhouse-gas meter—offering a tangible path toward Scope 3 decarbonization. The chapter begins by positioning dairy methane within the GHG Protocol framework, then introduces the architecture of a multiregion-deployed Edge IoT & AI sensor capable of logging chew counts and behavioural signals even on intermittently connected networks. Step-by-step signal processing—spanning temporal windowing, peak–trough detection, interquartile-range (IQR) filtering, and Fast Fourier Transforms (FFT)—feeds machine-learning pipelines that estimate daily methane output, assess model precision, and correlate emissions with feed, water, and medication data. The chapter concludes by scaling these barn-level insights to enterprise Scope 1–3 inventories across the U.S. dairy sector, illustrating how the fusion of IoT telemetry, AI-driven analytics, and ESG frameworks enables measurable, community-wide progress toward climate resilience and responsible agriculture.