A local-first smart home system that collects readings from utility meters, temperature sensors, and environmental monitors to build an intelligent understanding of household patterns and habits. Gaugemind correlates disparate data points to recognize activities, optimize usage, and provide meaningful insights.

The system processes electricity and water meter pulses alongside temperature, humidity, and other sensor data, identifying patterns like shower schedules, laundry cycles, heating efficiency, and room occupancy without invasive monitoring. By learning normal baselines, it detects anomalies such as leaks, inefficient heating, or unusual consumption.

Gaugemind maintains complete privacy through local processing, offering detailed analytics and visualizations of energy flows, cost projections, and habit formation over time. The interface reveals connections between environmental factors, usage patterns, and household routines.

Designed for incremental adoption, the system works with simple pulse counters, smart meters, DIY sensors, and manual entries, growing in intelligence as more data sources are added while always keeping data under local control.