EcoSense IAQ Monitoring Dataset: Edge vs. Cloud Pipeline Latency Across Three Campus Locations

5,317 balanced readings collected from an ESP32 WROOM-32D V4 IAQ monitoring node across three locations (residential apartment, university lecture classroom, computer laboratory) in Sokcho, South Korea, April 2026. Each record contains sensor readings (CO2, temperature, humidity, air quality, sound), edge processing latency (esp32_processing_us), cloud processing latency (cloud_processing_ms), session metadata, and IAQ scores for both pipelines. Collected using a 30-minute alternating A/B methodology. Associated paper: EcoSense: Edge vs. Cloud Computation Placement for Real-Time IAQ Monitoring in University Campus Environments.