Urban heat islands (UHIs) are a growing threat to the liveability of megacities such as Mexico City. On the Zacatenco campus—where the School of Computer Science (ESCOM-IPN) sits amid dense industrial activity and heavy traffic—we deployed an integrated sensor network to examine how local morphology and anthropogenic emissions jointly influence outdoor temperature, particulate pollution and indoor micro-climates. A Davis Vantage Pro-2 weather station, four Qingping indoor monitors and mobile Flatburn transects generated high-resolution meteorological and air-quality data. These streams were harmonised through an automated ETL pipeline, modelled in multidimensional cubes and visualised with GIS to produce spatiotemporal maps of heat and pollutants. The analysis reveals a persistent micro-UHI inside ESCOM: Classroom 22-S repeatedly reached 32–34 ℃ owing to restricted ventilation, continuous occupancy and heat released by active servers. Vehicular parking areas recorded the highest PM₂․₅ and PM₁₀ loads, highlighting transport emissions as a dominant particle source, while prevailing west-to-east winds channelled industrial emissions directly toward the campus. By coupling indoor and outdoor sensing with urban-context data, the prototype demonstrates a practical, multi-scale framework for diagnosing UHIs and particulate pollution in densely built academic settings and provides an evidence base for targeted thermal-comfort and air-quality mitigation strategies.