An experiment collecting temperature and humidity data to test models of air-conditioning use.
Outcome: Built a sensor-to-SQL workflow and tested statistical and predictive methods for air-conditioning decisions.
Could environmental readings help model air-conditioning use and support more efficient control decisions?
Arduino-based sensors collected temperature and humidity readings and posted them to SQL at frequent intervals. I used R and Power BI to analyse and report the data, and tested statistical and predictive methods for modelling air-conditioning behaviour.
The experiment connected sensor hardware, ingestion, storage, analysis, and reporting in one workflow. It provided a practical setting for testing models against measurements from a physical process.