During my 1-month internship, I completed four key projects that enhanced Plentify's smart water heating solution (HotBot):
- Developed an unsupervised model to calculate standing heat loss in geysers, improving energy efficiency assessments, and quantified its precision, with unknown true values, and with extremely noisy data.
- Created models for water flow patterns, enabling personalised recommendations to customers for optimal usage periods.
- Engineered a model to predict inlet water temperature for geysers, contributing to more accurate heating control and energy savings.
- Implemented monitoring systems for AWS Lambda functions, strengthening the reliability of cloud-based operations.
These projects allowed me to apply data science techniques to real-world energy efficiency challenges, while gaining valuable experience in cloud computing, and predictive modelling, in IoT applications.
