Introduction

In many households, the potential for energy efficiency often goes unrealized. Old and inefficient appliances, like outdated refrigerators, are kept for years, leading to unnecessary energy consumption and higher electricity bills. Households lack the tools and knowledge needed to identify these inefficiencies and the potential benefits of upgrading to more energy-efficient alternatives.

What

Our goal is to create an open data foundation that allows to identify the specific, old appliances from households and quantify the potential energy savings that can be achieved through the replacement with an energy efficient alternative. By providing detailed insights and actionable recommendations, we aim to enable households to make informed decisions, rewarding their efforts in the energy transition with lower energy bills and transparency in terms of consumption.

How

• Build an open data appliance catalogue with energy efficiency data
• Develop a workflow to identify old appliances using load disaggregation from user energy data.
• Implement image-to-text extraction from product manuals for appliance identification.
• Create a questionnaire-based tool to help users identify appliances ready for replacement.
• Visualize energy savings and cost reductions from upgrading to efficient appliances.

Where to start

We already have a prototype in place, which is currently running on Databricks.     This prototype includes fully set-up user accounts and a complete full-stack environment.     The environment is equipped with integrated data storage, connections to external data sources, pretrained machine learning models, and user-friendly web interfaces (using Gradio).     Additionally, Databricks personnel are available on-site to assist with any technical needs or further development.  This foundation allows you to immediately begin refining steps, integrating additional data sources, and enhancing the user experience, paving the way for a scalable solution that can be rapidly deployed and expanded.

Contact

Primeo Energie , Andreas Schuth and Timo Kropp