Bridging the Digital Divide in Sustainable Energy
A Frugal Design Approach for Inclusive Household Forecasting
TL;DR: A frugal and inclusive forecasting service designed to bridge the digital divide in sustainable energy consumption by supporting manual data entry.
While accurate energy forecasting is a powerful tool for sustainability, current solutions often require automated smart home technology, risking a digital divide that excludes households relying on manual data entry.
To address this gap, we are developing an inclusive forecasting service using a Design Science Research approach. The service is built on a computationally frugal machine learning model designed to handle the sparse data typical of manual input, aiming to provide a validated artifact that bridges the gap between digital innovation and equitable access.
Working Paper.