Energy-Efficient Solutions: Smart Recommender Engine for Sustainable Buildings

Background

Existing buildings are the largest consumers of energy and contributors to carbon dioxide emissions. However, it can take 30-50 years for new energy-efficient technologies, such as LED lighting, to fully integrate into these structures. The challenge lies in identifying cost-effective solutions for individual buildings and portfolios, which is currently a manual, time-consuming, and expensive process. Sales reps, engineers, and lengthy approval cycles hinder the efficient implementation of energy-efficient solutions.

Objective

The goal of this project was to develop a recommender engine that automates and simplifies the process of identifying, prioritizing, and recommending energy-efficient solutions for buildings and asset portfolios. This aims to reduce energy wastage, lower carbon emissions, and promote sustainability by offering cost-effective and tailored upgrades for building owners.

Approach

Omdena’s two-month challenge brought together 50 technology changemakers to build the Smart Energy scaleOS™ platform, which integrates a project recommendation engine. The engine automatically analyzes building characteristics, regional environmental factors, utility tariffs, government incentives, and available energy technology options. By evaluating these factors, it identifies specific energy-efficient and clean energy solutions, prioritizes them, and recommends the best options based on criteria like return on investment, carbon reduction, and building owner preferences.

Results and Impact

The Smart Energy scaleOS™ platform, powered by the recommender engine, enables the automated identification of energy-efficient upgrades. By analyzing building energy systems, the platform helps reduce energy consumption, carbon emissions, and upgrade costs for building owners. Additionally, it streamlines the upgrade process, improving project approval rates and accelerating implementation timelines. This solution has the potential to impact sustainability efforts globally by making energy-efficient solutions more accessible, cost-effective, and impactful.

Future Implications

Future iterations of the recommendation engine can optimize solutions for enhanced building occupant health and productivity, expanding its benefits beyond energy efficiency to broader social and environmental impacts. The tool can contribute to the adoption of renewable energy, microgrids, water conservation, and other green technologies. This project sets the stage for further advancements in automated building upgrades, influencing policy decisions and encouraging the adoption of clean energy solutions worldwide