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Optimizing and reducing energy usage is one of the greatest challenges of the 21st century in regards to climate change and rising costs of power. However, this challenge of optimization and frugality is not elementary. Many factors can change how much energy the same device uses - the time of day, climate trends (which inform heating needs), policy changes that limit energy in specific seasons, and more. Therefore, creating a model that takes into account all these variables and utilizes specific energy sensors available to UC San Diego’s researchers to compute energy uses and costs would give users crucial information to plan energy usage long into the future. Our goal in the project is to use energy data from a building on UCSD’s campus and auxiliary information about energy costs to build a model to predict future energy spending.


UCSD has initiated the deployment of various smart building technologies in some of its buildings, such as the student center and computer science building, due to the high volume of students visiting these locations. Improving the efficiency of these buildings is crucial because a significant portion of their operational costs is attributed to energy consumption. By monitoring energy usage through sensor data and analytics, substantial savings can be achieved. Additionally, identifying areas for energy conservation can aid in reducing the building’s greenhouse gas emissions. Apart from cost savings, energy usage insights can also facilitate adherence to building codes and regulations and the detection of malfunctioning systems.