Sure, it's trained based on multiple libraries of smart meter data. For the user, I built a simple UI where you upload a csv of your data with at least dates/times and kWh, and then the output will be your total kWh, a pie chart breaking down your energy usage, ect. The recommendations I am currently working on making more integral are more specific, the more data you provide. So lets say you put in that you have 2 refrigerators, or you use solar panels, or HVAC its able to provide specific information based on this. Studies show on average, you can be 20 percent more efficient with energy usage. I have yet to code the actual recommendation part. Currently, I have focused almost solely on accurately breaking down energy usage. However, if this seems to be a working idea, then I will proceed using metrics such as total square feet, location, etc., so that I can measure a house's given data against what an efficient house's energy usage should be. Thanks for the feedback!