We built this project with the motivation of suggesting the best use of renewable sources of energy which in turn affects sustainability on a large scale. It analyses weather data from a data set that involved hourly forecast from the days of 1st October 2012 to 30th November 2017 across 37 cities. The program outputs the better form of renewable technology after matching temperature and wind speed that is ideal for solar panels and wind turbines. We built the backend by programming python and training data model using the K-means algorithm. The front end was built by using the bootstrap framework and javascript. An ideal dataset was difficult to find and it took some time for both front and backends to communicate clearly with each other, however, we coded through and figured out how we could make a fluid application. We are proud of making an application that has real-life value and we hope that we can expand this period for eco-friendly consumers.

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